Search interesting materials

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.

No comments:

Post a Comment

Please note: Comments are moderated. Only civilised conversation is permitted on this blog. Criticism is perfectly okay; uncivilised language is not. We delete any comment which is spam, has personal attacks against anyone, or uses foul language. We delete any comment which does not contribute to the intellectual discussion about the blog article in question.

LaTeX mathematics works. This means that if you want to say $10 you have to say \$10.