Digital Disruption and Debt Resolution: A New Paradigm
Shivangi Gupta
5th Year BA. LL.B.(Corporate Law Hons.), School of Law, UPES, Dehradun
Introduction
“AI is present to provide a facilitative tool to judges in order to recheck or evaluate the work, the process, and the judgements.”
– Justice Dr. D.Y. Chandrachud
India has been criticised for falling behind the other nations in the development of its corporate economy by failing to follow trends in the western countries [[1]]. Aligned with the vision of Prime Minister Narendra Modi, numerous endeavours have been made to enhance the global perception of India’s corporate economy through the introduction of the groundbreaking laws that will significantly pave the way for the nation’s economic growth and development. Since 2014, India’s legal and procedural framework for the corporate sector has improved significantly. The regulations that were in place to address insolvency and bankruptcy had become outdate and old, which hindered the growth and expansion of companies [[2]]. Since the election of a new administration in 2014, significant changes have been made to the corporate and financial environment, including the introduction of the Goods and Service Tax, the modified Arbitration and Conciliation Act, Labour Reform, and the most important the Insolvency and Bankruptcy Code, 2016 (hereinafter known as Code).
The Code is widely regarded as the most significant economic reform in the legislative history of India, having completely redesigned the country’s credit ecosystem [[3]]. It represented a paradigm change from the previous laws, which were inadequate to address and resolve domestic insolvencies and were extremely fragmented and ineffectual [[4]]. A unified process for addressing corporate insolvency in India is offered under the Code. It seeks to improve efficiency with the insolvency and bankruptcy legislation framework by dividing the judicial and business aspects of the process. India now ranks higher on the ease of doing business index thanks to the substantial reinforcement of the regulatory framework guiding the liquidation, rehabilitation, and rebirth of failing commercial organisations. The Code introduces a major shift by moving from the prior tactic of “debtor in possession” to “creditor in possession”.
Restructuring and insolvency could be compared to the business equivalent of critical care, where a group of experts is assembled to give certain enterprises palliative treatment while assisting the others in their quest for recovery [[5]]. The insolvency process entails applying existing laws, regulations, and protocols to particular circumstances that differ throughout businesses. Usually, this means keeping track of enormous collections of business documents. This area is highly suited for the use of use of artificial intelligence (hereinafter known as AI) in the fields of data collection, classification, and process optimisation due to its integration of variables and rules. Before moving ahead with how technology like AI is affecting the insolvency and bankruptcy process, it is important to discuss the meaning of concepts like AI.
- Definition
John McCarthy, known as the father of AI, coined the term AI [[6]]. It is defined as capacity of computers or other machines to exhibit or simulate intelligent behaviour [[7]]. An example of an AI is IBM’s Watson Oncology which is able to recommend a treatment when relevant details of a patient are fed into it [[8]]. A similar application, Ross intelligence, is available for law. Ross can respond to legal questions after searching through legal databases and other documents [[9]]. Law firms that use Ross tend to treat it as a sort of research assistant [[10]]. Specifically, the American law firm Baker Hostetler has used Ross for insolvency cases [[11]]. There are several other AI tools in the market that are aimed at the legal sector.
Another example of an AI application is Chat Generative Pre-Training Transformer (hereinafter known as ChatGPT) which is able to interact with users conversationally. Its developer, OpenAI, claims that this ability to have a dialogue with the users makes it possible for ChatGPT to answer follow-up questions, admit its mistakes, challenges incorrect premises, and reject inappropriate requests [[12]]. Thus, this type of AI system can be used by non-experts as well. However, the system is also said to be unreliable. ChatGPT has been known to provide wrong answers and so only experts are able to use the application safely, and they too must be sure to double-check the answers generated [[13]].
AI Meets Law
It’s time to move on to the particular uses of AI in legal practice after giving a basic review of the technology. The use of computer and mathematical processes to the legal system in an effort to make it more understandable, manageable, practical, accessible, and predictable is fundamental to the idea of “AI and law” [[14]].
Scholars have been actively integrating computer science and AI principles into the subject of law since the mid-1900s. Calculus creator and attorney by profession, Gottfried Leibniz, was among the first to advocate using mathematical formalisms to solve legal issues [[15]]. The development of AI in the legal industry has largely followed the trend of the industry overall [[16]].
Knowledge representation and rule-based legal systems were early priorities for AI in law, as they were for AI in general [[17]]. However, starting about 2000, the emphasis in AI and law, like the rest of the field, has moved away from knowledge-representation techniques and towards machine-learning-based approaches [[18]].
- Interplay of AI and Technology in Insolvency Process
Technology is sometimes the most disregarded aspect of bankruptcy transformation, but it is also a crucial component that helps a bankrupt firm turn around and become a competitive organisation [[19]]. Given that we live in a technologically advanced period, technology is integral to our way of life. AI is quickly transforming the way the bankruptcy and litigation matters are managed. AI technologies are being utilised to increase the productivity and precision of document review instances. This is a different world than the one we were born into [[20]]. Technology has changed how we live, work, shop, communicate, and conduct business in the last few years. It has become a part and parcel of our daily routine without which humans cannot function. More recently, the COVID-19 pandemic and the need for lockdowns and social distancing throughout all the jurisdictions pushed the law to update by introducing technologies that were already in place and being used in other circumstances. Examples include video conferencing for court hearings and certain legally mandated meetings.
- Integration of Technology and AI in the Insolvency Process
The Code of 2016 brought about a paradigm shift in the Indian financial crisis resolution system, re-orienting it fundamentally and establishing a predictable, market-driven, and time-bound bankruptcy and insolvency system [[21]]. Evidence, however, indicates that excessive delays are plaguing court proceedings under the Code, which runs counter to the goal and purpose of the Code [[22]]. In this context, it has been recognised that information asymmetry and a lack of access to trustworthy financial data are causes of delay. To address this, the Code incorporates measures such as reporting requirements and requires information utilities to increase informational synergy amongst different stakeholders [[23]]. However, it seems that these actions have not been sufficiently successful.
Information asymmetry and lack of access to trustworthy financial information about the corporate debtor that is undergoing insolvency are frequently a major cause of procedural delays because concerned parties (like creditors and resolution professionals) must run from pillar to post in order to determine the financial position of the corporate debtor and obtain pertinent information regarding its debts and defaults [[24]].
- Impacting Three-Stages of Insolvency
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- Pre-Insolvency
Elaborate plans and documentation are required because of how drawn out and rigorous the Indian insolvency process is. One practical way expedites the process is to predict insolvency early on, or pre-insolvency [[25]]. Investors will be able to control risks if they can predict when a company would fail. Before advances in technology, experts would forecast a company’s insolvency based on its financial standing. But the advent of AI has revolutionised the insolvency evaluation process because it can radically change the process in terms of resource and time efficiency [[26]].
In the process of assessing insolvency, businesses gather vast amounts of information to help them satisfy the needs of their clientele and maximise profits [[27]]. When handled by human agents, managing massive volumes of data – also known as Big Data – that are distinguished by their enormous volume, quick velocity, and broad variety requires a substantial time commitment [[28]]. On the other hand, AI algorithms are designed to efficiently manage databases of this size in a much shorter amount of time and with fewer resources, avoiding the otherwise high requirements. Furthermore, machine learning specialists are utilising a range of machine learning approaches, including logistic regression, support vector machines, lasso regression, utilising decision trees and bagging to accurately forecast insolvency [[29]].
- Corporate Insolvency Resolution Process
When a corporate debtor or creditors defaults in payments, the Code’s corporate insolvency resolution procedure is started [[30]]. It entails a number of steps, including completing an application, starting a moratorium, forming a committee of creditors, hiring resolution specialists, and more. Big data is involved in this laborious procedure, which is often handled by resolution professionals. AI can greatly reduce the amount of the time required for the corporate insolvency resolution process (hereinafter known as CIRP) because Ais are built to handle large amounts of data easily. Through its evaluation of a company’s key performance indicators, AI may assist resolution professionals in making swift and decisive decisions [[31]]. AI can identify relationships between performance metrics and insolvency risk, allowing businesses to be alerted before they fail [[32]]. Investigators may utilise these AI algorithms to do file discovery searched on significant email servers and storage repositories. The AI algorithm accelerates the development of cases and the distribution of results by strengthening its ability to recognise sources and documents. Consequently, the period of time between filing and the CIRP’s commencement is significantly shortened. In the near future, professionals’ productivity can be raised and costs can be decreased by combining AI with CIRP. A statement issued by National Company Law Tribunal, Justice Ramalingam Sudhakar said “One aspect for early resolution is the development of AI technology … we are focusing on leveraging AI and standardisation of processes. This will help in reducing delays. We are also focused on evolving a code of best practices so that there is certainty in decision making. [[33]]”
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- Liquidation
Though it hasn’t been completed yet, time-bound liquidation has been a pillar of the Code since its beginning. The Insolvency and Bankruptcy Board of India (Liquidation Process) (Amendment) Rules, 2019 stipulate that the liquidator must finish the liquidation process within a year [[34]]. As per the data provided by the Insolvency and Bankruptcy Board of India (hereinafter known as IBBI), over 79% of active liquidation processes have exceeded the authorised time frame [[35]]. Because of their diligent labour, the authorities released the IBBI amendment on simplifying liquidation in June 2022 [[36]]. The Code’s objective of maximising asset value has been hampered by the inordinate delay in the liquidation procedure [[37]]. To be successful, a monitoring committee, a requirement for a shorter time limit, and other IBBI redressal proposals need innovative solutions. One such innovation is the introduction of AI and data analytics tools into the liquidation process.
In addition to this, the e-auction’s inconsistent nature presents a significant issue that must be addressed. The IBBI proposed several remedial actions, such as a dedicated auction website, distinct intervals between consecutive auctions, etc [[38]]. The authorities will have difficulties in putting these proposals into practice despite their recommendations. AI will save the day in these situations because of the development of promising AI technologies that employ machine learning to conduct optimum auctions. Since the liquidator is currently the only one in charge of managing both conventional and non-conventional data, the problem of time-bound liquidation still exists.
Global Perspective
Since courts have historically played a major role in formal insolvency procedures, it is necessary to investigate how technology might revolutionise court procedures. A concerted effort has been made in recent years to digitise and automate various activities and processes in the court system. The ongoing worldwide epidemic has focused attention on the advancement of this trajectory by serving to enhance and concentrate these efforts. AI looks to be acceptable in the legal system, including insolvency in developed nations like the US and the EU. AI technologies such as Data 61, Data Lex AI, and ROSS, which are trained for advanced analytics, modelling, and scenario planning based on financial performance, have been a huge a help to insolvency legislation [[39]]. Considered a classic example of AI deployment, LDM Global created its AI tool “Accelerator”, which helped the professional services firm provide positive outcomes in the insolvency procedure [[40]].
As a result of its unparalleled legislative powers and in reaction to the economic crisis, in 2021, the Colombian government adopted a decree permitting the application of AI to the administration of bankruptcy proceedings. The same year, new computerised features were added to the superintendence of companies, a government body that has been Colombia’s bankruptcy court for almost fifty years. The module is called as Insolvency Module [[41]]. Users interacting with the insolvency system will experience something new and profound thanks to the employment of this AI tool, which is easily accessed via the agency’s website. In the same year, the UK government fulfilled its pledge to put in place a “national AI strategy” to supervise AI governance and encourage the application of AI to legal and enforcement processes, including bankruptcy procedures [[42]]. In London, the Rolls Building Jurisdictions used the electronic pilot approach in 2015 [[43]]. In this system, which is already required in some court environments, e-filing is available 24/7.
Portugal has exhibited a proactive stance in incorporating various technological solutions with the objective of optimising and digitising legal proceedings. Reputable members of the legal profession, such as judges, public prosecutors, solicitors, enforcement agents, and insolvency practitioners, can easily access and use CITIUS, an excellent platform [[44]]. Finland in July 2019, adopted a revision to its Bankruptcy Act with the objective of addressing various difficulties, including the development of administrative efficiency in the application of the legislation, and digesting the same. In order to speed legal proceedings, the improvements included lowering administrative costs and minimising the court interference. As a result, it can be deduced that AI is more widely applicable in insolvency law enforcement than it is in India.
Benefit and Risks
- Benefit
An unintended but important benefit of various countries including India using the kinds of technological tools mentioned above in bankruptcy procedures – especially e-portals – would be the availability of data that can be utilised to assess a nation’s economic standing on a global and national level. These data can be used by local law reform initiatives to customise solutions for the particular circumstances. Data from each nation would show the efficacy of the insolvency law (and other pertinent elements) if countries made this data available. This comparative scope would promote international competition and regulatory learning. The enhanced openness that technology will provide will guarantee that stakeholders and, in high-profile cases, the general public, are able to trust the process.
After going over, the past uses of technology, particularly AI, in bankruptcy law, it’s critical to comprehend the dangers and make sure they are appropriately managed.
- Risks
The concern with AI deployment in any setting is that the algorithms may produce biassed, erroneous, or inaccurate results. As suggested by Sir Geoffrey Vos, the former problem can be resolved by making sure AI is first exclusively employed for small-scale decision-making and that stakeholders have the opportunity to appeal the result. When the government, regulator, or court, as the case maybe, is collaborating with developers to create or acquire an AI system that will be utilised on an official basis, bias will need to be taken into account throughout the testing stage. In the end, the option to challenge an AI system’s judgement will serve as a safeguard against this specific worry. Likewise, before depending on these technologies, professionals dealing with insolvencies, legal companies, and other AI users in the market will need to test them.
Data security and privacy is the other main issue that is frequently brought up in relation to AI use. These problems arise even from the simple digitisation of court procedures or other phases of the insolvency process. Similar to Finland, there will need to be clarification on the legal responsibilities of various parties and the people in charge of running the electronic platform with regard to the handling of personal data. Furthermore, efficient management of the systems integrity and security (e-portals, etc) will be required.
It will also be ineffective to mandate the use of technology in bankruptcy procedures without providing court employees, regulators, and insolvency specialists with the necessary training and instruction. Any state looking to formally integrate technology into bankruptcy procedures has to make sure that the required training is given.
Conclusion
The incorporation of technology and AI into the insolvency process signifies a radical shift in how financial crisis is managed. This paper has emphasised that the Code’s implementation in India has established a strong basis for the modernisation of insolvency procedures. Although technology makes insolvency resolution more accurate and efficient, it also brings with it new difficulties such as algorithmic bias, data privacy issues, and the requirement for practitioners to receive specialised training. Because of these intricacies, a cautious approach is required to guarantee that the advantages of technology breakthroughs be fully realised while reducing any potential hazards.
Furthermore, the worldwide view on AI’s use in bankruptcy shows that other nations are effectively using technology to improve their administrative procedures. Instances from countries such as Portugal, Finland, and Colombia demonstrate how creative digital solutions can enhance the effectiveness and openness of bankruptcy procedures. India can improve its own insolvency ecosystem by taking important cues from these global examples as it develops its legal framework. Proactive technology adoption can result in more successful dispute settlement techniques and ultimately improve the state of the economy.
To conclude, there are obstacles on the path to incorporating technology and AI into insolvency law, but there are also a lot of chances for advancement. Through promoting cooperation between legal experts and technological specialists, interested parties can establish an insolvency procedure that is more effective and transparent. To foster systemic trust as India adopts these innovations, it is critical to address moral issues and guarantee legal compliance. In the long run, effective technological integration will support economic growth and stability generally in addition to improving the efficacy of insolvency practitioners.
References:
[1] Ankeeta Gupta, Insolvency and Bankruptcy Code 2016: A Paradigm Shift within Insolvency Laws in India, (2018).
[2] Rajeswari Sengupta, Evolution of the Insolvency Framework for Non-Financial Firms in India, (2023).
[3] Saumy Kanti Gosh and Saket Hishikar, Economic and Financial Impact of IBC, (2021).
[4] M.S. Sahoo, A Journey of Endless Hopes, (2019).
[5] Joanna Goodman, Artificial Intelligence in Insolvency Work: Transforming Critical Care, (2023).
[6] S.L. Andresen, John McCarthy: Father of AI, (2023).
[7] Ibid.
[8] Akshaya Kamalnath, Rethinking Liability and Licensing for Doctors in the Era of AI: Insights from Company Law, (2018).
[9] Amit Chowdhry, Law Firm Baker Hostetler Hires: A Digital Attorney Named ROSS, (2016).
[10] Ibid.
[11] Karen Turner, Meet Ross, the newly hired legal robot, (2023).
[12] OpenAI, (https://openai.com/index/chatgpt/).
[13] Sara Merken, New York lawyers sanctioned for using fake ChatGPT cases in legal brief, (2014).
[14] Dickfos Jennifer, The Impact of Artificial Intelligence on the Insolvency Profession, (2017).
[15] Frans Coenen and Trevor Bench-Capon, A Brief History of AI and Law, (2023).
[16] Ibid.
[17] Christopher Collins, Denis Dennehy, Kieran Conboy, Patrick Mikalef, Artificial Intelligence in information systems research: A systematic literature review and research agenda, (2021).
[18] Ibid.
[19] Shannon Stucky Pritchett and Rachel Chesley, Rethinking Bankruptcy the importance of focusing on Talent, (2023).
[20] Jarrord Munro and Emily Jarman, The Impact of AI on the Insolvency Industry, (2023).
[21] Sreyan Chatterjee, An Empirical Analysis of The Early Days of the Insolvency and Bankruptcy Code, 2016, (2018).
[22] M.S. Sahoo and Anuradha Guru, Indian Insolvency Laws, (2020).
[23] Ankeeta Gupta, Addressing Challenges of Information Asymmetry in Financial Sector using Information Utility.
[24] Supra note 25.
[25] Jane Colstone and Christian Toms, The Role of Artificial Intelligence and Technology in Global Bankruptcy and Restructuring Practices, (2019).
[26] Sakshi Pandey and Harshvardhan Singh Sikarwar, Placing the Artificial Intelligence on the Insolvency Spectrum, (2022).
[27] Tibor Kezelj and Rudlof Gruenbichler, A Systematic Literature Review on Corporate Insolvency Prevention using Artificial Intelligence Algorithms, (2021).
[28] Franco Varetto, Genetic Algorithms Applications in Analysis of Insolvency Risk, (1998).
[29] Ibid.
[30] IBC, 2016 Sec. 6 (India).
[31] Samal Manohar, International Insolvency, Bankruptcy Law and Artificial Intelligence, (2022).
[32] Jose Garrido, The Use of Data in Accessing and Designing Insolvency Systems, (2018).
[33] https://economictimes.indiatimes.com/news/india/artificial-intelligence-could-beused-for-early-resolution-of-matters-says-nclt-president/articleshow/90464442.cms?from=mdr.
[34] IBBI (Liquidation Process) (Amendment) Regulations, 2019.
[35] https://ibbi.gov.in/uploads/whatsnew/b3a47a6df67ffb00832dc7baec47123c.pdf.
[36] Ibid.
[37] Ravi Mittal, Leveraging the Behavioural Change, (2022).
[38] https://ibbi.gov.in/uploads/whatsnew/b3a47a6df67ffb00832dc7baec47123c.pdf.
[39] Aditya Narvekar and Debashis Guha, Bankruptcy Prediction using Machine Learning and an Application to the Case of the COVID-19: Recession, Data Science in Finance and Economics, (2022).
[40] Gavurova Beata Artifical Intelligence in predicting the Bankruptcy of non-financial corporations, (2022).
[41] Nicolas Polania Tello, Columbia is using AI to improve Insolvency Proceedings, (2022).
[42] Biamca Piachaud, An Overview of the UK’s National AI Strategy, (2022).
[43] Akshaya Kamalanath, The Future of Corporate Insolvency Law: A Review of Technology and AI Powered Changes.
[44] https://www.portugal.gov.pt/pt/gc24.
