Author: Siddarth Raman

Siddarth Raman is a senior research lead at XKDR Forum.

On this blog:

• The MACT Litigation Overload: How India's Regulatory Trifecta Forces Cases into Court, 8 February 2026.
• High-Voltage Treatment for a Comatose Elephant, 28 December 2025.
• Establishing the baseline for the Kollam district court reform, 21 November 2025.
• Beyond Pendency: Counting Cases Correctly, 5 October 2025.
• Get them to the court on time: bumps in the road to justice, 12 June 2025.
• Who is litigating cheque bounce cases?, 5 June 2023.

The MACT Litigation Overload: How India's Regulatory Trifecta Forces Cases into Court

by Siddarth Raman and Maya Ramesh.

Indian courts are drowning in third-party motor accident claims. More than a million claims, worth over INR 80,000 crore await resolution. These disputes account for a tenth of all civil pendency. In this article, we argue that this explosion in litigation is a consequence of poor regulatory design. India's third-party motor insurance market operates under a unique set of rules that dismantle the foundational economics of insurance. Coverage is mandatory, insurers cannot select customers, premiums are fixed by the regulator, and liability for injury or death is uncapped. These rules distort incentives: they encourage claimants to pursue bigger awards through courts, while leaving insurers with only one strategy - delay. This behaviour is often narrated as a simple story of bad firms harming consumers, when it is the inevitable consequence of a certain arrangement of incentives. The system effectively guarantees that most accidents end up in litigation.

Insurance economics - A short introduction

Insurance operates on an elegant economic principle -individual risks aggregate across large populations to convert unpredictable events into manageable outcomes at the group level.

By pooling risks, insurers use the premiums of many to pay the claims of the few. Risk-based pricing is key: older people pay higher health insurance premiums than younger people, smokers pay more than non-smokers for life insurance, homeowners in flood or earthquake zones pay more for property insurance. In the UK, younger drivers pay higher premiums to get behind the wheel, compared to drivers over 30.

In most insurance transactions, the interests of the insurer and the policyholder align. When you buy health or comprehensive car insurance, your insurer wants to pay valid claims promptly to keep customers satisfied, build loyalty and ensure recurring revenue. This alignment breaks down in third-party (TP) liability. The insurer has no customer relationship to maintain with the victim, creating a financial incentive to minimize and delay payouts.

Unique distortions in the Indian market

The Indian regulatory framework distorts conventional TP insurance dynamics through three specific interventions:

1. Mandatory Purchase and Mandatory Offer: Section 146 of The Motor Vehicles Act (MVA) mandates that every vehicle owner buy third-party insurance. Section 32D of the Insurance Act, 1938 mandates that general insurers underwrite minimum percentages of motor TP business. IRDAI's 2015 regulations explicitly forbid insurers from refusing liability-only policies. This dual compulsion creates a captive market where neither buyer nor seller has meaningful choice.
2. Regulated, Non-Risk-Based Pricing: IRDAI sets the premium for this mandatory TP insurance. These premiums are based on vehicle categories and historical aggregate claims data. They do not factor in the individual driver's risk profile - their driving record, age, experience, location, or their history of insurance claims. A safe or good driver with no history of accidents pays the same TP premium as a high-risk driver for the same vehicle class who may have chalked up a record. This decouples price from individual risk, preventing insurers from charging premiums commensurate with perceived risk.
3. Uncapped Liability for Injury / Death: The MVA imposes unlimited liability on the insurer for death or bodily injury. The 2019 amendment has a mechanism to link premiums and liability (Section 147(2)). When notified, the Motor Vehicles (Third Party Insurance Base Premium and Liability) Rules, 2022 schedule continues to specify base premiums for unlimited liability.

As of December 2025, the premium for a 1-year TP insurance for a 4 wheeler of less than 1000 cc is INR 2094. Prices were last raised in 2020. The industry faces persistently high claims ratios (claims paid out as a ratio of premiums collected). In 2023-24, the industry-wide incurred claims ratio for motor insurance reached 78%. For PSUs like New India Assurance, the net incurred claims ratio hit 108% in FY 2024-25, meaning they paid out more in claims than they collected in premiums. The problem isn't new. The industry was discussing similar problems a decade ago.

The litigation funnel

Parties negotiate liability compensation in specialized Motor Accidents Claims Tribunals (MACT). A 2019 amendment automatically converts police DARs into claim petitions. Bargaining now begins under the direct oversight of a court. Litigation is the default, institutionalised starting point.

Consider the incentives this structure creates for rational actors. Insurers are forced to accept uncapped liability at a fixed, non-risk-adjusted price. Any large claim, involving injury or death is riddled with subjectivity, making it impossible to anticipate the potential payout. While an objective formula has been proposed, the deviations and exceptions are many. These formulae usually involve compensation of potential future income. In a poor country, this may involve pedestrians and drivers whose income isn't reported formally.

From the perspective of an insurance firm, each policy brings with it the prospect of potentially unbounded losses. There is no upside to paying higher amounts or doing it quicker - the insurer has no relationship to forge or salvage, and there are no reputational costs to delays or denial, unlike in own damage insurance. The legal costs in this kind of bulk litigation that insurance firms go through are comparably trivial to an uncapped liability. This is evident in the data from the IIB Motor Annual Report 2019-20: while 93% of OD claims settle for under INR 50,000, TP payouts run into lakhs.

In this context -

• Challenging the quantum of compensation is standard practice. It offers a chance to reduce the payout on appeal.
• Delaying the payout allows them more float.
• Signalling intransigence prevents future claims from using past allowances as precedent.

Insurers are also expected to make an offer within 30 days of the DAR being filed. This rarely happens. Any offer without a claim request will act as the floor for future bargaining. It is game theory optimal to lowball, or not make an offer. Contesting the claim amount, or challenging the facts surrounding income or extent of disability is perceived as unnecessary adversarial obstruction. It is a rational response to managing uncapped, subjectively determined liabilities against inadequate, fixed premiums, especially when bargaining in public.

Claimants pursue a different calculus. Under the standards established in Sarla Verma vs DTC (2009) and National Insurance Co. Ltd. vs Pranay Sethi (2017), the judiciary interprets 'just compensation' liberally. Any discussion between claimant and insurance firm is also intermediated through lawyers from the get-go. Lawyers acting to maximise their client's outcome advise the client on the potential for higher awards through the MACT process, leveraging the subjective elements in compensation calculation and the pro-claimant judicial stance. Accepting an early, potentially lower, out-of-court offer is less rational than pursuing the claim through the tribunal. If the initial award seems insufficient, claimants are also incentivised to appeal for enhancement in the High Court.

Why cases take decades

On paper, the system has avenues for settlement. In practice, they are largely an illusion. The regulatory architecture systematically discourages private resolution and co-opts settlement into the formal court process.

The moment a police officer files a Detailed Accident Report (DAR), the MVA mandates that the MACT must treat it as a claim petition. The clock starts ticking, and the case is officially in the judicial system, often before the claimant has even hired a lawyer. Even if the parties wish to settle, an offer to the claimant must be made within 30 days of receiving information of the accident, and recorded with the tribunal.

While mechanisms like Lok Adalats settle many cases, they function as an adjunct to the courts, handling cases referred by the MACT. The resulting settlement becomes a binding award, stamped with judicial finality. The system doesn't prevent compromise, but it demands that compromise happens under its watch, contributing to the docket load and reinforcing the MACT as the inescapable center of the universe for accident claims.

The MACT isn't necessarily efficient at disposing these claims. Cases last over a year, and the MACT often struggles with just getting parties to court. Even when an award is passed - both insurers and claimants have reasons to challenge it. For insurers, every MACT award above their initial assessment is worth appealing. The potential reduction in payout, combined with years of additional float on unpaid claims, makes the appeal economically viable even with low success rates. For claimants, the judicial system's pro-welfare stance and the subjective nature of compensation calculations mean enhancement petitions often succeed. Their lawyers, working on contingency, have every reason to encourage appeals.

The result is that cases often take decades to complete. We get a rough dipstick by examining a random sample of three judgements in MACT appeals that were delivered in January 2025 in the Delhi High Court.

• Case 1 - MAC APPL. 314/2021 (10 years): 2015 Accident → 2025 HC Judgment.
• Case 2 - MAC. APP. 94/2020 (12 years): 2013 Accident → 2025 HC Judgment.
• Case 3 - MAC. APP. 139/2021 (11 years): 2014 Accident → 2025 HC Judgment.

Each of these took over a decade to resolve. These are not outliers. Data from Delhi, Kerala, and Odisha shows that High Court MACT appeal pendency runs at 25-30% of district court pendency - a staggering appeal rate that reflects both parties' incentives to keep fighting.

Global parallels: The logic of trade-offs

India's regulatory framework is a global anomaly. While mandatory TP insurance is common worldwide, no other major economy imposes the same rigid combination of constraints. Other systems balance the mandate to purchase with trade-offs in pricing or liability.

The UK and Singapore, like India, have uncapped liability for personal injury to ensure victims are fully compensated. However, they balance this enormous potential payout by allowing competitive, risk-based pricing. Insurers can charge a high-risk driver more than a safe one, using the price mechanism to manage their exposure. China takes the opposite approach. It has regulated pricing for its compulsory insurance (CTALI), but it balances this by imposing strict statutory caps on the insurer's liability for death, injury, and property damage. The insurer's risk is known and finite. Most other systems, like those in the US and Australia, also mix and match, but they consistently avoid the trifecta. They pair mandatory insurance with risk-based pricing and various liability caps through tort reform.

Country	Regulated Pricing	Uncapped Liability
India	✔	✔
UK	✖	✔
Singapore	✖	✔
China	✔	✖
USA	✖	✖
Australia	Varies	✖

India stands alone in forcing insurers to take on unknown risks (uncapped liability) for a fixed, non-risk-based price. Insurance firms have no competitive edge - they cannot differentiate on offering, on price, on customer selection or ability to underwrite. This leaves them with no lever except optimising operational costs, or resorting to delay and dispute, making litigation the inevitable outcome.

Conclusion

The million-plus pendency overwhelming India's MACTs isn't a bug - the system is working as designed. When regulation simultaneously mandates purchase, fixes prices without regard to risk, and imposes uncapped liability, it makes fighting every claim the most sensible financial strategy for insurers. Claimants, guided by lawyers who understand the rules, have every reason to push for higher awards. Both sides are responding to incentives.

More judges won't solve this. Neither will faster procedures, or better technology. These are bandages to a structural problem. The solution demands fundamental regulatory reform: keep compulsory purchase (Section 146), but free the other levers - allow insurers to price for risk, and replace the unlimited liability by a capped liability schedule linked to base premiums (Section 147(2)). These are difficult changes with second order effects - poor drivers can get priced out and the burden of large claims will shift from firms to individuals. They may require complementary policies like higher penetration of personal accident insurance, a large public fund for the uninsured, top-up options to increase the liability cap for commercial vehicle owners. The fix is conceptually straightforward; the transition is unlikely to be. A time-bound expert committee should draft the amendments and phase them in.

India needs more functional insurance markets, not more courts. Markets need release valves - one cannot fix every variable and expect the system to work. Until our policies reflect this understanding, the litigation assembly line will keep running. Processing human tragedy through a decade-long judicial machinery serves no one's interests - not the victims waiting for compensation, not the insurers bleeding money, not the courts drowning in cases. In this case, the road to this dysfunction was paved with the best social welfare intentions.

References

Department of Justice, Government of India. n.d. National Judicial Data Grid (District Courts).

Economic Times. 2024. “10.46 lakh motor accident claims worth Rs 80,455 crore pending nationwide: RTI.” May 26.

Wood, Zoe. 2024. “They quoted £7,000-£8,000’: young drivers face huge car insurance rises.” The Guardian, January 27.

Insurance Regulatory and Development Authority of India. 2021. Motor Insurance Handbook. Hyderabad: IRDAI.

Insurance Regulatory and Development Authority of India. 2015. IRDAI (Obligation of Insurer in respect of Motor Third Party Insurance Business) Regulations, 2015. Gazette notification.

Ministry of Road Transport and Highways. 2022. Motor Vehicles (Third Party Insurance Base Premium and Liability) Rules, 2022. G.S.R. 394(E), May 25.

General Insurance Council. 2024. General Insurance Council Yearbook 2023-24. Mumbai: General Insurance Council.

The New India Assurance Company Limited. 2025. Annual Report 2024-25.

Saraswathy, M. 2013. “Third-party motor segment a burden on insurers.” Business Standard, September 14.

Mohapatra, Mugdha, Siddarth Raman, and Susan Thomas. 2025. “Get them to the court on time: bumps in the road to justice.” The Leap Blog, June 12.

Sarla Verma v. Delhi Transport Corporation. 2009. AIR 2009 SC 3104. Supreme Court of India.

National Insurance Co. Ltd. v. Pranay Sethi. 2017. AIR 2017 SC 5157. Supreme Court of India.

Rajesh Tyagi v. Jaibir Singh. 2009. Delhi High Court.

Insurance Information Bureau of India. 2020. IIB Motor Annual Report 2019-20.

Financial Times. 2021. “General insurance pricing practices.”.

Land Transport Authority. 2025. “Buying insurance.” OneMotoring.

LawinfoChina. 2022. “Compulsory Traffic Accident Liability Insurance (CTALI) Regulations.”.

National Association of Insurance Commissioners. 2024. Product Filing Handbook.

State Insurance Regulatory Authority. 2021. CTP Premium and Market Supervision: Review of the Risk Equalisation Mechanism (REM).

Siddarth Raman is senior research lead at XKDR Forum. Maya Ramesh is Counsel at Solaris Legal. The authors thank Shubho Roy, Ajay Shah and Susan Thomas for useful inputs and discussions.

High-Voltage Treatment for a Comatose Elephant

Unshackling the Elephant by Anand Prasad: A Review

by Siddarth Raman.

Anand Prasad's Unshackling the Elephant provides an interesting clean-sheet critique of the Indian legal system. India's development story into the 21st century is shackled by a judicial system that is stuck in the past. The book succeeds incredibly well at applying economic logic and management principles to the judiciary. Many of the suggested reforms have the weight of common sense - the kind that becomes visible once someone has taken the trouble to articulate it well. It stumbles into uncertain territory when suggesting we succumb to indigenous instinct, especially given the fragility of India's current state capacity and my own preference for cautious reforms that avoid the treacherous currents of populism.

This book matters. It is precise in its diagnosis and bolder in its questions than most will venture. Systems rest on assumptions we stop interrogating; surfacing these debates is important because knowing why we got here tells us what needs to be fixed and what doesn't need relitigating.

The Low-Hanging Fruit of Process Modernisation

On several fronts, Prasad's prescriptions will invite broad agreement - particularly from those who have witnessed the impact of process modernisation in other fields and wondered why the legal system has resisted it for so long.

The law is both judicial reasoning and process management. Other fields have walked the journey of process improvement. IT services, consulting, accounting, even corporate law in some aspects. Templatised pleadings and standardised procedures need not be recreated from first principles for every matter; translation tools chip away at language barriers; and the knowledge management systems Prasad envisions - his "legal knowledge grid" - would make legal corpora accessible to law graduates and large language models alike. Ideas of virtual hearings and asynchronous proceedings push this further, reducing the friction of physical presence without necessarily compromising procedural integrity.

These are safe bets. They enhance capacity without demanding discretionary overreach. Early efforts have begun and should be embraced (see here, here, here); many of these ideas deserve serious piloting as part of the eCourts Phase III modernisation effort.

Prasad also questions the figure of the "all-purpose judge" -the expectation that foundational legal education alone equips one to adjudicate matters spanning technology, finance, and specialised commercial arrangements. The assumption may have held in a simpler era. Whether it holds today is less certain.

A note of caution on artificial intelligence. The justice system functions because society accepts the state's monopoly on coercive power and consents to have it applied through due process. This is a social contract grounded in human accountability. AI may assist judges. But the decision must remain with someone who can be questioned, overruled, and held responsible. As much as the engineer in me might wish law were code, it is not.

Fixing the Incentive Systems

Courts are not just forums for dispute resolution. They are markets where incentives shape behaviour.

Consider the interest rate regime applied to legal disputes. Courts award simple interest at rates that don't match any reasonable cost of capital. The effect is predictable: delay becomes a strategy. A defendant who owes money has every reason to stretch proceedings; time works in their favour. Prasad is correct to argue that judges need to understand the time value of money. Aligning judicial interest rates with economic reality would shift the calculus against strategic delay.

On damages, Prasad makes the case for stronger deterrence -particularly through punitive awards for corporate fraud. On costs, he argues that allowing successful litigants to recover expenses would reduce barriers to access, enabling those confident in their position could invest in quality representation without bearing the full risk.

He also correctly identifies information asymmetry and power imbalance as distortions in the current system. Those with deeper pockets hire better lawyers, and in an adversarial system, this matters considerably. His proposals - removing restrictions on contingency payments, allowing lawyers to advertise, and litigation funding - would make legal representation function more like a market, creating a more level playing field.

Like Chief Justice Suryakant, Prasad echoes the need for judicial performance reviews. This deserves serious consideration, though any implementation must balance accountability against judicial independence. For the bar, he calls for high penalties for malpractice and stricter consequences for perjury. Whether the profession will police itself remains an open question. Prasad's experience understanding lawyers and litigants shines through in this section - he dissects how courts, like any market, respond to incentives.

The Temptations of an Overhaul

Anand Prasad's frustration with the legal system is understandable. Stepping into a courtroom feels like walking back through time.

While some structural reforms like splitting the Supreme Court into a constitutional court and court of appeals or curbing judicial legislation merit serious debate, some of the more radical proposals warrant caution. Moving towards an inquisitorial system would transform judges from neutral adjudicators into active investigators. In a country where discretionary power is prone to abuse, such a shift is a dangerous gamble.

The most troubling temptation is the urge to decolonise the system. Weakening foundational principles like the presumption of innocence in favour of indigenous traditions risks legitimising majoritarian sentiment as law, especially when honour killings persist in the 21st century and extrajudicial encounters meet public approval. The philosophical questions in attempting an Indic reinterpretation are formidable - attempting to balance ideas of karma against retributive justice, uniform civil codes against community specific practices, or the contextual obligations of Raja Dharma against the common law tradition that all stand equal before the law.

The Contradictions

There is an internal tension in the book's vision. It praises codification for its clarity and bemoans lack of consistency in judgements while simultaneously advocating for inquisitorial discretion and culturally-responsive justice. Codification demands predictability. Instinctive justice invites its opposite. A similar tension runs through the hope that algorithms will fix what humans could not. AI may detect patterns across thousands of judgements, but it cannot bear responsibility for any one of them.

The deepest contradiction is one of trust. The book hopes to build a high-trust society where precedent holds and contracts are sacred. This is hard to reconcile with privileging cultural instincts that are fluid and contested. One cannot ask people to trust in precedent while empowering judges to override it.

Conclusion

The boldness of the project deserves recognition. Unshackling the Elephant is a precise diagnosis of a system that has resisted reform for too long. Many treatments align with modernity. But there is a rebel streak - perhaps born of frustration - that carries risk. Giant shocks may end up killing the elephant rather than reviving it.

References

Prasad, Anand. 2025. Unshackling the Elephant: Transforming Indian Law, Culture and Economy. Bloomsbury India.

Siddarth Raman is Senior Research Lead at XKDR Forum.

Establishing the baseline for the Kollam district court reform

by Siddarth Raman.

An important milestone in Indian legal system reform has been underway in Kollam district for the last year. The High Court of Kerala has launched a court for cheque dishonour cases under Section 138 of the Negotiable Instruments Act as its first pilot in the 24x7 ONCourts initiative. PUCAR - of which XKDR Forum is a part - is a knowledge partner to the High Court of Kerala in this.

24x7 ONCourts aims to make the litigant experience efficient, predictable and seamless. Before assessing the intervention's impact, we need a baseline. We estimate five measures of court performance using a random sample of 100 disposed cases filed in 2015-2024. In Kollam, the median case takes 609 days over 12 hearings. Only 19% of hearings are substantive. The first substantive hearing occurs after 240 days. The gap between hearings is 61 days. Stage-wise analysis shows that the most time is spent in getting the litigants to court, and most cases do not reach trial. We compute the same metrics for Thrissur to enable future difference-in-differences analysis.

Motivation

Changing a system is hard. Public policy interventions in India are often guided by conjecture, anecdote and assumption. Too many reforms fail because they are not grounded in data, and their outcomes are not measured. A data-driven process with clear hypotheses on the problem, the solution and the expected outcomes, backed by rigorous measurement and empirical evidence, is needed to distinguish success from failure.

Early in the 24x7 ONCourts journey, we planned for continuous assessment. The first step is to establish a baseline. It fixes the pre-intervention state so later changes can be attributed to the intervention rather than unrelated trends. Publishing a compact, replicable baseline also lets other researchers repeat the measurement after go-live and compare the site of implementation against unaffected locations.

Approach to measurement

Courts and court processes should be judged by their impact on litigants; they are the central stakeholders in the system. In this, there are two types of measures one can develop. There are coarse black-box metrics that give a broad picture of outcomes - like the time to disposal. Alongside this, there can be fine-grained process metrics like the time taken to make payments, extent of delay attributable to postal services or police processes, or the time taken by an accused person to file for bail. These are necessary for continuous improvement of processes. Existing court systems do not capture or publish this type of process data.

We use coarse metrics for our baseline, relying purely on public data, so that anyone can reproduce the numbers without privileged access to court systems. As courts modernize and publish more data in the public domain, we may be able to develop more sophisticated metrics.

Using this approach, we pick five measures of court performance:

1. Time to disposal is the number of days from filing to the court's final order.
2. Hearings to disposal is the number of hearings a case goes through before it ends.
3. The share of substantive hearings is the fraction of hearings that move the case forward towards resolution. For instance, a hearing where the judge is on leave or a summons is re-issued is non-substantive; hearings where evidence is recorded or arguments are heard count as substantive.
4. Time to the first substantive hearing is the wait before meaningful progress begins.
5. Time between hearings is the within-case median gap between consecutive hearings. Lower the time, quicker the next hearing. The inter-quartile range (IQR) across cases is a measure of scheduling predictability. A lower IQR implies less variation in the time between hearings across cases.

A more detailed discussion of these measures and how to use them in evaluating court reforms is available here.

We conducted data collection and analysis in November 2024. Our approach, methodology and data are public, so that others can repeat the measurement for different samples, periods, or districts using e-Courts records.

Methodology

This article reports the pre-reform numerical values for Kollam, using a simple empirical strategy. We construct a baseline for Kollam before the 24x7 ONCourts intervention and compare it with Thrissur, which serves as the control district for future difference-in-differences analysis. We selected Thrissur as the control district after eliminating regions with existing special NI courts. Thrissur mirrors Kollam in judicial capacity (approx. 2,500-2,900 pending cases per judge), economic activity (GDVA per capita ratio of 0.9), and administrative composition (both have municipal corporations).

While Thrissur shares structural similarities with Kollam, direct cross-sectional comparisons of absolute performance levels between the two districts are methodologically unsound. Districts differ in idiosyncratic ways that are difficult to quantify -caseload volume, caseload mix, allocation rules. Consequently, our evaluation strategy avoids asking 'Is Kollam faster than Thrissur?' Instead, we focus on within-district changes over time.

We draw a random sample of 100 disposed Section 138 matters filed in 2015–2024 from Kollam and Thrissur using the public e-Courts database. Cheque dishonour cases are filed before the magistrate's court. In Kerala, these are filed as private complaints (criminal miscellaneous petitions) before becoming criminal cases. For each case, we reconstruct the case lifecycle from hearing dates and order text, tagging hearings by stage and classifying them as substantive or non-substantive.

For the baseline, we report medians and means. Medians describe the typical case; means indicate the influence of long tails. By sampling only disposed cases, we measure the speed of the 'successful' cohort. We acknowledge this introduces survival bias: this metric underestimates the time for difficult cases still stuck in pendency. We aim to address this in future work by using survival analysis to estimate the time to disposal for ongoing cases.

Results

The tables below report the pre-reform baseline values for Kollam and, for comparison, Thrissur. They describe how long cases took, how many hearings they required, and how much of that time and effort was substantive.

1. Time to Disposal (days)

   District	Median	Mean
   Kollam	609	782
   Thrissur	792	1003

2. Hearings to disposal

   District	Median	Mean
   Kollam	12	15
   Thrissur	7	10

3. Share of Substantive Hearings

   District	Median	Mean
   Kollam	19%	26%
   Thrissur	25%	28%

   Note: The dataset spans 2015-2024; COVID-19 lockdowns (2020-2021) introduce exogenous shocks to the metric; it has not been adjusted for here.

4. Time to First Substantive Hearing

   District	Median	Mean
   Kollam	240	446
   Thrissur	276	447

   Note: Changes in procedure resulting from the shift from Criminal Procedure Code (CrPC) to the Bharatiya Nagarik Suraksha Sanhita (BNSS) may affect this metric.

5. Time Between Hearings

   District	Median	Mean	IQR
   Kollam	61	74	48
   Thrissur	123	121	62

Stage-wise Analysis

We analyse how time and hearings are distributed across case stages, as part of understanding the pre-reform baseline. In S138 cases, the case trajectory is:

• A complainant files a case.
• Post scrutiny and error correction, the case is registered as a miscellaneous petition.
• The judge takes cognizance and the case is now a criminal case.
• On cognizance, a summons is issued to the accused, followed by warrants and other methods to compel appearance of the accused.
• On appearance, the accused pleads not guilty and takes bail.
• Trial follows with evidence and arguments.
• The court delivers a judgement.

Not all cases go through all stages. For cases that reach each stage, we compute the median and mean time and hearings spent at that stage.

Kollam	Time		Hearings		Cases
	Median	Mean	Median	Mean
Filing - Registration	0	4	-	-	99*
Cognizance	149	268	2	4	63
Appearance	312	533	5	7	74
Trial	337	454	11	15	41
Judgement	27	38	1	1	100

Note: *An error on e-Courts for one case reports the registration before the filing, which has been excluded.

Thrissur	Time		Hearings		Cases
	Median	Mean	Median	Mean
Filing - Registration	0	1	-	-	100
Cognizance	235	317	2	2	52
Appearance	721	878	5	8	81
Trial	335	451	8	12	13
Judgement	42	69	1	1	100

In both districts, getting the litigants to court takes the most time. We also observe that most cases do not reach trial. This reaffirms earlier observations in other district courts.

Way Forward

24x7 ONCourts has been running for about a year. It is too early to compare outcomes - only a fifth of cases filed have been disposed. But this benchmark will enable comparison when the court reaches its full load. We aim to track the court through this journey and continue to share updates on the court's performance.

We will continue to refine our methodology. The baseline analysis provides simple statistics from a set of 100 disposed cases. This suffers from the problem of censoring. We are only observing cases where the event of interest has occurred and we do not take into account ongoing cases. In systems like the court, where pendency is common, we should be using methods like survival analysis to account for ongoing cases. Other methods like time series analysis could identify trends. With Thrissur as a control, a difference-in-differences design can attribute average changes to the 24x7 ONCourts intervention. The present benchmark is the starting point; as post-intervention data accumulate, we can apply more demanding econometric checks using these tools.

Data and metrics form the backbone of evidence-based reform. The 24x7 ONCourts dashboard reports case statistics on a public dashboard in near real-time. This openness to measurement and public accountability sets a precedent for judicial reform initiatives across India. Public reporting supports continuous monitoring, mid-course correction and iterative refinement. A steady flow of transparent data, paired with simple, repeatable measures, is the practical route to learning what works.

References

24x7 ONCourts website.

Vision, ONCourts 24x7.

Evolution and Implementation of the 24x7 ONCourts: A Journey of Innovation Through Collaboration, PUCAR, 2024.

In Service of the Republic: The art and science of public policy, Vijay Kelkar and Ajay Shah, Penguin Allen Lane, 2022.

Approach to evaluate court reforms, Siddarth Raman, Seminar #9 of the series 'Indian Legal System Reform' by XKDR Forum, 2024.

Evaluating contract enforcement by courts in India: a litigant's lens, Pavithra Manivannan, Susan Thomas, and Bhargavi Zaveri-Shah, XKDR Working Paper No. 16, 2022.

How substantial are non-substantive hearings in Indian courts: some estimates from Bombay, Pavithra Manivannan, Karthik Suresh, Susan Thomas, and Bhargavi Zaveri-Shah, The Leap Blog, 6 December 2023.

Get them to the court on time: bumps in the road to justice, Mugdha Mohapatra, Siddarth Raman, and Susan Thomas, The Leap Blog, 12 June 2025.

Understanding Judicial Delays in Debt Tribunals, Prasanth Regy and Shubho Roy, Working Paper 195, National Institute of Public Finance and Policy, 2017.

Making courts transparent: What every litigant should know before filing a case, Pavithra Manivannan, Siddarth Raman, Gokul Sunoj, and Bhargavi Zaveri-Shah, Bar and Bench, 2025.

A litigant's guide to courts: How efficient is your court?, Pavithra Manivannan, Siddarth Raman, Gokul Sunoj, and Bhargavi Zaveri-Shah, Bar and Bench, 2025.

A litigant's guide to courts: Understanding predictability in India's courts, Pavithra Manivannan, Siddarth Raman, Gokul Sunoj, and Bhargavi Zaveri-Shah, Bar and Bench, 2025.

A litigant's guide to courts: Towards a more measurable future, Pavithra Manivannan, Siddarth Raman, Gokul Sunoj, and Bhargavi Zaveri-Shah, Bar and Bench, 2025.

The Long Road to Change, Ajay Shah and Amit Varma, Episode #36 of the podcast 'Everything is Everything', 1 March 2024.

Siddarth Raman is senior research lead at XKDR Forum. XKDR Forum is part of PUCAR - Public Collective for Avoidance and Resolution of Disputes. PUCAR is a knowledge partner to the High Court of Kerala in their 24x7 ONCourts initiative.

Beyond Pendency: Counting Cases Correctly

by Pavithra Manivannan, Siddarth Raman and Bhargavi Zaveri-Shah.

The discourse on Indian judicial reform is dominated by questions of pendency and the workload of courts. However, official sources of caseload estimates in India have been found to be deficient in terms of both the methodology used, and the quality of underlying data (Jain and Reddy, 2025; Damle and Anand 2020). This leads to miscalculation of the caseload of courts and renders it unamenable for comparison across courts. In this article, we propose a new approach for estimating the caseload at Indian courts. We apply this to analyse the caseload at the Original Side of the Bombay High Court, which accounts for 35% of the total caseload of the Court. Our analysis yields three main findings. First, the caseload at the Original Side of the Bombay High Court (the Court) is being overcounted by 66%. Second, the caseload composition of the Court has remained largely stable over the 7-year period of our study with two case-types, namely, inheritance cases, and writ petitions filed against the government, accounting for half the cases filed in the Court. Third, suits as a case-type generates the most number of sub or interim cases.

In India, there are two official sources that publish information on caseloads - the annual report of the Supreme Court and the National Judicial Data Grid (NJDG). Apart from the quality of the data, there are two specific problems with the estimation methodology used by these sources. First, as a case progresses in a court of law, it generates multiple sub-cases. For instance, if a case is filed as a "Suit" for recovery of money, several interlocutory applications may be filed through which the main money suit (the 'main case') progresses. Such sub-cases could range from simple applications seeking the addition of a new party to the proceedings to an interim injunction seeking a stay on the transfer of assets of the respondent. Currently, the NJDG counts such sub-cases as distinct cases. This leads to overestimation of the caseload, inflating pendency and disposal rates. This is because the hearings for sub-cases are held as part of the main case proceedings. Further, a reading of the orders of cases suggests that more often than not, the final disposal order is common for both the main case and its sub-cases. Second, the taxonomy for case-type categorisation is inconsistent across official sources. The Bombay High Court's website lists 142 case-types on its Original Side. On the other hand, the NJDG reports only 19 case-types for the Original Side of the Bombay High Court. This includes an 'Original' and an 'Other' category, which provides little to no information on the case-type filed in the court. Further, the annual report of the Supreme Court has an altogether different classification system, which cannot be readily mapped to the other two official sources. It has a large bucket under 'Other' which does not have a clear definition. Our approach attempts to address these problems.

We count sub-cases as part of its corresponding main case. That is, we adopt the 'family of cases' as the unit of analysis for caseload estimation. This involves collapsing the 142 case-types on the Original Side of the Court into 17 main case-types and two sub case-types, based on their subject. For example, of the 142 case-types, 80 case-types are in the nature of sub-cases such as "Interim Applications", "Leave Petitions", "Chamber Order Lodging" and "Notice of Motion". We classify these as "Interim Applications" and count these as sub-cases. Similarly, "Arbitration Petitions" and "Arbitration Applications" are categorised as "Arbitration cases". This standardisation of case-types makes the caseload estimation exercise scalable and amenable to comparison across similar courts. The list of the 142 case-types and the classification assigned by us can be accessed here.

Data and Methodology

We collect the life-cycle data of 2,36,953 cases filed at the Original Side of the Court between the period January 2017 to December 2024 (Study Period). The Bombay High Court exercises original jurisdiction or jurisdiction over first time civil cases, and appellate jurisdiction or jurisdiction over cases that come before it as appeals from lower courts. We source the information on the life-cycle of cases filed at the Court's original jurisdiction from its website, and it is comprehensive to the extent the Court has made the data available.

As on the date of our data collection exercise (February 2025), the Court's website reported 1,43,514 (61%) cases as disposed of and 93,254 (39%) cases as pending. If the status of a case was unknown or marked as transferred, we classify it into the 'Other' category (185 cases).

We tag each case in our dataset as a main case or a sub-case. Next, we create a family of cases using the CNR number assigned by the Court as the unique identifier. This family of cases becomes our unit of analysis. Finally, each family of case is classified into one of the 17 case types.

Finding 1: Official sources overestimate caseload

The Court's website shows that about 2.5 lakh cases are filed before its Original Side during our Study Period. That is, on an average, about 30,000 cases are filed every year. However, we find that about 40% of these cases are sub-cases (Table 1 below). Viewed in this light, the 30,000 new cases per year can be understood as an overestimate. The annual average of new main cases filed before the Original Side of the Court is about 18,000, almost half of the original estimate.

Table 1: No. of filings

Nature	Count	Average per-year	% of total
Main cases	1,41,608	17,850	60
Sub-cases	95,435	11,769	40
Total	2,36,953	29,619	100

Finding 2: Six case-types dominate caseload

On applying our categorisation framework, we find that six case-types contribute to about 95% of the caseload at the Original Side of the Court (Table 2). In that, Inheritance cases and Writ petitions constitute half the caseload. We also find that the share of case filings across years for these categories do not vary significantly.

Table 2: No. of filings per case-type

Case Category	Count	% of Total
Writs	36,145	25.5
Inheritance and Succession cases	32,979	23.3
Execution cases	19,779	14.0
Tax cases	19,665	13.9
Arbitration cases	16,529	11.7
Suits	8,652	6.1
Other	7,859	5.6
Total	1,41,608	100.0

Finding 3: Suits generate the most sub-cases

We take a closer look at the number of sub-cases per main case in Table 4 for the top six case-types. We find that, while Inheritance cases and Writ petitions are the highest contributor to the caseload of the Court, Suits that is at the bottom of Table 2, has the highest number of sub-cases per main case. 50% of Suits have upto two sub-cases, suggesting that on a per-case basis, Suits may generate more workload for judges compared to Writ petitions and Inheritance cases.

Table 3: Sub-cases per case-type

Case category	Sub-cases per main case (in %)
	0	1-2	3-5	6-10	>10
Writs	86	13	1	0	0
Inheritance and Succession cases	77	21	2	0	0
Execution cases	86	13	1	0	0
Tax cases	84	16	0	0	0
Arbitration cases	84	15	1	0	0
Suits	31	52	14	3	0

Conclusion

Our finding that the caseload of the Bombay High Court is overestimated by about 66% likely means other courts across India are overreporting caseloads as well. When official sources like the NJDG count sub-cases as distinct new filings, it exaggerates the problem of pendency. This prompts the policymakers to focus on solutions like increasing the number of judges, and creating more courts or courtrooms. Such a sole focus on this metric not only neglects the underlying data quality issues leading to inefficient resource allocation but also ignores the unique challenges that each type of case filed in the court face.

Measures of the economy such as GDP, inflation, and employment rate, took decades to be built and continue to be challenged and improved, by researchers and policy-makers alike. Similar sound systems for the measurement of court metrics, of which caseload is only one part, need to be developed. Such systems are imperative for any meaningful discussion on court reform.

References

Chitrakshi Jain and Prashant Reddy T. Tareekh Pe Justice: Reforms for India's District Courts. Simon and Schuster India, 2025.

Devendra Damle and Tushar Anand. Problems with the e-Courts data. NIPFP WP Series, 314, 2020.

Mugdha Mohapatra, Siddarth Raman and Susan Thomas. Get them to the court on time: bumps in the road to justice. The Leap Blog, 2025.

The authors are researchers at XKDR Forum, Bombay.

Get them to the court on time: bumps in the road to justice

by Mugdha Mohapatra, Siddarth Raman and Susan Thomas.

India's district courts currently face a staggering backlog of 4.6 crore pending cases (as of May 2025): 3.5 crore criminal and 1.1 crore civil. Proposals to solve this are familiar: hire more judges, build special courts, adopt new technology. But before rushing to solutions, it is important to understand where cases get stuck in their journey through courts. We hand-collect and analyse the life-cycle of a sample of cases from district courts, with some surprising observations. First, between 50-70 percent of cases are disposed before they get to trial, which is before the judge hears the substantive matter of the dispute. The time spent waiting for parties to appear is over a year. While criminal cases necessarily require strict adherence to due process, even civil cases face delays. These findings challenge conventional wisdom about judicial delays and point to a unexpected bottleneck. If getting people to show up in court is the core source of delays and pendency, strengthening the administrative processes of the court rather than the size of the bench, could lead to more speedy justice delivery from our courts.

The objective of building judicial capacity to achieve judicial efficiency requires an understanding of how cases move through courts, not just tracking pendency rates. This is because the journey of a case moves through deterministic stages, which vary in duration, and imposes varying resource demands from judges and staff. There have been few systematic studies of how a case moves through court. While some studies examine the total time for case disposal, few break this down by stage.

This study analyses stages for two common types of cases that represent a significant portion of the workload of courts: cheque bouncing cases (criminal matters under Section 138 of the Negotiable Instruments Act) and motor accident claims (civil matters under the Motor Vehicles Act).

Cheque bouncing cases account for 10-15% of criminal court workloads, while motor accident claims constitute over 10% of pending civil cases. Cheque bouncing cases happen when a cheque issued does not deliver payment as expected. Motor accident claims are filed to claim compensation for damages caused in the accident against the owner of the vehicle involved, with the vehicle insurance company as a co-respondent. Cheque bouncing cases are filed in a magistrate court, and the motor accident claims at the Motor Accident Claims Tribunals (MACT). Across these two types of cases, there are differences in procedures: whether it is for criminal and civil cases, and for different types of courts.

We use this analysis to answer the following questions:

1. What fraction of the cases go through the whole life-cycle?
2. How much time is spent in different stages of the case life-cycle? Is this different for civil and for criminal cases?

Methodology

The analysis examined 200 disposed cases randomly sampled from from the e-courts database for district courts from courts across Maharashtra, Kerala, Karnataka, Tamil Nadu, Delhi, Telangana and Rajasthan, filed between 2018-2022. After excluding transfers and circumstances where cases never went a court process, the final sample included 147 cases - 77 cheque bouncing cases and 70 motor accident claims cases.

Each case was tracked through its entire journey by analysing court orders and hearings. Cases go through different stages - filing, admission, summons, warrants, bail, written statements, framing of issues, evidence and others. We classify these different stages of 'Pre-Trial' and 'Trial'. Trial begins after both parties appear before the judge - in cheque bouncing cases, after the accused files for bail; in motor accident claims, after written statements are filed and issues are framed.

Results

1. The first finding relates to the stage at which the cases are disposed. Table 1 shows the number of cases disposed at each stage.

Table 1: Where cases end their journey

Stage	Case type: MV		Case type: S138
	No. of cases	Percentage	No. of cases	Percentage
Pre-trial	38	54 %	55	71 %
Trial	32	46 %	22	29 %

More than half of the cases analysed never reached trial. This is higher for the (criminal) cheque bouncing cases, where 70% of cases are disposed before they reach trial. For the (civil) motor accident claims cases, 54% of the cases are disposed before reaching trial.

2. The second finding relates to the time spent in the two stages

Table 2: Time taken by stage

Case type	Total no. of cases	Pre-trial	Trial
MV	70 (32 reached trial)	9.5 months	4 months
S138	77 (22 reached trial)	12 months	3.5 months

Once all parties are in present in court, cases resolve quickly - usually in 3-4 months. Most of the delay in matters is in the pre-trial stage where the court is waiting for parties to appear (usually the respondent). This takes between 9 months to a year.

These findings align with broader patterns visible in the National Judicial Data Grid for district courts (NJDG). The data shows that 72% of pending cases are stuck before trial: 48% are at the appearance stage, 14% are awaiting service of summons, and 10% are awaiting service of warrants. While the data from the NJDG is useful to know where cases are placed within the judicial system, it does not provide insights on the time spent in different stages. Our analysis quantifies the extent of the bottleneck.

Discussion

The analysis points to two key observations: Most cases that are filed in court do not reach trial, where judicial mind is applied to decide issues of the case. Further, the bulk of the time is spent in getting the parties to court. Once all parties are present, the time to resolution is much lower. The puzzle is in understanding what shapes these features, and how this understanding can be used to improve court efficiency in dealing with case workload.

• Are the delays in court cases inevitable?

The analysis points to the paradox of procedural protections for some cases. Cheque bouncing cases and other criminal matters demand the presence of the accused. This creates an inherent tension between speedy resolution of the matter and judicial procedure. The accused, facing potential imprisonment, has every incentive to delay appearing in court until forced by warrant. The very protections meant to ensure fair process become tools for delay.

In India, these procedures continue to evolve. Under Section 223 of the newly introduced Bharatiya Nagarik Suraksha Sanhita, magistrates must now offer the the accused an opportunity to be heard before admitting a complaint as a criminal case. This involves sending a notice by post, a process not unlike the current summons process. While intended to enhance due process, this additional step could further extend the timeline for cheque bouncing cases. The new code also allows for trial 'in absentia' under Section 356. If a person is declared as a 'proclaimed offender', and if the judge thinks that they are absconding to evade trial, the court can proceed without the accused. How these practices are implemented remains to be seen.

• Administrative and judicial functions of the court

The findings expose a fundamental blind spot in how courts actually work. The popular image of justice - a judge hearing arguments, weighing evidence and delivering verdicts - represents only one aspect of the judicial system. Behind every courtroom drama lies an extensive administrative operation of filing documents, scheduling hearings, maintaining records, and getting parties to court. These two systems complement each other, but our understanding of the administrative aspects of the court system is limited, because it is behind the scenes.

Current reform proposals focus heavily on expanding judicial capacity: hiring more judges, creating specialised courts, and implementing new technologies for case management. While these interventions have merit, they miss the core issue revealed by this analysis. The judicial system extends far beyond judges and courtrooms. Delivering summons and notices typically involves police officers, postal services, or process servers. When the simple act of getting parties to court becomes the biggest bottleneck, the solution requires rethinking the entire administrative infrastructure supporting the courts.

What does imply for potential solutions for institutional reforms of the judiciary? Some approaches that could address the summons/notices bottleneck include:

1. Digital service of summons and notices could reduce delays, though this requires updated legal frameworks and reliable technology infrastructure.
2. Police-court integration might improve warrant execution, though this raises questions about optimal resource allocation - should a capacity constrained police forces pursue cheque defaulters or focus on serious crimes?
3. Quicker escalation to warrants may secure attendance faster, but wielding state power to restrict liberty demands careful consideration. A judge's decision to issue an arrest warrant carries real consequences.
4. Penalties for non-appearance could be introduced to create stronger incentives for timely court attendance.
5. Private process servers, as used in U.S. courts, offer another model worth exploring.

Conclusion

The clamour for court reform has been dominated by traditional solutions: more judges, rewritten procedures, and new technology. But when the relatively simple task of getting parties to court becomes the system's biggest bottleneck, a more nuanced approach is essential. Court reform must recognise that efficient justice delivery requires strengthening both judicial and administrative capacity in parallel. Separating court administration from judicial functions, as some countries have done, could allow specialised focus on each component while maintaining their complementary relationship.

The invisible administrative machinery of courts deserves as much attention as the visible judicial functions. Until administrative capacity matches judicial capacity, Indian courts will continue struggling with delays that have less to do with complex legal reasoning and more to do with basic case management. The path to speedier justice may lie not in the courtroom, but in the clerk's office, the process server's route, and the administrative systems that bring cases to life. Only by addressing both aspects of the judicial system can India's courts deliver the swift justice that 4.6 crore pending cases demand.

Siddarth and Susan are senior research lead and senior research fellow at XKDR Forum. Mugdha was a research associate at XKDR Forum. We thank Pavithra Manivannan for insights, Shubho Roy for help with the interpretation, and Ajay Shah for inputs.

Who is litigating cheque bounce cases?

by Siddarth Raman.

Cheque bounce cases under Section 138 of the Negotiable Instruments Act are an important source of case load at the Indian judiciary. This has inspired many attempts at modifying laws and court procedures so as to reduce the burden. In this journey, empirical evidence about the nature of the litigants is required. In this article, we establish a dataset about these matters, and measure the shares of financial firms, non-financial firms and individuals. We find that in Mumbai, financial firms filed 52% of cases, and that 83% of cases were against individuals. Cases filed by financial firms are likely to be disposed quicker than those filed by individuals. We explore how the cheque is used as a means of credit, and why financial firms accept them as collateral / security. It appears that financial firms are using cheques and Section 138 as a coping mechanism for poor civil remedies. While there is a need for legal system reform in the context of S.138 of the N.I. Act, it would also be useful to find solutions in banking regulation and personal bankruptcy law. We conclude with a recommendation of caution. Just as the amendment in 1988 has led to certain behaviours and industry practices, new solutions will alter the equilibrium, creating new incentives and new behaviours. The patterns seen in Mumbai are not present in regions of lower economic activity like Jhabua-Nimar. We need to be aware of the wide differences across different districts and states of India, and be mindful of complexity, as we proceed on the path to legal system reform.

Introduction

Section 138 of the Negotiable Instruments Act, which was introduced in 1988, creates the possibility of imprisonment for upto two years, a fine upto twice the amount of the cheque, or both, in response to cheque bouncing. The Act prescribes a six month time horizon for disposing these cases. This 1988 amendment is widely used as an example of the need for judicial impact assessment: The legislative action substantially enhanced the load upon the judicial branch, but there was a lack of commensurate operational planning and resourcing to deal with the enhanced case load.

What fraction of the pending cases or the flow of new cases emanates from this? A precise answer to this is not feasible under the present state of legal system data in India, but it is likely to be about 15 per cent (Chapter 3, Law Commission of India, 2014 ^[1] ; Supreme Court in Makwana Mangaldas Tulsidas vs The State Of Gujarat, 2018 ^[2] ; Mahadik D, 2018 ^[3] ). An important paper in this literature, Damle and Gulati, 2022 ^[4] examines 363,720 cases across 8 States and 2 Union Territories and estimates that cheque dishonour cases represent 13.2% of the courts' workload and take 395 days for disposal.

One pathway to legal system reform lies in an 80:20 analysis, in a vertical approach of finding solutions that are specific to certain classes of matters. Many thinkers have proposed making progress on S.138 of the N.I. Act as a component of legal system reform (Law Commission of India, 2008 ^[5] ; Law Commission of India, 2009 ^[6] ). Alongside this is the proposal for decriminalisation of cheque bouncing, broadly drawing on the concept that debtors prisons are not how modern economies operate. All these discussions require more knowledge about the nature of litigants in these matters, which is presently lacking.

This article seeks to fill this gap. In their paper, Damle and Gulati, 2022 ^[4] establish that the impact of Section 138 cases on caseload, pendency and time to disposal varies by State. We ask the questions: Who are the litigants in Section 138 cases? Does the nature of cases vary based on who the participants are? Do these characteristics vary based on location?

Methodology

The e-courts database for district courts was used to build a dataset about pending and disposed cases relating to Section 138 of the Negotiable Instruments Act. This was done for India's most advanced region (Bombay). For a comparison, this was also done for the group of districts (termed "homogeneous region" by CMIE) with the highest share of households in agriculture. This is the "Jhabua-Nimar" homogeneous region, which comprises six districts in Madhya Pradesh - Alirajpur, Barwani, Burhanpur, Dhar, East Nimar (Khandwa), Jhabua, West Nimar (Khargone). These two datasets thus show the full range from the old India to the new India.

Litigants were classified into three groups:

• Financial Firms
• Non-Financial Firms
• Individuals

This was done through a process of looking for keywords in the name:

1. Financial Firms typically have the terms bank, finance, invest, loan, and related keywords and variations.
2. Non Financial Firms have terms like ltd, pvt, corporation.
3. Non Financial Firms may contain common nouns from the English Language.
4. Litigants with the term proprietor in the name were categorised as individuals.
5. Those that did not fit these criteria were categorised as individuals.

This classification heuristic requires a standard corpus of English words. We used the NLTK Wordnet corpus and identified all words in the names of litigants that overlapped. A manual cleanup was required as the corpus contained some proper nouns. We assessed the words which made up 95% of the instances of overlap with the corpus and eliminated names and common nouns that could be Indian names ("Rout", "Harsh", "Baby", etc.). In Mumbai, we found 8133 unique words appearing 763,593 times. The 95% filter resulted in 1,165 unique words in Mumbai. For Jhabua-Nimar, we found 1,006 unique words appearing 19,974 times. The 95% filter resulted in 345 unique words.

These heuristics will of course engage in a small rate of misclassification. Some names like Banku and Chitra containing the terms Bank and Chit could be classified incorrectly. We do not account for firms that have common nouns in their name from languages other than English. In many cases, an individual proprietorship may have the term company or finance in their name. The methodology does not take into account spelling errors.

In order to assess the accuracy of the work, it is important to estimate the defect rates associated with these heuristics. We manually analysed a random sample of 100 cases (and 200 litigants) in each district, in order to measure the error rate. We found two errors in our Mumbai analysis. They are:

1. Ms M. D. Vora Co. is a non-financial firm categorized as an individual.
2. Alexander Xavier Dsouza is an individual categorized as a non-financial firm. Alexander is present in the wordnet corpus, and appears 16 time in the dataset which puts it in the bottom 3% of words by frequency, which is why it was excluded in the manual cleanup.

Similarly, we found seven errors in our Jhabua-Nimar analysis. They are:

    Two cases where non-financial firms with names in Hindi were misclassified as individuals:

1. Shri Krishna Prajapati Sakh Sahkari Sanstha Maryadit.
2. Shubhalakshmi Sakh Sahkari Sastha Mrya. Dhamnod By Nitesh Bhawsar.

    Two cases where financial firms with typos were misclassified as individuals:

3. EEASVAM KREDIT KO DVARA VIJAY.
4. BHARATEEY STET BAIANK MUKHY SHANABAG BURAHANAPUR.

    One case of an individual misclassified as a financial firm:

5. Kashish Finance H.U.F Propriter Vijay Rathore.

    Two cases where the State was a party. The State was misclassified as a non-financial firm.

This suggests a defect rate of 1% for Mumbai and 3.5% for Jhabua-Nimar. This gives us a sense of the extent to which the estimates presented ahead should be treated with caution.

Results

In Mumbai, we have a dataset of 417,437 cases. Of these, 317,225 are disposed, and 99,712 cases are pending.

Table 1: Section 138, NI Act cases in Mumbai district courts classified by Type of Litigant

Respondents → Petitioners ↓	Financial firm	Non-financial firm	Individual	Total
Financial firm	0.2%	6.5%	46.2%	52.8%
Non-financial firm	0.1%	7.0%	21.3%	28.4%
Individual	0.2%	4.8%	13.8%	18.8%
Grand Total	0.5%	18.3%	81.2%	100.0%

This yields the facts:

• Finance firms filed 53% of cases, non-financial firms 28%, and individuals 19%.
• 81% of cases were filed against individuals, 18% against non-financial firms and less than 0.5% against financial firms.
• The biggest chunk of cases are financial firms vs individuals - 46%, followed by non-financial vs individuals - 21%.

In Jhabua-Nimar, we have a dataset of 22,564 cases. Of these, 14,130 are disposed, and 8,434 cases are pending.

Table 2: Section 138, NI Act cases in Jhabua-Nimar district courts classified by Type of Litigant

Respondents → Petitioners ↓	Financial firm	Non-financial firm	Individual	Total
Financial firm	0.0%	0.2%	12.3%	12.5%
Non-financial firm	0.0%	0.6%	5.2%	5.8%
Individual	0.1%	2.1%	79.5%	81.2%
Grand Total	0.1%	2.9%	97.0%	100.0%

• Individuals filed 82% of cases, finance firms 12%, and non-financial firms 6%.
• 97% of cases were filed against individuals, 3% against non-financial firms.
• The biggest chunk of cases are individuals vs individuals - 80%, followed by finance firms vs individuals - 12%.

At an overall level, disposal rates in Mumbai are close to 90%+ for years before 2015, from where we see a steady decline in share of cases disposed. Thus today's pending cases are largely those that began after 2015.

Figure 1: Total Cases by Year and % of Cases disposed as of April 2023

In Figure 1 above, the blue bars on the chart are the total number of cases filed. The orange line depicts the % of the cases filed in that year which stand disposed as of April 2023 when the data was analysed.

In Mumbai, we see an interesting pattern when we compare the disposal rates of cases filed by financial firms, non-financial firms and cases filed by individuals.

Table 3: Share of cases filed in a specific year that stand disposed as of 2023

Year	Financial Firms	Non-Financial Firms	Individuals
2015	74.0%	65.9%	66.9%
2016	61.1%	60.7%	66.4%
2017	77.8%	50.8%	51.1%
2018	75.9%	47.9%	41.1%
2019	48.8%	42.8%	28.9%
2020	75.3%	35.0%	27.6%
2021	42.2%	25.5%	19.6%

This table shows the share of cases that were filed in Mumbai in a certain year that are now disposed. An important finding here is that cases filed by financial firms have a much higher likelihood of getting disposed in 2-3 years compared with cases filed by individuals.

Figure 2: Cases filed between 2015-2021 by Status and Type of Litigant

In Figure 2 above, we see that Financial Firms account for 60% of the total cases filed, but constitute ~70% of the cases that have been disposed, and account for only 50% of the pending cases.

We see no such patterns in Jhabua-Nimar with disposal rates not being dependent on the nature litigant filing the case.

Discussion

We now have new facts about litigation associated with the S.138 of the NI Act. What have we learned? How does this change our mind? What are the downstream implications of this new knowledge?

Most attempts at reforming Section 138 have focused on on improving the processing speed within courts. Little has been done towards preventing cases emerging in the first place. Our data shows that financial firms are the main petitioners in Mumbai, with a higher disposal rate than individual litigants or non-financial firms. This may reflect greater organisational capability in financial firms. Cases filed by individuals or non-financial firms vary based on the nature of contract entered into by the two parties. We speculate that cases filed by financial firms are mostly related to loans.

Financial firms often use cheques as an alternative form of collateral. This can help individuals with poor credit ratings to access loans. Should there be a loan default, there is the choice of filing a criminal case. This process is expedited by Section 138 that requires petitioners to file a case within 45 days of the cheque bounce. Banking regulations may also be a contributor. In December 2016, the Supreme Court ruled that officers of private banks are to be treated as public servants under the Prevention of Corruption Act. Financial firms have practices to ensure that a debt is indeed irrecoverable before they can classify it as bad debt. The large volume of cases from banks may be a mechanism to check against petty corruption from branch officials and comply with regulatory requirements.

Filing a Section 138, NI Act case not only allows a bank official to demonstrate effort and intent, it also allows the lender access to the coercive power of the State. The police arriving with a non-bailable warrant at your doorstep is a persuasive means of negotiating with a borrower. Petitioners in a Section 138 case are using this to recover dues. Are there better civil alternatives to debt recovery? How does their efficiency in terms of time to disposal compare with those in Section 138 cases? As we think of improving processes, we should consider the possibility that making Section 138 cases more efficient may prevent litigants from considering civil recourse. The combination of slow civil courts and under-developed credit markets make Section 138 cases an attractive proposition for financial firms. Accepting cheques as security may have developed as an industry practice because it allows financial firms to be less diligent when making loans as they can now rely on the criminal justice system to coerce settlement. In addition to court processes and legislative changes, remedies to the burden of Section 138 on the Indian courts may also lie in the realm of banking regulation, credit practices, and personal bankruptcy law.

The introduction of Section 138 has resulted in some discernable behaviors from financial firms. Future changes to the status quo will invariably alter incentives resulting in different behavioral patterns among litigants. The variation in litigant composition between different regions illustrates that litigation patterns are shaped by local context. The patterns observed in a metro like Mumbai, largely influenced by financial firms, don't find a parallel in areas such as Jhabua-Nimar. Attempts at legal system reform must account for the disparities across the various states and districts of India. We caution against one-size-fits-all solutions and suggest that solutions be crafted keeping in mind the local context.

References

[1] 245th Report On Arrears And Backlog - Law Commission of India, 2014 . Retrieved from 20th Law Commission of India.

[2] Makwana Mangaldas Tulsidas vs The State Of Gujarat , Order dated 5 March, 2020. Retrieved from Supreme Court of India.

[3] Mahadik D, 2018. Analyses of Causes for Pendency in High Courts and Subordinate Courts in Maharashtra. Retrieved from Department of Justice.

[4] Damle D, Gulati K et al. 2022. Characterizing Cheque Dishonor Cases in India: Causes for Delays and Policy Implications. SSRN.

[5] 213th Report on Fast Track Magisterial Courts for Dishonoured Cheque Cases, 2008. Retrieved from 18th Law Commission of India.

[6] 230th Report on Reforms in the Indian Judiciary - Some Suggestions, 2009. Retrieved from 18th Law Commission of India.

Siddarth Raman is a researcher at XKDR Forum.