Supervising what you cannot inspect

by Maninder Singh Juneja and Renuka Sane.

In traditional financial regulation, supervisors are able to inspect the thing being regulated. For example, a scorecard by a bank was usually a short list of factors that one could comprehend. These factors could be traced to key documents within the bank, banks had a stated rationale for why they were being used, and there was some common sense in making weighted averages. The scorecard itself was static - the same weighted factors were applied over a period of time. Inspecting this process of constructing the scorecard and using it for management decisions was how trust was built. The AI world is different. Models are rented rather than built, change continuously, and behave probabilistically. They cannot be fully inspected even by the institution deploying them let alone by the regulator.

How should we then think of regulation?

One approach is to intensify the traditional approach where regulators demand more explainability, more documentation, and more validation. This will drive up the costs of compliance. But more importantly, this is ill suited to the new world where the technology changes rapidly, where the bank does not control the AI it uses, where there is no clear artefact that the bank can give the supervisor such as a model or a document (Board of Governors et al 2026). When regulators push traditional approaches, banks will respond by choosing AI models which are easy to document rather than the ones best for them, or defer AI deployments altogether. All these are unhappy consequences. What we need are policy makers who understand the live systems of the new world.

In this article, we analyse these emerging problems from first principles. We start from scratch, understand the landscape of market failure in the world of AI in banking, and think about how regulators can grapple with this world.

Our key idea is that AI systems resist replicability. Regulatory strategies that demand replicability will flounder or choke technology deployment. We suggest the regulatory standard applied should be AI deployments that are "supervisable" - the outcomes should be observable, they should be attributable to causes, and reversible by humans.

How AI is actually deployed

Before we get to the puzzles faced by regulators, we need to describe what AI in banking is. This categorisation is not unique to banking. Banking is simply where their consequences are regulated. Five modes span the range.

AI as Tool: AI augments a step, a search, a calculation, a first draft that the human controls. The human is cognitively engaged.

AI as Collaborator: The human and AI co-produce iteratively, and the human participates at every stage.

AI as Recommender: AI generates scores or options, and the human makes the decision. This is the classic human-in-the-loop, but credible only if the human can meaningfully interrogate the recommendation and not degenerate into cognitive surrender.

AI as Preparer: AI does the work and the human signs off. The approval here is closer to a check by a supervisor rather than a re-derivation.

AI as Autonomous executor (agentic AI): AI executes autonomously inside guardrails and the human monitors on exception. Emerging forms of agentic AI for banking run from single-task agents (a payment released, a service query resolved) to multi-step workflows and customer-facing agents that transact.

A central issue here is the true (de facto) role of the human. A reviewer who approves a thousand recommendations a day is not overseeing a model, the model is overseeing her. A feature of any deployment is the measured divergence between the model recommendation (and estimated uncertainty) vs. the human decision. Managers of banks will need to worry about relapses of human behaviour inside the organisation, a bit like how hospital managers worry about bad behaviour by doctors within their organisation.

What AI does to market failure in banking

We now shift gears to look at the standard knowledge on market failure in banking. Regulation may be justified when (and only when) there exist market failures which cannot self-correct fast enough, and there is adequate state capability in banking regulation to be able to correctly identify them and intervene. AI's distinctive feature is that it can cure several classic failures. Better default prediction reduces credit rationing, better fraud detection cuts deadweight loss, richer risk assessment lets banks serve customers they previously could not price, AI advisors help customers avoid some malpractices by the bank. But there are also some new problems that are anticipated.

Information asymmetry: This happens in banking at two levels: borrower-to-lender (adverse selection, hence credit rationing) and firm-to-consumer (product complexity, hence mis-selling). AI narrows the first through alternative data and may widen the second. On one hand, the customer armed with AI can see through many things proposed by the bank which are not in her best interest. But the consumer cannot observe why they were shown a product, offered a price, or steered toward a specific insurance plan. The sales process itself becomes more opaque. Personalised pricing approaches first-degree price discrimination, extracting consumer surplus. A single flawed model can mis-sell to millions simultaneously, converting isolated conduct failures of the pre-AI world into a big correlated event. And redress weakens when a denial comes from a model the firm itself cannot explain.

Systemic externalities from shared infrastructure: Each bank chooses its models, data sources and vendors to optimise its own performance. When multiple entities choose the same ones, the sector's exposures become correlated, which is a cost no individual bank prices in. We list the vulnerabilities below:

Correlated model risk: banks on similar models and the same foundation providers respond identically to an event. The regulator, at the system level, has to manage what happens when institutions move together, because no single entity has experience of such behaviour or of the impact synchronisation adds.

Third party concentration: one vendor's failure propagates everywhere at once. India has already run this experiment, when a ransomware attack on one shared technology provider knocked roughly three hundred cooperative and regional rural banks off the payments network.

Correlated cyber breach: shared stacks mean one exploited vulnerability is every institution's vulnerability. AI lowers the attacker's costs (automated vulnerability discovery, deepfake social engineering) and adds new attack surfaces (data poisoning, model inversion, prompt injection against agents that can move money).

Runs on banks at level 3. The bank runs of old were a queue on the pavement. Then we got to Silicon Valley Bank where over a weekend, customers took away money from the bank. Now we can be at level 3: autonomous agents managing customer cash can turn a shared signal into a self-reinforcing run at machine speed.

The various market failures listed above behave differently across the five modes of AI use. For example, when a human constructs the offer, opaque pricing can get contained. However, when an agent personalises autonomously at scale, this may become severe. Systemic correlation is moderate when AI advises and severe when fleets of similar agents act simultaneously. Any regulation that grades by model type alone, or by use case alone, misses half the object. The next question is the mode of regulation itself.

Regulatory strategy

Regulation can work in two ways. Process-based regulation is ex ante: it prescribes how the firm must operate, defines required controls, mandates oversight, validation standards, limits on autonomy. Outcome-based regulation is ex post: it prescribes ends, fair treatment, solvency, and judges results, leaving the choice of methods to the firm.

Outcome-based regulation is the efficient default. It is technology-neutral, so it does not ossify as methods change; it lets firms find the least cost route to compliance; and it does not require the regulator to understand the firm's production function better than the firm does. But it has important preconditions: the outcome must be observable and measurable; it must be attributable to the firm and, ideally, to the cause; and the harm must be reversible or compensable. Process regulation is the right departure from the default when those preconditions fail and where outcomes are unobservable, harm is catastrophic or irreversible, or damage manifests only systemically or with a lag.

Traditional doctrine treats these preconditions as given: examine the activity, choose the mode. This does not work for AI. Whether an AI deployment's outcomes are observable, attributable, and reversible is an engineering choice, which needs to be settled at design time. We suggest that regulation should mandate observability. This makes it possible to have an "outcome-based supervision" model. There are three ways to ensure observability.

1. Telemetry implies that the institution keeps a track of every decision such that the system records which version of itself it was using, what information it was given, and any time a person stepped in to overrule it. This makes outcomes attributable. That way if a certain group starts getting more (or less) approvals than before, the organisation can evaluate what caused the shift - was it the model, or the group itself. Such a capability is being mandated elsewhere in the world for similar use-cases (European Parliament and Council of the European Union, 2024). The regulator should also consider if it wants to set a minimum common telemetry standard.

2. Boundaries and rollback include putting caps on what the system is allowed to do, rolling out new updates to just a small number of cases first (instead of everyone at once), and having a tested plan for switching back to the older version if something goes wrong. This ensures that if a bad update slips through, it only affects a small slice of decisions.

3. Probes make bias observable. One way is "paired testing": one submits two applications that are exactly the same except for details that hint at things like someone's race or gender, and see if they get treated differently. One can also compare approval rates against the company's own normal levels. Together, these checks can catch an unfair credit model in just a few weeks, instead of waiting years to see who actually pays back their loans. One can also check rejected applicants against credit-bureau data to see which ones got approved by someone else, and how they fared.

These are similar to the idea of decision receipts that record which rules were applied to which facts and in what sequence for every decision made by a government or public system (Srivastava, 2026).

Over time, the supervisor should also build a repertoire of its own test cases drawn from incidents, complaints and examinations across the system and run it against every material AI deployment, much as stress-test scenarios are run against every balance sheet today. This will ensure that what surfaces in one institution becomes a probe for all others. It thus allows the regulator to set its own observability layer.

Process regulation is then reserved for the harms that are systemic, correlated, or irreversible at machine speed. For such events there need to be protections such as circuit breakers that halt things before they cause damage, limits on how much the systems can do on their own, model diversity so they don't all fail the same way, and rehearsed back-up plans.

What follows for the supervisor, the board, and the customer

For the supervisor: The unit of examination shifts from the model to the deployment, and the examiner's question shifts from "show me the validation report" to "show me the behaviour": what boundaries were set, what exceptions were thrown, what overrides were exercised, how far the system drifted from its baseline. Supervisors will also need to find the intellectual clarity to avoid a wide variety of extraneous claims about regulation of AI, e.g. the push for economic nationalism which has nothing to do with market failure.

For the board: A board cannot certify systems it cannot inspect or understand. Its role is to govern the framework which includes the limits on what the system is allowed to do, and making the rules for when a decision must be escalated to a human. The board then needs to continuously check the exceptions and overall performance.

Exception-handling should also be written into policy. If a problem stays unresolved beyond a defined size or time limit, it automatically gets escalated to the board. Internal auditors should double-check that the numbers are real. The board sticks to this audited framework and does not inspect the system directly.

If a board is asked to approve something they can't understand, they will default to saying no. But if you let them govern the limits and the exceptions instead, they can say yes.

The customer: The customer becomes part of the supervisory architecture. The widening firm-to-consumer asymmetry has a structural corrective the pre-AI world lacked: the customer now has AI too. Mainstream assistants abroad have begun connecting directly to users' accounts. If product terms (rates, fees, eligibility criteria) are mandated to be structured and machine-readable, the customer's own AI does the comparing, the explaining, and the policing of mis-selling, continuously and at zero supervisory cost. The redress channel weakened by opacity is restored the same way: an adverse decision should carry its reason to the customer, and what would have had to be different for the answer to change. This restores the ability to contest. The same asymmetry that AI widened, AI-equipped customers can close, but only if regulation hands them the data.

An example

Consider a debt-collection example. When borrowers fall behind on payments, the bank has to decide how to chase each overdue account. Contact methods differ in cost. Automated SMS and IVR (the automated phone system - "press 1 to pay") are cheap; having an employee actually phone the customer is expensive. So the bank builds a model that allocates accounts: cheap automated nudges for most, and the costly human call reserved for the accounts where the model predicts that talking to a person will actually "cure" the account (get it back to paying). Human calling works better but it costs more. The model is rationing an expensive resource to where it thinks it'll pay off.

With AI, the collection systems would retrain continuously or run reinforcement-style optimisation against a live reward (cure rate per rupee spent). The model would be moving on its own, faster than the review cycle, toward a target that is a proxy for what the bank may actually want. Under the conventional "inspect-the-artifact" approach, the model is checked before deployment, signed off, and reviewed on a schedule (say quarterly or annually). However, if AI is an active optimiser, a quarterly review discovers deterioration only after it has touched thousands of accounts. It may drift toward a mis-specified target in a way no one can read off the model itself. Further, if the collections model is a shared vendor product, or several banks fine-tune the same foundation model on similar data, they all go bad the same way at the same time when borrower behaviour shifts. In contrast, in a "supervisability-built in by design" approach, a small slice of accounts is deliberately kept on the previous allocation method, running live alongside the new model. This allows comparison between the old and the new in real time.

Every decision should keep a record of a few things: which version of the AI was used, what action it chose, which group of customers it was dealing with, and how things turned out in the end. This is how it helps: Say the AI's overall success rate is going up, but one particular group is quietly getting fewer phone calls from real people and doing way worse because of it. With all that recorded, that gap shows up right as it's happening. You can compare it against what's going well elsewhere, trace it back to a specific version of the AI, and undo it that same day, because the older setup is still up and running as a backup.

The company should never have to dig into the AI's inner "thought process" to realize its behaviour has taken a bad turn. None of this replaces the normal testing that the firm would do anyway. The difference is that here, the ability to observe what's happening, pin down what caused it, and shut it down are all built right into the system from the start, instead of being things you have to go do to the AI afterward.

Conclusion

AI deployments sit uneasily in conventional mores of banking regulation. The intelligence is rented, the behaviour is probabilistic, and harms can move at machine speed. We suggest that the response should not be more inspection of what cannot be inspected, nor blind faith in outcomes that arrive too late. Efficient regulation will emerge from observability, attributability, and reversibility. Regulators should require banks to build these.

References

Board of Governors of the Federal Reserve System, Federal Deposit Insurance Corporation, and Office of the Comptroller of the Currency. "Supervisory Guidance on Model Risk Management." SR Letter 26-2. April 17, 2026. https://www.federalreserve.gov/supervisionreg/srletters/SR2602.pdf.

European Parliament and Council of the European Union. Regulation (EU) 2024/1689 (Artificial Intelligence Act), arts. 12, 26(6), and Annex III(5)(b). https://ai-act-service-desk.ec.europa.eu/en/ai-act/article-12.

Srivastava, Manish. "Digital Governance Needs Decision Receipts." Episode 73 of Big Ideas. XKDR Forum, June 1, 2026. Podcast, video, 13:06. https://youtu.be/WFX4ITb9yok

Unsophisticated households and banks versus securities

by Ajay Shah.

The borrowing of banks through deposits

When a household deals with a bank, there is a clear promise by the bank, that the deposit will be redeemable at par with some interest that is known up front. But how is a household to verify that the promise will be met at future dates? Monitoring a bank every day is hard for unsophisticated investors. Unsophisticated households face asymmetric information, a market failure.

In order to address this market failure, we do two things in financial regulation. First, we have micro-prudential regulation. The regulator coerces banks to bring down their failure probability to an acceptable level. A good thumb rule for Indian conditions is to aim for a failure probability of 2% on a one-decade horizon. This requires two elements of work: forcing banks to mark their assets to market so that bad loans are valued at fair market value, and a leverage rule which caps the leverage of banks. Second, we require a Resolution Corporation to deal with bank failure: a specialised bankruptcy process, which pays out deposit insurance to households (Rai, 2017).

This is the well understood regulatory apparatus that is brought into play when banks borrow through bank deposits, which go alongside high intensity promises.

Resource mobilisation by firms through the securities markets

How should we think about households and investment in securities (equity or debt)? Conversely, what should a financial regulatory apparatus do when a firm (a bank, an NBFC or a non-financial firm) wants to issue shares or bonds on the primary market?

A key difference on the stock market or the bond market is the lack of a promise. No promise is made, either about liquidity or about the price at which a future transaction will take place. This immediately improves the situation from a regulatory standpoint. Investors walk into buying bonds or shares with their eyes open, no promises are made to them.

Hence, we do not need to worry about micro-prudential regulation of the issuer when an investor buys shares or bonds on an exchange.

What about the primary market? In a primary issue, there is the risk of an advertising campaign that makes lurid promises to unsophisticated investors. This is addressed nicely by having a rule which requires that a minimum x% of the primary issue (of either bonds or shares) be purchased by sophisticated investors, and these investors be locked in for a certain short period. A good definition of a `sophisticated investor' for this purpose is a person who invests a minimum of Rs.10 million in the issue. Once the issue passes the market test of appealing to such investors, it is safe for households to participate directly in the primary market for securities.

Under such conditions, the gatekeepers for resource mobilisation through the primary issuance of shares or bonds are sophisticated investors and not the state. If a firm had poor prospects, or mispriced its securities, it would not get the support of these investors, and the issue would fail. How much leverage, and what debt characteristics, are appropriate for a highway or a steel company or an NBFC? There is no need for the government to get involved in terms of micro-prudential regulation or interference in the price. The only role of the state is in the adequacy and truthfulness of disclosures that are made at the time of the issue.

As there is no high intensity promise by an NBFC, failed NBFCs should go to the ordinary IBC process. The need for the Resolution Corporation, in handling firm default, is only when a systemically important NBFC fails.

When a bank borrows using the bond market, this changes the overall leverage of the bank, and the bank would of course have to comply with micro-prudential rules that cap its leverage. But there is nothing special about the primary issue of a bank, when compared with the reasoning above.

Conclusion

NBFCs in India are facing many difficulties. However, micro-prudential regulation of NBFCs is not the answer. There is no need for the state to get involved, or engage in micro-prudential regulation, of bond issues by banks, NBFCs (Roy, 2015; Shah 2018) and non-financial firms.

The sophisticated investors on the primary market are the gatekeeper; unsophisticated households free ride on their price discovery.

The Companies Act should not interfere in the bond issuance of companies, and RBI should not micro-prudentially regulate NBFCs.

The reticence of the bond market in lending to some NBFCs, from August 2018 onwards, is market discipline at work.

References

The regulatory difficulties of NBFCs in India, Shubho Roy, The Leap Blog, 24 December 2015.

Movement on the law for the Resolution Corporation, Suyash Rai, The Leap Blog, 19 June 2017.

Financial regulation for the Fintech world, Ajay Shah, The Leap Blog, 21 March 2018.

Credit stress in large Indian firms

by Ajay Shah and Pramod Sinha.

We in India are used to thinking about banks and NPAs. We infer the state of difficulty of the banks, and indirectly of their borrowers, by using data from banks. There are many advantages in looking directly at the state of credit stress in the large non-financial firms, and identifying the firms where there is high credit stress:

1. Do not rely on bank information. This evidence is not filtered through the difficulties of banking regulation. Whether a bank classified Kingfisher Airlines as an NPA or not, we can see credit stress in the financial statements of Kingfisher Airlines.
2. Look beyond banks. Banks are not the only financial lenders to the non-financial firms. As an example, bank-centric thinking is not useful in understanding runs on mutual funds. When there is stress in a borrower, this impacts not just on banks but on all lenders. Pulling together information about stressed borrowers helps us see the difficulties of lenders, on a financial system scale, and not just in banks.
3. Micro-prudential considerations. The stressed firms face likely defaults. The debt of such firms is likely to be worth less than book value. Under sound micro-prudential regulation, banks and other lenders should mark down these assets, even if no default has taken place. The extent of stress, as seen here, gives us insights into the fragility of banks and other lenders.
4. The bankruptcy process, the distressed debt industry. There is a new world opening up in India, of distressed firm transactions and the bankruptcy process. We will see the empirical contours of this industry, and the bankruptcy process, by examining the state of credit stress in the non-financial firms.
5. A drag on growth. A firm that is in a state of credit stress is likely to face difficulties meeting payments to creditors. It might often be liquidity constrained, and may struggle to obtain cash to pay its suppliers. The mind space of the leadership of such a firm is likely to be absorbed in the struggle for survival. Such firms are unlikely to fare well on growth through increasing the resources utilised or through increased productivity. To understand what is coming in Indian macroeconomics, we should look at the non-financial firms and their balance sheet difficulties.

Identifying stressed firms

The interest cover ratio is defined as PBIT/interest. If a firm has to make interest payments of 100, and if its profit before interest and taxes is 150, then its interest cover ratio ("ICR") is 1.5. Such a firm has the 100 required to pay interest in the year, but there may be a task in terms of juggling the dates on which interest has to be paid versus the dates on which the business produces cash. And, such a firm is left with just 50 after paying interest, which can be used for debt repayment and the regular capital expenditures required for the upkeep of the business.

A good thumb rule which identifies a firm in a state of stress at time $t$ is: The firm has ICR$ < 1.5$ in year $t$ and in year $t-1$. This avoids the false positive of a firm which only hits ICR$<1.5$ for one year.

A `stressed firm', by this definition, is not necessarily one that has defaulted (and is thus eligible for the bankruptcy code), and it is not necessarily one that is classified as a non-performing asset by RBI's rules of recognition. We would, however, suggest that a firm with two consecutive years at an ICR of below 1.5 is under stress, has an enlarged risk of default, and has a management team that is absorbed in dealing with this stress.

Methodology

We study all the non-financial firms in the CMIE database. At each year, we isolate the firms which are observed for two consecutive years. Some additional sanity checks are applied. Through this, we are able to construct two sets at each point in time: The set of all firms observed and the subset of this, which is the stressed firms.

Here are some counts of the firms in the two sets.

Year	Total	Stressed
2014-15	9,289	3,674
2015-16	9,208	3,702
2016-17	6,687	2,573

In the table above, the total number of firms (9,289) for 2014-15 is the number
of non-financial firms that are observed, and pass some sanity checks, in both 2013-14 and 2014-15. Of these, 3,674 were stressed. The last year that we utilise here -- 2016-17 -- has fewer firms when compared with the years prior to
it, where information for a larger number of firms has trickled into the CMIE database. In this last year, we see 2,573 non-financial firms in the database, where the ICR was worse than 1.5 in both 2015-16 and 2016-17.

Conditions in 2016-17

Parameter	Value (Rs. Tln)
Balance sheet size
Stressed firms	29.79
All firms	77.24
Bank borrowing
Stressed firms	8.87
All firms	14.94
Total borrowing
Stressed firms	15.58
All firms	27.59

This shows that the sum of the balance sheet size for all the 6,687 firms for 2016-17 was Rs.77.24 trillion. Of this, Rs.29.79 trillion was in the 2,573 stressed firms.

Totally, borrowing of Rs.27.59 trillion was visible. This is small when compared with the total assets of these firms of Rs.77.24 trillion. Of this borrowing, Rs.15.58 trillion was in the stressed firms.

Finally, we are able to see Rs.14.94 trillion of borrowing from banks, in this sample of 6,687 firms, in 2016-17. Of this, Rs.8.87 trillion was in the stressed firms.

How has credit stress evolved over time?

We are able to do these calculations for all years from 1998-99 onwards. We will express the time-series evidence using confusingly similar graphs, all of which produce important stylised facts for our understanding of the economy.

The share of bank debt to stressed firms, in the total bank debt seen in the sample firms

The health of banks is related to the health of their borrowers. Hence, in the graph above, we compare the sum of bank credit to stressed firms (in our sample) against the sum of bank credit to all firms (in our sample).

The business cycle is clearly visible here. In the last tough downturn, 2000-2003, this ratio was at about 50%. That is, about half of the bank borrowing seen in the CMIE database was in stressed firms.

This ratio dropped all the way to about 15% in 2007. It climbed steadily thereafter and is now at about 60%. There is a tiny gain in 2016-17 when compared with the previous year.

In the last recession, this measure improved through the recovery of the economy. Firm exit took place through the sluggish traditional ways. When the bankruptcy reform resolves or liquidates a large volume of stressed firms, this will deliver improvements in this measure. To the extent that the bankruptcy reform works, we may expect the next recovery to proceed faster than the last one, where it took five years of a powerful expansion to get from about 50% to about 15%.

We apply this same thinking to total borrowing -- instead of just bank borrowing:

The share of total borrowing by stressed firms, in the sum of borrowing seen by all sample firms

The last business cycle downturn got to values of above 50%, there was a great decline to about 20%, and then it has risen to about 55%, with a slight improvement in 2016-17.

Implications

There is considerable balance sheet stress. In the latest year, the aggregate balance sheet size of the stressed firms -- observed in the CMIE database -- was Rs.30 trillion. The stressed firms had Rs.15.6 trillion in borrowings of which Rs.9 trillion was from banks. This has implications in other parts of finance, beyond banking.

Bank debt in stressed firms is about 60% of total bank debt seen in the sample. Similarly, the borrowing by stressed firms is about 55% of all borrowing in the sample. Under sound micro-prudential regulation, asset-based lenders would mark down these assets based on the price at which the loan/bond could be sold on the market.

In the conventional wisdom, there is about Rs.10 trillion of bad debt on the balance sheet of banks. Our analysis shows that in the 6,687 large non-financial firms, where Rs.15 trillion of bank debt is located, we see 2,573 stressed firms with Rs.9 trillion of bank debt. The 2,573 stressed firms that we see in this sample, alone, account for 11.4% of the overall bank debt ("non-food credit") in the economy.

The stressed firms are about 40% of the overall corporate balance sheet. These firms are likely to fare poorly in investing or in productivity growth, and are thus a drag upon overall economic growth.

It is likely that many of these stressed firms will be sold, or go into the bankruptcy process. There is a substantial task ahead, in terms of resolving these firms and paying for the losses experienced. These 2,573 firms are the happy hunting ground for this new industry. This process of resolution is central to India's economic recovery.

There is much value in understanding the balance sheet stress in the economy using such methods. We obtain insights into difficulties of the financial system going beyond a bank-centric view, we get a view of the new distressed debt industry, and we get insights into the drag on GDP growth that the stressed firms represent.



The authors are researchers at NIPFP.

There be dragons: Off-balance-sheet liabilities of the Indian State

by Ila Patnaik and Ajay Shah.

Conventional fiscal stability analysis looks at the stock of debt and wonders whether a country can pay off this debt, under reasonable scenarios for future interest rates and fiscal surpluses. In many countries, though, the fiscal sustainability story has turned on promises made by a government which were not explicitly counted in the debt. There are obvious liabilities that are kept off the books - such as debt in public sector companies or state electricity boards. In this article we look deeper, at less obvious ways in which off-balance-sheet liabilities have arisen, and the checks and balances that can contain them.

Off balance sheet liabilities of the government

Off balance sheet items come in two kinds.

1. A promise that looks like the cashflows on a bond. Example: A pension promise to a person is no different from a series of coupons that are paid out every year. Promising a pension is exactly like issuing that comparable bond.
2. A promise that looks like an option payoff. Example: If a government is in hock to pay the lenders of a firm when it goes bankrupt, it is much like being the seller of an option. When governments write guarantees, this changes the risk profile of the exchequer and generates possibilities of large payouts when those options mature in the money.
   It should be noted that organisations backed by statute are not automatically backed by a government guarantee. As an example, in the UTI crisis of 2001, the government had no legal obligation to make good the losses of investors, but a political decision was made to use fiscal resources to pay half the loss. There is a mixture of financial risk ("Will X get into trouble?") and political risk ("Will the government backstop X?").

A correct reckoning of the liabilities of a government should add in these off-balance-sheet liabilities of both kinds. The FRBM Act brought control on one kind of off-balance-sheet liability of the Indian State: explicit guarantees given by the government. But there is more to the problem of off-balance-sheet liabilities than explicit guarantees.

Differences in cost versus differences in transparency

In the field of pensions, an interesting distinction is made between an unfunded defined benefit program vs. a funded defined benefit program that has assets invested in government bonds. In the conventional wisdom, a funded DB program is always superior to a pay-as-you-go unfunded program.

However, these two approaches are exactly the same in terms of the cashflows: both involve a highly predictable set of claims on the exchequer at future dates. To promise a pension is to implicitly issue a bond. This equivalence, between the cashflows of a bond and the cashflows of a pension, has an interesting implication. Consider a funded DB public pension program that invests in government bonds. The two streams of cashflows cancel out.

This approach to funding (holding government bonds) does not make things cheaper: it is only superior in that it is transparent and connects into the fiscal planning process. Cost savings only come about when a funded DB program invests in higher return assets, such as equities, through which the claims upon the exchequer at future dates are reduced on expectation.

What are the important off-balance-sheet liabilities of the Indian State?

Some important components of the off-balance-sheet liabilities are:

• Promises made for defined benefit pensions of civil servants, in particular the new `one rank one pension' (i.e. wage indexed) pensions for uniformed folk, and the underfunded `Employee Pension Scheme' (EPS) that is run by the EPFO. For the civil servants recruited after 1/1/2004, there is no such problem, as these new recruits are in the New Pension System.
• Promises made in a variety of health-related entitlement programs (Patnaik et. al., 2018).
• The temptation to make good the promises made by public sector financial firms, that experience distress in the future, even when there is no explicit guarantee. Of these, LIC has a balance sheet of Rs.28 trillion.
• The temptation to make good the promises made by private financial firms that experience distress in the future, even when there is no explicit guarantee. As an example, will the failure of IL&FS -- a private financial firm -- induce a direct or indirect fiscal impact upon the exchequer? So far, the government has not put money on the table, but could this change?
• The use of fiscal resources in responding to a full blown financial crisis, that may occur at a future date.
• The Parliament has enacted many laws, which could potentially evolve into large inflexible expenditures. These include `Right to education', `Right to food' and NREGS. On a similar note, the promises which are being made under `minimum support price' (MSP) could turn into large expenditures if the future brings together a certain combination of political pressures, jurisprudence and development of State capacity. Until repeal, these laws are a genotype that could, under the right combination of events at future dates, get expressed in a way that involves major fiscal risk.

These liabilities add up to large sums of money, of the same order of magnitude as the overt stock of public debt. Hence, off-balance-sheet liabilities should become more prominent in the Indian fiscal discourse.

How do the incentives of politicians and officials change?

At present, there is no check-and-balance influencing these opaque promises and risks. Each party in power looks to enter into greater off-balance-sheet obligations so as to get re-elected. How might this change?

The key thing that shapes these incentives is financial repression. At present, government debt is mostly sent into involuntary lenders. When the fiscal system graduates from financial repression to voluntary lenders, off-balance sheet liabilities would matter. There are numerous gains from removing financial repression: voluntary borrowing is more efficient than forced borrowing, the magnitude of resources available in a crisis would become greater, etc. But this requires a government that faces a skeptical bond buyer who demands a risk premium based on the extent to which the Indian State may engineer inflation or default.

In India today, there are many loose ends, which periodically induce fiscal surprises. This creates an adverse risk profile of Indian government bonds, and would drive up the required interest rate for borrowing when faced with voluntary buyers of bonds. In such a world of market discipline, when a government dips into LIC's resources, this would induce a higher cost of borrowing.

In India today, most of the attention in fiscal reforms lies upon tax policy reforms, such as the GST and the Direct Tax Code, and there is some interest in FRBM. There is much more to a mature fiscal system, including the issues of tax administration, debt management, the bond-currency-derivatives nexus, off-balance-sheet liabilities, accrual-based accounting, and the budget process. We need to broaden our research and policy work to address this full range of problems.

Tracking and understanding off-balance-sheet liabilities, communicating them to lenders, and communicating these concerns back into the budget process, is part of the work program of the future Public Debt Management Agency (PDMA) (Pandey and Patnaik, 2017). A Fiscal Council will help. Accrual based accounting will help.

Once we start paying attention to off-balance-sheet obligations, this creates fresh impetus for economic reform in many areas. As an example, if a monsoon failure induces a farm loan waiver paid for by the government, this is like a monsoon derivative that has (maybe) been written by the government. When reforms of personal insolvency and reforms of agriculture remove this possibility, the risk profile of the Indian exchequer will improve, and the cost of borrowing will go down.

Off-balance-sheet liabilities and financial reform

There is a close connection between public finance and finance, centering around the government bond market and the PDMA. For public finance, PDMA and the government bond market are the source of debt. For finance, the PDMA is the biggest investment banker of the country and the government bond market is the tool for low risk transfers of resources across time. What is less widely noticed is the intimate connection, between public finance and finance, through the question of off-balance-sheet liabilities.

How will off-balance-sheet liabilities change when micro-prudential regulation improves and the resolution corporation is setup? Financial firms will face distress less often, we will discern that distress early, and we will have an institutional mechanism to put the distressed firm down. Conversely, under present conditions, we get surprised by the difficulties in an IL&FS or in a UTI. These crises lead to a political question being thrust upon the leadership: Will you make liability-holders happy by using taxpayer money? We should, of course, have a mature political system which is able to turn down such requests most of the time, but we should have a mature financial regulatory system so that these situations do not arise in the first place.

Governments worldwide have faced claims on fiscal resources when dealing with full blown financial crises. The probability of occurrence of such crises, and the severity of such crises, is shaped by the institutional capacity in systemic risk regulation. The FSLRC apparatus for systemic risk regulation -- the Financial Stability and Development Council (FSDC) and its information system, the Financial Data Management Centre (FDMC) -- will reduce fiscal risk and thus the cost of government borrowing. As an example of the work program which should take place through FSDC/FDMC: At present, we have the possibility of runs on mutual funds (Sane et. al., 2018), which can lead to a full blown financial crisis, which requires policy thinking and reforms on a financial system scale.

Our objective in financial economic policy should be: to be as sparing as possible in ever asking for resources from public finance policy. For a sound fiscal system, we require financial sector reform. This will have a beneficial impact upon contingent off-balance-sheet liabilities and thus the cost of borrowing.

The need for a research community and a research literature

A remarkable feature of the existing Indian policy process is that no fiscal estimation was done in the policy process that led up to the announcements  about one rank one pension, or the various health insurance programs.

Even if policy makers had tried to reach into the research community to obtain such estimates, the state of data and knowledge is weak, and it is difficult for policy makers to obtain policy support from researchers. Some early work on the civil servant's defined benefit pension (Bhardwaj and Dave, 2005), one rank one pension (Sane and Shah, 2015) and banking (Shah and Thomas, 2000) is available. Much more needs to be done in this important field.

In an ideal world, record level data would be available from the government which would permit estimation of the value of the implicit debt or the implicit derivatives that the government has issued. The state of information systems and transparency of government is often a bottleneck, and creative research strategies have to be employed. As an example, Bhardwaj and Dave, 2005, utilise data from a national scale household survey to identify present and future beneficiaries of the traditional DB civil servants pension, and extrapolate the sample estimates to an estimate of the implicit pension debt associated with the traditional civil servant's DB pension. Similarly, Shah and Thomas, 2000, exploit information in stock prices to estimate the equity capital gap in banks, which helps overcome the opacity of banks and banking regulation.

A research community is required, which will build a research literature in estimating these expenditures based on exploiting diverse datasets. There will, of course, be multiple different estimates, as different researchers search for useful approximations through different assumptions and modelling strategies. A coherent picture will emerge from these debates. The PDMA, and buyers of government bonds, will be important users of this research community.

Off balance sheet liabilities and GDP growth volatility: A conjecture

There is a big gap between short spurts of GDP growth and sustained GDP growth. A mature market economy is a turtle, it plods along for a century, obtaining a low rate of growth on average, and harnessing the power of compounding. Poor countries fail to get sustained growth. The striking fact in cross-country comparisons is how volatile the GDP growth of poor countries is.

What might be going on? An analogy from a different field is useful. A well known problem in financial portfolio management is the returns that can be obtained, in the short term, by selling out-of-the-money options. For some time, the option seller seems to make a lot of money. But in time, some of those options get exercised and the portfolio gets into a lot of trouble. In similar fashion, for some time, a government that takes on option-like off-balance-sheet liabilities can gain votes and possibly accelerate economic activity, at the cost of sustainability.

Perhaps one element of the high GDP growth volatility of poor countries runs as follows. Mature fiscal systems create checks-and-balances which reduce the extent to which debt or off-balance-sheet liabilities can surge. Perhaps less developed countries have weak institutions, and then the political leadership sees a different optimisation. Short bursts of GDP growth can then be achieved in many bad ways, such as a surge in debt, piling up off-balance-sheet liabilities, etc. But this is not sustained growth: We get a spurt of high growth, and then things go wrong. This yields one more element of the translation of bad institutions into high GDP growth volatility.

References

Bhardwaj, Gautam and Surendra A. Dave, 2005. Towards estimating India's implicit pension debt, Working paper.

Pandey, Radhika and Ila Patnaik, 2017. Legislative strategy for setting up an independent debt management agency. NUJS Law Review, 10(3).

Patnaik, Ila, Shubho Roy and Ajay Shah, 2018. The rise of government-funded health insurance in India. NIPFP Working paper.

Sane, Renuka and Ajay Shah, 2015. What is the cost of one-rank-one-pension? The Leap Blog.

Sane, Renuka, Ajay Shah, Bhargavi Zaveri, 2018. Runs on mutual funds, The Leap Blog.

Shah, Ajay and Susan Thomas, 2000. Systemic fragility in Indian banking: Harnessing information from the equity market. IGIDR Working Paper.



The authors are researchers at the NIPFP in New Delhi. We are grateful to Shubho Roy, M. Govinda Rao and Arbind Modi for useful discussions.

Fair play in Indian health insurance

by Shefali Malhotra, Ila Patnaik, Shubho Roy and Ajay Shah.

India's National Health Protection Scheme (NHPS) aims to be the world's largest government-funded health insurance programme. As in the existing government-funded health insurance schemes, health insurance companies are likely to play a crucial role in the implementation of NHPS. In addition, the number of Indians purchasing health insurance (on their own) has grown in the past few years. Of the total out-of-pocket expenditure (80% of the total health expenditure), payments for health insurance premium have increased from 5.28% in 2013-14 to 6.51% in 2015-16. However, all is not well in this growing industry. This has raised concerns of fair play and efficiency in the industry.

While there is some literature on consumer protection concerns in the overall insurance industry, the existing literature on the health insurance industry in India is sparse. In a new paper, Fair play in Indian health insurance, we study the functioning of this industry through an analysis of the claims ratio and the complaints rate.

Efficiency in the insurance market is commonly measured through the claims ratio. The claims ratio is defined as the percentage of the total premium collected that is paid out as claims by an insurer. Claims ratio close to (but less than) 100% indicates that the insurer is efficient (low operating costs). Claims ratio above 100% indicates that the insurance company is paying more than it is collecting as premium. This implies that the insurance company is unsustainable and may go bankrupt. When the claims ratio is too low, there are concerns about consumer protection. It indicates that the insurer is charging too much from the consumers. Figure 1 shows the range of claims ratio that insurance regulators use as an indicator for the insurer's quality.

Fig 1. - Regulatory concerns associated with the claims ratio.

Our analysis of the claims ratio shows that the functioning of the Indian health industry is neither desirable nor sustainable. A part of the industry, the private stand-alone health insurers, appear to be overcharging its consumers. Between 2013 and 2016, the claims ratio of these insurers fell from 67% to 58%. Such low claims would have triggered mandatory refunds if these insurers were operating in the US. However, there are no regulations mandating minimum claims ratio in India. Another part of the industry, the government insurers, suffers from financial fragility. Group insurance businesses and government-funded health insurance schemes also raise concerns related to insolvency. We conclude that the evidence from claims ratio raises concerns about consumer protection and micro prudential regulation.

In addition to the claims ratio, the complaints rate is used to measure the quality of products in the insurance industry. The complaints rate is the number of complaints made by consumers of insurance (to a third party) in a year per million persons covered. Our analysis of the complaints rate shows that India has the highest complaints rate when compared with other common law jurisdictions: Canada, Australia, UK and California. This finding is probably conservative for two reasons. First, unlike other jurisdictions, Indian health insurance only covers hospitalisation. In addition to hospitalisation, other jurisdictions provide clinical visits, medication and some wellness care under health insurance. Thus, increasing the number of touch points and transactions, where failures can generate complaints. Second, India is a less litigious country than other jurisdictions. So, we must adjust the Indian complaints rate with the litigation rate (civil suits filed per hundred thousand persons). Table 1 is our estimation of the complaints rate in India and the compared jurisdictions for 2015-16. The last column is our estimation of India's litigation rate adjusted complaints rate (Column 3).

Table 1: Complaints rate for the year 2015-16 (Source: Authors' calculation)

Country	Complaints rate	India's complaints rate
	(2015-16)	(Adjusted)
India	360.72	-
Australia	178.51	1607.48
Canada	11.53	1511.81
UK	337.54	3837.44
California	351.19	6052.34

Putting these two factors together, we view the complaints rate that prevails in the Indian health insurance industry as a source of concern. We also read a large number of court orders settling health insurance disputes. One common thread which stood out was the absence of complexity in these disputes, most relating to arbitrary and illegitimate rejection of claims by the insurers.

When we investigate the sources of these problems, they are traced to infirmities in the regulatory framework governing the health insurance industry. We identify three issues in the regulatory framework. The first issue is deficiencies in the existing regulations. For example, the regulations are not clear on disclosures that insurance companies should make to its consumers, the manner in which disclosures should be made and the procedure for settlement of claims. The second issue is poor enforcement of existing regulations. The insurance regulator and the insurance companies seem to easily bypass their obligations under the regulations without any repercussions. The third issue is fundamental deficiencies in the design of the insurance ombudsman, in so far as its offices and day to day administration is controlled by the insurance industry. We then engage in a comparative law analysis, where each of these issues is analysed with respect to the legal systems of Australia, South Africa, US and UK.

Finally, we turn to existing strategies for reform in the Indian insurance sector. Financial Sector Legislative Reforms Commission, provides insights into the approach to consumer protection for financial services. The report comprises of two volumes. Volume I is "Analysis and Recommendation". Volume II is the "Indian Financial Code", a model law for the regulation of the financial sector. We engage in counter-factual analysis of the three identified issues in a hypothetical world, where the Indian Financial Code was enacted. We find that all the three issues are suitably addressed. We conclude that the Financial Sector Legislative Reforms Commission, provides an intellectual framework through which the problems of health insurance can be understood and solved. Implementation of these measures will have positive implications for health insurance in India.

The authors are researchers at the National Institute of Public Finance and Policy.

Financial regulation for the fintech world

by Ajay Shah.

In India, there is a confusing term `non-bank financial company' (NBFC). This is an unfortunate phrase as the term, when taken literally, includes insurance companies, etc. In India, it denotes a $10 \times 2 \times 2$ classification of business models which are regulated by the RBI.

There is a lot of confusion in the present regulatory treatment of these classes of firms. The existing levers of regulation are inappropriate, and it is not clear why RBI -- which should be about sound money and sound banking -- is doing all this work. These concerns are becoming particularly important in the context of the fintech revolution, where all kinds of new firms are being shoe-horned into NBFC regulation.

It's hence useful to take one step back and think about  financial regulation from first principles. Where and why is financial regulation required? Financial regulation is based on exactly four motivations:

1. Consumer protection. Financial firms generally require a layer of restrictions, that impact upon their dealings with customers, that improve fair play. These problems are heightened when the financial firm directly deals with unsophisticated individuals.
2. Micro-prudential regulation. When a financial firm makes a high intensity promise to a consumer, generally there is a need for restrictions upon the risk-taking by the firm, to curtail the probability of firm failure. Such micro-prudential regulation is  (in turn) motivated by consumer protection: we wish to improve how consumers are treated in their dealings with the financial firm. When a firm takes a deposit from a household, that requires micro-prudential regulation, but when the firm lends to a household, the household is quite comfortable with the prospect of firm default, and no micro-prudential regulation is required.
3. Resolution. When a financial firm makes promises to consumers, or when a financial firm is systemically important, the conventional bankruptcy process (of IBC) is inadequate. A specialised bankruptcy process is required, which is run by the Resolution Corporation. 
4. Systemic risk regulation. The behaviour of firms needs to be restricted from the viewpoint of systemic risk. This is mostly about system thinking, and not looking at individual firms ("the woods and not the trees"). But one ("trees") element of this tends to be a reduced target failure probability for a few firms which are termed `systemically important'.

FSLRC drafted the Indian Financial Code (version 1.1, 2015). The four components of financial regulation show up there as:

1. Part VII which does consumer protection (S.105 to S.151)
2. Part VIII does micro prudential regulation (S.152 to S.184)
3. Part XII does resolution (S.286 to S.310). This has morphed into the FRDI Bill.
4. Part XIII does systemic risk regulation (S.311 to S.341).

This treatment is non-sectoral. There is no special law which defines consumer protection for banks vs. consumer protection for mutual funds. All kinds of financial business is treated identically, within these four components. The advantage of  non-sectoral law is that the law does not have to be modified when new business models are invented, or when multiple kinds of activities are undertaken under one roof.

Now let's apply this thought process to what, in today's India, would be called an NBFC. To keep things simple, consider a company which finances itself using the bond market, has no unsophisticated consumers, and gives out loans to companies. How would we think about regulating this?

1. Consumer protection: As this firm has no unsophisticated customers, this simplifies the problem of consumer protection. See Table 5.5 in FSLRC Volume 1. The protections that would have to be enforced are: professional diligence, unfair contract terms, unfair conduct, privacy, fair disclosure and redress.
2. Micro prudential regulation: As this firm makes no promises to unsophisticated individuals, there is no need for micro-prudential regulation. The bond market is what will discipline the risk taking of this firm. This is similar to how the bond market shapes the leverage and access to debt capital of an ordinary non-financial firm.
3. Resolution: Ordinary IBC processes will suffice to deal with failure. The bond market will reward more resolvable businesses with a lower cost of capital.
4. Systemic risk regulation: Until the balance sheet becomes 1 per  cent of GDP, i.e. $20 billion, the firm is not systemically important.

By this logic, for most NBFCs, there is a need for a little bit of consumer protection and nothing else. Most of the existing edifice of NBFC regulation, which seems to be inspired by the regulation of banks, is not required.

Enacting the Indian Financial Code addresses this situation at two levels. First, as described above, it gives a clear conceptual framework on how to think about financial regulation, without encoding business models into the law. Second, the FSLRC regulation-making process encourages the institutionalised application of mind. When mistaken ideas start out in the regulation-making process, there will be greater push back. The staff of financial agencies will rise to higher quality thinking when placed into the FSLRC regulation-making process.

In a previous article, Renuka Sane and I wrote about the barriers faced for the Fintech Regulatory Sandbox. The question discussed here -- the problems associated with shoe-horning fintech into the NBFC framework -- connects integrally to that. Once a project is proven in the sandbox, it will come out into the regulation making process. If the concepts and principles of the regulation-making process have basic defects, this will hamper the working of the regulation-making process, and yield poor outcomes.

Movement on the law for the Resolution Corporation

by Suyash Rai.

Capitalism without bankruptcy is like Christianity without hell.
- Frank Borman

On June 14th, the Union Cabinet approved the proposal to introduce a Financial Resolution and Deposit Insurance Bill, 2017 ("the FRDI Bill"). This is an important step forward for a critical component of the overall strategy of India's financial sector reforms. Shaji Vikraman has insight on this in the Indian Express. In this article, I look deeper into the concept of the resolution corporation, why it matters, how we got to this milestone, and what comes next.

The slow unfolding of the banking crisis reminds us of the fragility of our financial system. The financial system, especially the banking system, is generally disaster-prone. On one hand, financial firms can make mistakes and experience losses. In addition, there is a link between problems of the economy and hardship in financial firms. When an economic downturn happens, the value of business activities declines, and this induces losses upon financial positions. We need to build a financial regulatory apparatus which will reduce financial fragility. This involves three main elements of machinery : micro-prudential regulation (which aims to push the failure probability of each financial firm to a desired value), systemic risk regulation (which aims to reduce the probability of a disruption in the overall financial system, and have tools to respond to such a disruption when it does arise) and resolution (a specialised bankruptcy process for most financial firms). At present, in India, we have weaknesses on all three elements.

Consequences of a weak resolution system

When micro-prudential regulation works well, the failure probability of financial firms is at a low level chosen by the relevant financial agency. The failure probability is not zero. Failure of inefficient firms is essential for `creative destruction'. The process of failure of inefficient firms, and the shift of capital and labour to efficient firms, is essential for productivity growth. The question is: How can we make the failure of financial firms orderly?

The failure of financial firms can often be quite disorderly. Unlike real sector firms, many financial firms manage a large amount money belonging to households and businesses, with only a small amount of capital brought in by their owners. Banks in India typically have leverage of 18$\times$ to 20$\times$, which means that their balance sheet size is 18 to 20 times the amount of equity capital. Such leverage is never seen with real sector firms. When the firm gets into trouble, there is clamour by the creditors who want to see a fair and efficient process through which they get some of their money back. Matters are more challenging with some financial firms which are so large and complex that their failure could induce instability in the financial system.

An orderly failure is one where a) the consumers either get their money back quickly or continue to get services without any significant inconvencience, and b) the stability of the financial system is not threatened. If we are not able to obtain orderly failures in the financial system, this has many adverse consequences:

• Consumers of failed financial firms suffer. As an example, in India, many cooperative banks fail every year. In spite of high entry barriers, larger institutions also fail (e.g. Global Trust Bank in 2004). Consumers lose money in these failures. These bad experiences make consumers wary of engagement with the financial system, and increase the share of gold and real estate in their portfolios.
  
• Financial stability is threatened, because even if one systemically important financial firm fails, the entire system could be destabilised by a messy, long-drawn bankruptcy process. This forces government to bail out such financial firms. So, a financial crisis ends up having a fiscal consequence.
  
• When faced with the possibility of harm to consumers, and threats to financial stability, governments get cold feet in situations of firm distress. They are then prone to bail out financial firms using taxpayers' money. We in India are familiar with this story. Public sector banks are routinely recapitalised with public funds to ensure they do not fail. This is almost never a good use of public money.
  
• Regulators sometimes respond to these problems by setting up entry barriers, which harm competition and economic dynamism. They justify the every day harm to competition on the grounds that this averts harm to consumers, risks to financial stability and the fiscal cost of bailouts.
  
• Financial firms suffer from moral hazard, and take greater risks. At its worst, financial firms obtain supernormal profit from these two interlinked channels: the certainty of being bailed out and the lack of competition.
  

A system that ensures quick and orderly resolution of failed financial firms can help avoid these outcomes. The system should be such that government, financial firms and consumers believe that the failures will be orderly. The present system of resolution in India is inadequate.

First, it mostly empowers the respective regulators (eg. RBI for banks) to do the resolution. Since regulators give the licenses and are supposed to ensure safety and soundness of the firms they license, they tend to be tardy in acknowledging their mistakes. This regulatory forbearance leads to delays in recognition of failure, which increases the costs of resolution, and may lead to losses for consumers and increases risk to stability of the financial system. There is a conflict of interest between micro-prudential regulation (achieving a target failure probability for a financial firm) and resolution (gracefully closing down financial firms which are nearing failure).

Second, the present system gives very limited powers of resolution. The powers that are given are: forced mergers/amalgamation, and winding up. Some of the other powers, such as bail-in (discussed later), are not available.

Third, even these limited powers are not enjoyed over many of the financial firms. For example, regulators do not have resolution powers over public sector scheduled commercial banks and regional rural banks.

Fourth, the way the system is structured, a bankruptcy resolution can take years, sometimes even longer than a decade. This is partly because the regulators do not have powers to take timely resolution action.

The Financial Resolution and Deposit Insurance Bill

Indian policy thinking on this began in the RBI Advisory group on reforms of deposit insurance, 1999, chaired by Jagdish Capoor.

This slumbered until we got to the Financial Sector Legislative Reforms Commission, chaired by Justice BN Srikrishna, which worked from 2011 to 2013. In its full design of Indian financial regulation, it recommended a Resolution Corporation.

In 2014, a Working Group of Ministry of Finance and Reserve Bank of India, co-chaired by Shri Arvind Mayaram and Shri Anand Sinha, also recommended a resolution capability for financial firms.

In 2014, the Ministry of Finance constitued a Task Force for the Establishment of the Resolution Corporation, under the chairmanship of Shri M. Damodaran, to work out the plan for establishing the Resolution Corporation. This was part of the two-part creation of task forces for building the new institutions required in the FSLRC architecture, which came about as four task forces followed by one more.

The budget speeches of 2015-16 and 2017-18 announced a plan to draft and table a Bill on resolution of financial firms. In September, 2016, a draft of the Bill was placed in public domain for comments.

On June 14th, the Cabinet approved the proposal to introduce a Financial Resolution and Deposit Insurance Bill, 2017 ("the FRDI Bill") in Parliament. The FRDI Bill, when enacted, will create a framework to ensure that failure of financial firms is orderly. It will establish an independent Resolution Corporation tasked with resolving failed financial firms. The Corporation will also subsume the deposit insurance function presently performed by the Deposit Insurance and Credit Guarantee Corporation.

This Bill stands at the intersection of two long-term reform projects: 1) financial sector reforms, of which bankruptcy resolution of financial firms is an integral part; 2) bankruptcy reforms, of which financial firm resolution is an integral part. So, this Bill moves both these projects forward, and is an important building block for an efficient system of capital allocation in India.

FSLRC had envisioned a separation between the resolution corporation, which would apply for most financial firms, and the bankruptcy code, which would apply for the remaining financial firms and for all non-financial firms. The Bankruptcy Legislative Reforms Commission (BLRC), which drafted the Insolvency and Bankruptcy Code (IBC), worked with this scheme. IBC does not cover financial firms, unless the Central Government notifies certain financial firms to be covered under that law. Many types of financial firms, especially firms handling consumer funds and firms that are critical for financial stability, require a specialised resolution mechanism. For firms handling consumer funds (eg. banks, insurance companies), the process under IBC is not suitable, as a large number of small value consumers will find it difficult to invoke that process. The processes of IBC are designed for creditors who are firms, not individuals. For systemically important financial firms (eg. central counterparties, larger banks), a creditor-led resolution process under IBC is not suitable, because what is at stake is not just the interest of creditors but the stability and resilience of the financial system. Hence, for such financial firms a specialised resolution regime is required. The FRDI Bill will create such a specialised resolution regime.

What is resolution?

In the world of financial firms, resolution complements regulation. Regulators and the Corporation are expected to work in tandem, with the regulators focused on maintaining financial health and, when a firm gets into trouble, pushing for its recovery. The Resolution Corporation will take over and resolve a firm after recovery efforts have failed. Although the version of the Bill approved by the Cabinet is not yet in public domain, based on the version that was released for public consultations last year, the framework is divided into four stages.

First, when the financial firm is healthy, the respective regulators will monitor the firm and work to ensure it continues to stay healthy. At this stage, the Resolution Corporation will only get information indirectly through the regulators. Substantive powers to monitor the firm or to take any other action with respect to the firm will not be available to the Corporation.

Second, once the financial firm starts deteriorating, the respective regulator will attempt recovery. At this stage also, only the regulators will continue to have substantial powers over the firm.

Third, if the recovery efforts fail, and as the financial firm get close to failure, the Corporation will get substantial powers to instruct the firm to improve its resolvability and prevent actions that may erode the values of assets available for resolution. At this stage, the role of regulators is restricted.

Finally, when the firm fails, the Corporation will take charge and resolve it. Resolution typically means selling the failed financial firm, as a whole or in parts, to another financial firm via a competitive bidding process. However, resolution could also involve other instruments. For example, the firm could be "bailed-in", which means that the rights of and obligations to creditors may be written down to recapitalise the firm from within. Bail-in typically includes converting some junior debt into equity, but may also include writing down other types of claims. This is the opposite of a bail-out, wherein outside investors rescue a borrower by injecting money to help service a debt. Finally, liquidation may be a tool used for resolution.

There is a certain degree of tension and potential conflict between the Regulators and the Resolution Corporation. This is a healthy check-and-balance. Resolution works as a check on regulatory incompetence and forbearance. Both sides will need to be mature, respect the role of the other, and coordinate.

The idea of a specialised resolution regime for financial firms is well-accepted globally. The US has had a resolution system for banks for more than 80 years. The scope of this system was extended after the financial crisis of 2008. There have been more than 600 bank failures in US since the crisis. In this time, there has been not been even one bank run in the US, because depositors trust the resolution system to work. Why the crisis happened in the first place is another matter, which is beyond the scope of resolution. Resolution comes into play only after regulation fails, and the occurrence of crisis resulted from regulatory failure, among other factors.

Many other countries have put in place comprehensive resolution systems. These include: all European Union member states, Switzerland, Australia, Canada, Japan, Korea, Mexico, and Singapore. Many jurisdictions have ongoing or planned reforms to resolution regimes. These include: Australia, Brazil, Canada, China, Hong Kong, Indonesia, Korea, Russia, Saudi Arabia, Singapore, South Africa, Turkey.

Next steps

We are still a few years away from having a full-fledged resolution regime. Now that the Bill is going to the legislative branch, it remains to be seen what version of the Bill eventually gets enacted. If the essential features of a good resolution regime are diluted in the final version, the chances of success will be low.

Even after the Bill gets enacted, it would still take some time to build an independent and competent Resolution Corporation. Since this capability currently does not exist in the system, it will have to be cobbled together, and then strengthened over a period of time. Consider the example of human resource strategy. There are many models out there. While the Canadian authority works with fewer than 100 employees, the US authority has more than 10,000 employees. The Corporation could choose to run a tight ship, and rely on contractual work to scale up capacity in times of crisis, or it could choose to build a large organisation that is able to, on its own, deal with a crisis. Similarly, given the skill sets required to do this job, the Corporation will have to think innovatively about attracting top talent within the constraints of a government agency.

The Task Force on Establishment of the Resolution Corporation, led by M. Damodaran, has done considerable work that lays the groundwork for constructing the agency. The implementation of their project planning needs to commence immediately, so that the delay between enacting the law and enforcing it can be minimised.

It will also take our governance system some time to get used to this kind of a system of taking over and resolving a failed financial firm in a decisive and quick manner, as opposed to the present approach of allowing things to linger on. If things do go right, there are many potential benefits of this reform.

 

The author is a researcher at NIPFP.

Regulatory Policy in India: Moving towards regulatory governance

by Lalita Som.

Regulatory policy, a comparatively young discipline, is evolving in different ways across the world, reflecting the diverse range of legal, political and cultural contexts on which countries have built their public governance. Regulation, one of the key levers of state power, is of critical importance in managing the economy, in sequencing business behaviour, implementing social policy and influencing behaviour. Regulatory policy thus helps to shape the relationship between the State, citizens and businesses.

In OECD countries, policies to increase competition in markets, and to "roll back the frontiers of the state" in the 1980s and 1990s, broadened to become regulatory reform. Regulatory reform became an essential adjunct to structural reforms, reaching out beyond the network sectors to encompass product market reforms and the liberalisation of professional services. Independent regulatory agencies were developed to manage key aspects of economies and society at an arm's length from the political process. This became known as the regulatory state. The regulatory state paved the way for the idea of regulatory governance (OECD, 2010a).

In OECD countries. regulatory policy has made a significant contribution to economic growth and societal well-being - through its contribution to structural reforms, liberalisation of product markets, international market openness, and a less-constricted business environment for innovation and entrepreneurship. Regulatory policy has supported the rule of law through initiatives to simplify the law and improve access to it, as well as improvements to appeal systems. Increasingly, it has supported quality of life and social cohesion, through enhanced transparency which seeks out the views of the regulated, and programmes to reduce red tape for citizens.

Many OECD countries are concerned about distributional equity – to maximise the welfare of the most disadvantaged, paying attention to distributional consequence of policy actions, albeit not beyond the point at which they would impede on overall prosperity. These insights have had a strong practical influence on approaches to the impact assessment of regulations and especially, analysis of costs and benefits, including distributional aspects and under conditions of uncertainty (OECD, 2010a).

Regulatory reform can be viewed strategically, in both developed as well as emerging markets, as one of the core instruments at the disposal of policy makers. The modern State will have to utilise its regulatory power wisely if it expects to be smarter in order to face challenges like the growing fiscal burden for providing key public services such as health, education and social insurance schemes, in establishing governance arrangements and rationalising complexities to manage the consequences of decentralisation, in supporting the investment climate and in reducing the state's role as an active investor in the economy.

In fulfilling these objectives in an effective way the overall framework of the formulation of laws and regulations requires an explicit whole-of-government approach for regulatory policy, including: responsibility for co-ordination and oversight of regulatory policy; a commitment to assess the cost-benefit of new regulatory proposals and existing regulations, and; the effective implementation of the principles of transparency and public consultation in regulatory decision making (OECD, 2010a).

In emerging markets, extensive state ownership and interference have led to regulatory uncertainty and a business climate that is not conducive to fair competition in open markets. The state's dual role as an active investor and referee has meant that the government is uniquely positioned to shape the applicable legal regime with its interests as shareholder in mind. In many cases, state ownership has created conflicts of interest for the authorities and distorted or suppressed competition. Regulatory institutions and processes are still young in emerging markets, and often regulatory authority is fragmented across a number of bodies, some of which have conflicting mandates. Inadequate co-ordination among government bodies at the national and sub-national levels is a widespread problem, leading to unclear, duplicative, and often conflicting efforts in a number of areas. The lack of sound regulatory governance has meant that popular perceptions of endemic patrimonial politics have persisted, with vested interests and collusion being assumed to operate at the expense of the national interest.

A recent OECD Regulatory Policy Working Paper, Regulatory Policy in India: Moving towards regulatory governance, looks at India’s existing regulatory regime and its evolution in the last two and half decades. The mechanisms of regulatory governance have weaknesses, and in some cases have fallen short of expectations. The paper looks at India's uneven regulatory environment and how its legacy features constrain the evolution of regulatory governance.

Foremost is the difficulty in designing and implementing regulatory policies given the government's inclination to maximize its revenue at the expense of social welfare. This trade-off has compromised effective regulation in the country because of a lack of understanding of what constitutes the objectives of regulatory governance. The paper highlights how the dichotomy between the interests of governments and businesses, as well as that of citizens, has manifested itself over the years in four distinct sectors i.e. mining, hydrocarbons, power and telecoms.

Basic regulation in India is implemented via the concerned line ministries, which may proceed to create industry-specific regulatory authorities that have varying degrees of autonomy, functions, and power. There are significant variations in the structure of the governing bodies, tenure of the members, sources of finances, and interface with the government. A noticeable feature of many of the regulators in India is that they are charged with the promotion and development as well as the regulation of a certain industry. That can result in the regulator thinking of the interests of the industry rather than the users of the industry.

In sectors like insurance, coal, petroleum, telecoms, banking, regulatory strategies are hampered by the presence of State owned firms. The inadequate institutional distance between regulators and state-owned firms, especially when there are no firewalls between them, has meant that the regulators have not promoted enough competition.

In these areas, the State is obliged to play a dual role: i.e. that of market regulator when it is also the owner of commercial SOEs, particularly in newly deregulated, often partially privatised industries. Whenever this happens, the State is inevitably conflicted in its opposing interests as: first, a major market player/firm owner in its own right, and second, as an arbitrator in the (supposedly) neutral, impartial, dispassionate role of regulator.

Regulators are expected to behave independently, and the challenge of independence is to avoid capture by interest groups who stand to benefit from regulation. It is equally significant to avoid regulatory capture by local politicians. Local politicians are attracted by the possibility of large economic rents in perpetuity. Too often, regulators have actively internalised political sentiments in their decision-making. In addition, the elite governmental bureaucracy has a ubiquitous presence in regulatory bodies. Regulatory independence from the executive is difficult to administer if regulators themselves come from a career backdrop of directing political decisions. This strain is exacerbated when regulators are appointed directly from senior governmental positions, requiring them to shift, from administering and defending government positions, to acting as an impartial referee (Dubash, 2008).

Many areas, such as agricultural markets, warehousing, or land, require coordinated approaches to regulation (both rule-making and enforcement) by the central government, and sub-national governments at the state and city levels. Economic liberalisation, coming on the heels of political federalisation, has transformed federal –state relations unleashing unintended and unplanned decentralisation (Sinha, 2004). Any regulatory reform agenda depends crucially on a close co-operation between different levels of government. Federal-state relations have been affected significantly with the rise of multi- party coalition governments and alliance politics in the 1990s. Coalition and alliance partners from states have become progressively more powerful at the national level and more capable of bargaining with the national government. That political reality has added considerable complexity to the environmental and social dimensions of economic decision-making which need the cooperation, and an explicit ethos for regulatory governance, of both national and state governments. The need for multi-level policy coordination has been felt making way for the creation of technical and regulatory agencies at various levels, at times adding to the complexity of policy processes, at others to the bypassing of traditional forms of accountability at all levels (Arora, 2014).

In addition to the legacy features of India’s regulatory environment, the country lacks a coherent policy on regulation. A whole of government policy towards "regulating" would provide the connectivity of different reform efforts and help the concerted effort towards regulatory governance instead of disconnected regulatory reforms. This may include a combination of creating or enabling institutions to embed good regulatory principles into their functioning, but also include the systemic implementation of good regulatory practices such as regulatory impact assessments, public consultation and administrative simplification in priority sectors.

Some sub-national regulators in the power sector and the airports regulator have embedded stakeholder engagement with discernible positive outcomes. the more active use of Regulatory Impact Assessment (RIA) and stakeholder consultation, can inform the government on the cost of some of the trade-offs that India faces in the design of its regulatory policy. Although there exists a certain consensus on the importance of RIA and half-hearted efforts have been made so far to implement it, lack of political will, capacity constraints and limited awareness amongst other stakeholders are impeding its further application. Experience with regulatory governance in the last two decades has resulted in the Regulatory Reform Bill 2013 which intends to legislate an overarching regulatory law to introduce further regulatory reforms and standardise some basic institutional features and processes across all regulatory bodies. The OECD would welcome the opportunity to engage with the NITI Aayog during the redrafting process of this bill.

In addition, India could learn from the experience of both mature and young regulatory governance countries in implementing its regulatory policies. Malaysia which has undertaken large market reforms leading to initiatives for greater regulatory coherence. Australia and New Zealand’s Productivity Commissions, show, most importantly, that the regulatory environment needs to be constantly evaluated to make sure it is keeping pace with the changing technology, business environment, and consumer needs and demands (OECD 2010b). The United Kingdom’s Regulatory Policy Committee provides opinions and scrutiny over the quality of analysis by government departments and are engaged in setting "regulatory guidance" across the government. Korea's Regulatory Reform Committee drives forward the regulatory reform agenda (OECD, 2015).

Bibliography

OECD (2010a). 'Regulatory Policy and the Road to Sustainable Growth', OECD Publishing, Paris.

Dubash, Navroz (2008). 'Institutional Transplant as Political Opportunity: E-Practice and Politics of Indian Electricity Regulation', Comparative Research in Law & Political Economy Research Paper No. 31/2008.

Sinha, Aseema (2004). 'The Changing Political Economy of Federalism in India: A Historical Institutionalist Approach', India Review, Vol. 3, No.1.

Arora, Dolly (2014). 'Trends in Centre-State relations', Indian Institute of Public Administration, New Delhi.

OECD (2010b). 'Review of Regulatory Reform: Australia', OECD Publishing, Paris.

OECD (2015). 'Regulatory Policy Outlook', OECD Publishing, Paris.

 

Lalita Som has worked for the Organisation of Economic Cooperation and Development, Paris. She can be reached at lalita.som@gmail.com

The regulatory difficulties of NBFCs in India

by Shubho Roy.

The founder of the Shriram Group, R. Thyagarajan, who is one of the most respected people in Indian finance, spoke to Forbes India expressing concerns about the things that are being done with the regulation of NBFCs. This is important food for thought for understanding the problems of Indian finance. He talks about how the NBFC sector is being stifled with regulation and the need for moving it away from the Banking Regulator. He points out that the mind-set and objectives of RBI, in regulating NBFCs in ways that are appropriate for banks, is killing the industry.

Banks and NBFCs are different, pose different problems for financial regulation, and should be regulated differently. RBI is smothering NBFCs by applying banking thinking for them, and is thereby hampering access to credit for the firms who obtain financing from NBFCs. The FSLRC approach offers logical answers to these questions.

What motivates regulation

Regulation must not degenerate into central planning; it must be motivated by the need to correct a precisely stated market failure. We must understand the anatomy of the market failure, and use the coercive power of the State at the precise root cause. Occam's Razor of Regulation implies that we should get the job done with the minimum use of force. The market failures associated with banks and with NBFCs are quite different. For banks, the market failure is consumer protection of unsophisticated depositors. This is the reason why we have detailed banking regulation. If there are no unsophisticated depositors in a lending institution, regulating them like banks is wrong, and harms the economy.

Consumer protection in banking regulation

When you deposit your money in a bank, you can go and withdraw the principal at any time you want. Even for fixed deposits, the principal is protected in the case of premature withdrawal.

How does a bank pay interest on money which you can withdraw at any time? Through loans. However, when a bank gives a loan: the bank gets repaid only as per the loan terms (and not when the bank needs money). If you take a home-loan or a car-loan for five years, the bank cannot come and ask you to repay the entire money before the five years are up (unless you default). The bank can only ask for the regular predefined installments. No bank can come to you (a borrower) and say:

"a lot of people are withdrawing money this month, so please pay up your five year car loan, ahead of time, this month."

Similarly, when you (depositor) go to withdraw the money from a bank the bank cannot say (legally prohibited):

"a lot of people have delayed their loan repayments so you cannot withdraw your money today, come back after a few months."

These types of deposits are technically called deposits callable at par. i.e. Deposits you can withdraw at any time without losing the principal.

Contrast this with a term loan or a bond/debenture. When you buy a five year Tata Motors debenture in the debt market, cannot withdraw it at par before the debenture matures. i.e. If you go with the debenture to the offices of Tata Motors before the five years are up, Tata Motors has no legal obligation to repay the loan amount in the debenture. You can only get your principal and interest payments as per the terms of the debenture and not a minute before that. You may sell your debenture to someone else (secondary market), but that is not the same as getting your principal back from Tata Motors. In the secondary market you have no assurance you will get your principal amount back.

Ensuring that households are able to withdraw their deposits, whenever they need it, is not trivial. Whenever a bank fails do it, eventually, there is a run on the bank. A run happens when you households panic that their life savings will be destroyed and queue up to get withdraw their deposits. Governments know (from the history of bank failures) that you cannot trust banks to pay up to households on time. Therefore, countries create banking law and corresponding banking regulator to check the banks.

Three important components of these regulations are:

1. Deposit Ratios: This requires the bank to lend out only a part of its deposits, say 80%. The bank has to keep the rest for withdrawals on any given day.
   
2. Equity buffers: Banks are required to have a certain minimum equity capital. As an example, in India, the leverage of the banking system is roughly 20 times, which means that for each 20 rupees of total assets there is 1 rupee of equity capital. This acts as a buffer against losses as the shareholders bear the loss.
   
3. Loss Recognition: Banks are forced to recognise losses and write them off using equity capital, so as to not subvert the intent of the equity buffer.
   

Banks have the incentive and capability to cover up bad news about the loans they have made. If banks admit they have bad loans then the banking regulator forces them to raise money from other sources (equity market). Raising money from the equity markets is hard, expensive and, dilutes existing shareholders. Normally, a bank likes to hide and delay the fact that debtor is not repaying as long as possible.

Unlike sophisticated creditors, you and I are unable to really understand the balance sheet of a bank. I cannot judge whether the bank will have enough money to repay a fixed deposit five years from now. Without a financial agency looking over banks every day, it is easy for banks to lend money profligately and end up defaulting to depositors.

The oversight of the financial agency, and the checks imposed by these regulations, are not without benefit to banks. In return for complying with all these regulations, the government encourages the general public, to keep money in banks. The government and the central bank extends a guarantee of safety in bank deposits. The Jan Dhan Yojana does not encourage you to buy corporate bonds but put money in bank deposits. The government runs a deposit insurance program to protect helpless households who have deposits with banks.

NBFC regulation

Non-Banking financial companies should be what their name suggests: non-banks. Sadly, this was not the case for India till about a decade ago. Because, there were few banks, Indian laws allowed NBFCs to also take deposits callable at par. i.e. Take money from depositors (unsophisticated savers) which the depositors could withdraw at any moment (working hours). These were called NBFC-Deposit Taking.

Over the last few years, RBI has gradually removed this category. Today, most NBFCs take money from the bond market or term loans (sophisticated depositors). There are no unsophisticated depositors in most NBFCs today. Since there are no unsophisticated depositors who may need their money immediately on demand, there is no consumer protection angle from deposits.

However, in spite of closing down most deposit-taking NBFCs, RBI continues to regulate NBFCs like banks, requiring them to keep liquid funds (in government securities) and also recognise problematic loans and keep capital against it. This defeats the very purpose why NBFCs are prohibited from taking deposits callable at par from household. If you are not taking deposits callable at par from households, you can go and make risky loans which banks are not going to make. There is no point in recognising and regulating NBFCs, if they are forced to meet banking regulations. We may as well call them banks and allow them to collect deposits callable at par.

The FSLRC approach

FSLRC does not indulge in artificial distinctions between banks and non-banks. It has a clear functional test for designating something as a bank or not:

Are you taking deposits from the public?

If you are; you are a bank; and you will be regulated like a bank; by the banking regulator. If you are not; then you are not a bank and you will not be regulated as a bank.

It takes care of concerns of shadow banking (entities taking deposits callable at par without complying with banking regulation) with a principled based approach. All the regulator has to test is if an entity is taking deposits callable at par. Then whatever be its name, it should be regulated like a bank.

FSLRC recommendations are driven by informed analysis of the need for regulation. Banks have unsophisticated consumers on both sides of the balance sheet and therefore the regulations have to address the consumer protection issues on both sides of the balance sheet. NBFCs on the other hand have unsophisticated consumers only on the side of borrowers. There are no depositors in an NBFC in the same sense as banks.

FSLRC recommended that financial firms which do not do this activity should not be regulated like banks and therefore not be regulated by the banking regulator. FSLRC does not leave NBFCs out of regulation. It concentrates regulation of NBFCs in two areas:

1. The protection of unsophisticated consumers who borrow from NBFCs, in line with regulation on consumer protection.
   
2. Systemic risk regulation, which would be done in a consistent way for all systemically important financial firms, some of which may be NBFCs.
   

The concerns of systemic risk however is not limited to NBFCs. Systemic risk regulation cross-cuts across all segments of the financial sector and has its own set of instruments/regulations which are not the same as the ones in banking regulation.

Conclusion

Mr. Thyagarajan reminds us that it's broke. We should fix it. He recommends that the central bank should not regulate the NBFC sector. The intellectual framework for regulating banks and NBFCs is so different that the same regulator cannot do it. India has a few large and stable businesses which banks can lend to. However, most of India's growth will come from new businesses which are small and risky. The small entrepreneur who buys a truck will face liquidity shocks (will miss a few of the regular installments). As long as such entrepreneurs are not being funded with household safe savings, there is nothing wrong in that. NBFCs have to be different from banks, they should be more risk taking. And yes, more of them will fail, but it will not harm the unsophisticated savers.

Regulation should be based on some rational requirement to address market failures. Without identifying market failures, regulations are no more than arbitrary injunctions from the powerful which serve no purpose.


Shubho Roy is a researcher at the National Institute for Public Finance and Policy.