Friday, June 16, 2023

Announcements

TrustBridge is an organisation that works on improving Rule of Law for better economic outcomes. We focus on understanding the gaps in the existing legal and regulatory framework, evaluating how they impact economic growth, and studying the various ways that these could be improved upon. We aim to undertake legal, quantitative and policy oriented research and dissemination that will inform principles and evidence-based policy making. We believe that implementing ideas that emerge from our research will help bring us closer to our objective of improving the Rule of Law. Our work is in the areas of Energy Transition, Financial Markets, Contract Performance in government and private contracts, and Governance in the start-up ecosystem.

TrustBridge is looking for two full time associates to work on its projects.

Position 1: Quantitative Research Associate

As a quantitative research associate you will deploy quantitative techniques to create and analyse data sets and to generate insights about the problems we are working on.

The requirements for the role are:

  • Prior demonstrable experience of working with R, Python, Julia and other open source tools for generating statistical/economic analysis.
  • A degree or a professional qualification in Mathematics, Statistics, Economics or Computer Science will be desirable.
  • You must be curious and passionate about research and be comfortable working in an interdisciplinary environment. You must be ready to work on independent outputs as well as function in teams.

Position 2: Policy Research Associate

As a policy research associate you will be required to work on projects that seek to engage with governments and with the private sector to generate sustainable reforms in the areas of our interest.

The requirements for the role are:

  • A Master's degree or a professional qualification in economics/management/public policy, strong written and oral communication skills.
  • Prior work experience in the the areas of interest to TrustBridge.
  • A quantitative/computational orientation will be a plus.
  • You must be curious and passionate about research and be comfortable working in an interdisciplinary environment. You must be ready to work on independent outputs as well as function in teams.

The remuneration offered will be commensurate with your skill and experience.

Please send an email with your CV to careers@trustbridge.in if you are interested.

Thursday, June 15, 2023

Helping litigants make informed choices in resolving debt disputes

by Pavithra Manivannan, Susan Thomas, and Bhargavi Zaveri-Shah.

The Indian legal system faces numerous difficulties, and the discourse on legal system reforms has emphasised the workings of the courts from the perspective of judges and registries. Such a focus is not so useful for litigants who are also participants in the legal system. The decisions that they make and the incentives that they face add up to create the case load at the courts.

Consider a supplier of spare parts to a certain manufacturer, who has not been paid her dues. Her lawyer advises her of multiple legal remedies that she can use to recover her dues, from filing a money suit before a civil court to pursuing arbitration proceedings outside a court to initiating insolvency proceedings against the manufacturing company. How would she decide which legal remedy to pursue? More generally, litigants make four classes of decisions: Should one sue? Should one appeal? When faced with a certain proffer, should one settle? When alternative forums are available, which one to prefer? Flaws in a litigant's decision making when faced with such decisions reshape the case flow of courts. In the Indian legal system reform discussion, it is important to think about the incentives and the decision-making of litigants.

At present, litigants make these decisions based on their own, generally limited, prior experience. They are advised by lawyers who specialise in a certain forum. However, lawyers tend to be specialists in one forum or another, and often know impressions rather than systematic evidence. Further, lawyers have an interest in the litigant's decision. Under these conditions, the decisions of litigants might sometimes be sub-optimal.

First steps in measurement

All the four types of litigant decisions - to sue, to appeal, to settle and to choose a forum - involve forecasting the time taken in the legal process, and associated expenses. In an ideal world, litigant decision making would be supported by statistical systems that forecast these two numbers.

In this article, we develop a legal system measurement that can produce such insights for litigants, who are litigating on a narrow class of problems. We do this for three Bombay courts, as a proof of concept of a simple analysis that can help litigants.

The narrow class of problems that we focus on are debt dispute resolutions. Several laws in India allow the enforcement of debt contracts in different forms, which provides us a unique opportunity to compare their relative performance in providing redress for debt default. There are also multiple courts and tribunals that adjudicate disputes on debt contracts in different ways. We choose three in Bombay to study:

  1. The Bombay High Court which has original jurisdiction to adjudicate high value contractual matters.

  2. The Mumbai bench of the Debt Recovery Tribunal (or DRT), which is a specialised tribunal that has been adjudicating recovery of debts due to banks and financial institutions since 1993.

  3. The Mumbai bench of the National Companies Law Tribunal (or NCLT), which is a specialised tribunal adjudicating insolvency petitions against companies.

We build on earlier work that points out that litigants are found to care about the access, efficiency, effectiveness, independence, and predictability of judgements (Manivannan et al, 2023). It is known that secondary data (such as those from court websites) have constraints: (a) it can be used to measure only a subset of these aspects; and (b) even this subset cannot be necessarily computed for all the comparable courts. Assuming that access is not a constraint, Manivannan et al (2023) suggest that the litigant can get an estimate of what she can expect of the amount of time in the court, for each of these courts. They point out that it is possible to get an estimate of what she can expect of costs she will incur, through the expected number of hearings at a given court, where each hearing induces a certain unit cost.

In this article, we move towards three new questions in the field of litigant decision making:

  1. How likely is it to get a first hearing in the first year from filing the case in the court?
  2. How likely is it that the matter will get disposed in the first year from the filing of the case?
  3. How many hearings are most likely to take place in the first year from the filing of the case?

While the first two questions help to address the efficiency in terms of time expected in a court, the third can be used as a proxy for the kind of costs that a litigant can expect from a given court, since every hearing requires the time of (and fees charged by) legal counsel.

Data description

We collect and analyse sample data of cases involving debt disputes, which were listed and heard at three courts in Bombay for the period from September 2021 to December 2022 ('sample period'). The websites of these fora record cases filed across different timelines and do not archive case life cycles of historical cases. This sample period allows us to compare cases that have been filed at the same time and therefore have comparable life cycles.

  • In the case of the Bombay HC, the selected matters include suits, summary suits, commercial suits and commercial summary suits, filed under its original jurisdiction.

  • For the DRT, we extract cases arising under the Recovery of Debts Due to Banks and Financial Institutions (RDDBFI) Act, 1993, and the Securitization & Reconstruction of Financial Assets & Enforcement of Security Interest (SARFAESI) Act, 2002.

  • For the NCLT, we extract all cases listed under the Insolvency and Bankruptcy Code (IBC). We understand that cases involving debt enforcement will be covered under these case-types at the relevant court.

Table 1 shows the number of cases in the data set for all the three courts. We additionally include the status of these cases as pending or disposed. A case is categorised as disposed of by the courts where the disposal is by way of a decree passed by the court, or if it is settled, or it is has been withdrawn for any reason.

Table 1: Distribution of cases

Court Total Disposed Pending
Bombay HC 1243 159 1084
DRT 843 125 718
NCLT 2645 897 1748

Thus, for the same period of time, there have been a different number of applications in the matter of debt dispute resolution in these three courts.

While, this can be used to calculate the 'disposal rate' of matters in each court, these measures suffer from two limitations. It does not take into consideration the duration of the pending cases. Further, it does not take into account that the amounts involved and the complexity are different in the cases handled at different courts. An approach that takes these aspects into account is the survival analysis modelling approach.

Statistical analysis

'Survival analysis' is a method for modelling the time to an event of interest. If the event of interest is the time to disposal, the model will yield the estimated probability of a case being completed between any two timepoints t1 and t2.

Survival analysis models have been previously employed to study judicial delays including at the Income Tax Tribunals (Datta et al, 2017) and at the NCLTs (Shah and Thomas 2018, Bhatia et al, 2019). In this article, we draw on the intuition of survival analysis and offer simple estimates of two quantities (for each of the three courts):

  • What is the probability of a case being being heard atleast once within one year? The first hearing is generally an important milestone for a litigant to know the possibility of getting interim relief. How likely it is that this will happen within the very first year?
  • What is the probability that the case is disposed of in the first year?

These probabilities are estimated for each of the three chosen courts separately on matters of debt dispute resolution. Much of the earlier research have computed and presented sample means of completed cases only, without taking into account cases that have not been completed. The standard techniques of survival analysis fare well on harnessing information using observations of cases that have not completed as well.

Q1: Chances of getting a first hearing in the first year from filing of a case

Figure 1 presents a graph of the survivor function for a matter getting a first hearing across the Bombay HC, the DRT and the NCLT. Here, time to first hearing is on the x-axis. We pull up the probability of getting to the first hearing within a year from these curves for the three courts and present this in Table 2.

Table 2: Chance of first hearing within the first year at Bombay HC, DRT, NCLT

(in %)
Bombay HC 36.6
DRT 94.0
NCLT 99.8

A case at the NCLT has the highest chance (of nearly 100%) of being heard with the first year from its filing. There is nearly a similar probability of a first hearing at the DRT within the first year, with a 94% chance. At the Bombay HC, on the other hand, there is a less than 40% chance that a similar matter will get a first hearing within a year of being filed.

Using this approach, we could similarly estimate the probability of a case being heard atleast once within say, the first three months of filing. Our analysis finds that for a litigant at the NCLT, there is an 86% chance of getting atleast one hearing within the first three months of filing a case. The corresponding probabilities for the DRT and the Bom HC are 74% and 5% respectively.

Q2: Chances of getting a case disposed in the first year from filing of a case

Figure 2: the survivor function for disposal for three courts

Figure 2 shows the litigant the chances of a debt dispute resolution matter getting disposed, within one year of it being filed in each of these three courts. This presents a very different picture than for the survivor function for the chances of getting a first hearing that we see in Figure 1. The chances of disposal are (logically) much lower at any given point in time. Table 3 presents the chances of disposal of case within the first year of being filed. The NCLT has the highest chance of disposal at nearly 40%. Between the Bombay HC and the DRT, the DRT has a higher chance at 17.3%. But the Bombay HC has a similar chance at 16.3% of the case being disposed within the first year.

Table 3: Chance of disposal within the first year at Bombay HC, DRT, NCLT

(in %)
Bombay HC 16.1
DRT 17.0
NCLT 39.3

Q3: Expected number of hearings in the first year from the filing

So far, we have focused on the time to completion, which matters greatly through its impact upon the net present value of the moneys recovered. We now turn to the question of the costs of ligitation. We compute the expected number of hearings within the year and present these in Table 4. We recognise that there is a sharp distinction between substantial hearings and infructuous hearings, but in the present state of the research, we treat both alike.

Table 4: Expected number of hearings within the first year at Bombay HC, DRT, NCLT

Number
Bombay HC 0.4
DRT 2.7
NCLT 4.0

The NCLT has the highest expected number of hearings within the first year of filing at 4 hearings, while the Bombay HC has the least (not even one hearing may happen within the first year of filing).

Using these estimates, a litigant can estimate her legal costs for the first year. For example, we now know that a litigant will face 4 hearings, on average, in the first year after filing at the NCLT. If the legal fees that she is charged by her legal team are Rs.100,000 per hearing, on average, this implies that she can expect to pay Rs.400,000 in the first year from filing.

Discussion

Better decisions by litigants are not only valuable for the litigants, but will also improve the working of the Indian legal system. We have shown simple statistical results about delay and costs at three alternate venues for one narrow class of matters. These results point out the differences that exist among three courts, in terms of the kinds of legal remedies they offer, their administrative processes and their capacity. Litigants would have to weigh those considerations also in their thinking.

These results have many interesting implications. For instance, if a bank strategically prefers an early first hearing, it might be better off instituting proceedings at the NCLT compared to the DRT, even if the latter is a forum dedicated to banks and financial institutions. On the other hand, if a bank prefers disposal within fewer hearings compared to an earlier first hearing, the analysis indicates that it is better to approach the DRT.

We recognize that there may be other considerations that weigh with the litigant in making her decisions. For example, Mannivannan et al, 2021 find that litigants also care about the fairness of a judge and the effectiveness of the remedy. But our analysis in this article focuses on metrics that can be evaluated with secondary data from courts. Another consideration is that the analysis does not consider the nature of the legal remedies offered by the three courts. While litigants may approach the Bom HC and the DRT for debt recovery, the NCLT offers a remedy of insolvency resolution. But creditors in India find it optimal to use both recovery and resolution processes to recover their dues. Finally, it is not that the litigant prefers one forum over another, but that important metrics such as the probability of disposal within a given time frame allows the litigant to choose one among multiple choices of forum.

We believe that the comparative approach in this article can be extended in, at least, three ways. First, these measures can be calculated for locations other than Bombay. A comparative exercise of this kind can potentially help understand benches with bottlenecks and potential areas of improvement. Second, within this class of matters, statistical modelling can permit these estimates to vary with case characteristics. Finally, these measures needs to be calculated beyond this narrow class of matters. For example, such an approach could offer more clarity to litigants involved in involuntary litigation, such as criminal litigation.

The data used for this analysis can be found here. The dataset can be cited as Manivannan, Pavithra and Thomas, Susan and Zaveri-Shah, Bhargavi (2023), "Helping litigants make informed choices in resolving debt disputes".

If you're interested in seeing other WIP applications of this framework, XKDR Forum is organizing a roundtable in Mumbai on the 17th of June (Saturday).

References:

Bhatia, S., Singh, M., & Zaveri, B. (2019). Time to resolve insolvencies in India. The Leap Blog, March 11, 2019.

Datta, Pratik & Surya Prakash B. S. & Sane, Renuka, (2017), Understanding Judicial Delay at the Income Tax Appellate Tribunal in India, Working Papers 17/208, National Institute of Public Finance and Policy.

Manivannan, Pavithra and Thomas, Susan and Zaveri, Bhargavi, Evaluating Contract Enforcement by Courts in India: A Litigant's Lens (November 26, 2022). Also available at SSRN: https://ssrn.com/abstract=4286562.

Shah, A., & Thomas, S. (2018). The Indian bankruptcy reform: The state of the art, 2018. The Leap Blog, December 22, 2018.


Pavithra Manivannan and Susan Thomas are researchers at XKDR Forum. Bhargavi Zaveri-Shah is a doctoral candidate at the National University of Singapore. We thank Ajay Shah for inputs on the survival analysis, Geetika Palta for research and data support, Tushar Anand for helping out with corrections to the data, and participants of the internal seminar series at XKDR Forum for their comments and feedback.

Monday, June 05, 2023

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:

  1. EEASVAM KREDIT KO DVARA VIJAY.
  2. BHARATEEY STET BAIANK MUKHY SHANABAG BURAHANAPUR.

    One case of an individual misclassified as a financial firm:

  1. 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.