The management of mounting non-performing assets (NPAs)/ non-performing loans (NPLs) has emerged as a critical challenge for banking and financial institutions today. Fortunately for the industry, stringent regulatory measures by the Reserve Bank of India (RBI) have been showing results with the gross non-performing asset ratio dwindling to 2.8% in March 2024 – a12-year low. The increasing adoption of technology to comply with robust regulatory mandates while assisting with the proactive detection and mitigation of credit risk has been instrumental to this transition.
Non-performing assets pose a significant threat to the financial stability and profitability of banks and the country’s economic progress. To tackle this issue effectively, institutions are increasingly turning to innovative solutions such as early warning systems (EWS). This blog explores how early warning systems can help in reducing non-performing assets and credit risk, ensuring a more secure and robust financial environment.
What are non-performing assets?
Non-performing assets are loans or advances that have ceased to generate income for the lender. This typically occurs when the borrower defaults on payments for a specified period, usually 90 days or more. Having a large number of non-performing assets can severely impact a bank’s balance sheet, eroding profits and diminishing investor confidence. Thus, managing and reducing non-performing assets is of paramount importance.
How do non-performing assets work?
Understanding how non-performing assets work is essential for effective management and reduction strategies.
Non-performing assets arise when borrowers fail to meet their repayment obligations for a specified period, typically 90 days. The lifecycle of a loan leading to a ‘non-performing asset’ status typically involves these stages: loan origination, possible servicing with timely payments in the initial period, eventual delinquency, and default. Once classified as a non-performing asset, the loan undergoes efforts aimed at recovery or resolution, such as loan restructuring, collateral seizure, or legal action. Financial institutions are required to report non-performing assets to regulatory bodies, which monitor the health of the banking sector.
What are the types of non-performing assets?
Non-performing assets can be broadly categorized as below:- Sub-standard assets
Loans that have remained non-performing for a period less than or equal to 12 months fall under this category. These assets still have a reasonable chance of recovery, and banks might focus on loan restructuring or other remedial measures during this period.
- Doubtful assets
Loans that have been non-performing for more than 12 months are classified as doubtful assets. Banks may need to make higher provisions for doubtful assets due to the increased risk of loss.
- Loss assets
These are loans that the bank or its auditors have identified as uncollectible and of such little value that they should be written off. However, they have not yet been written off completely due to pending legal actions or other recovery efforts.
- Restructured assets
Loans that have been modified to provide relief to borrowers fall under restructured assets. They carry a higher risk of relapsing to non-performing assets if the borrower fails to adhere to the new terms.
- Write-off accounts
These are loans that have been written off by the bank as bad debts. Write-offs are often used to clean up the balance sheet, but efforts to recover the loan amount continue.
The role of early warning systems in reducing non-performing assets and managing credit risk
What is an early warning system?
An early warning system is a proactive tool designed to identify potential risks before they materialize into significant issues. In the context of banking and finance, early warning systems utilize a combination of data analytics, machine learning, and predictive modeling to monitor loan portfolios and detect early signs of distress. They provide comprehensive risk assessment by analyzing vast amounts of data from various sources to evaluate the credit risk of each borrower, ensuring a holistic approach that considers all potential risk factors for more accurate assessments. By analyzing many factors such as transaction patterns, market conditions, and borrower behavior, early warning systems can provide timely alerts about potential non-performing assets, allowing banks to take action. Additionally, advanced predictive models used in early warning systems forecast potential defaults based on historical data and current trends, allowing banks to implement proactive risk mitigation strategies and thereby reduce overall credit risk.Benefits of early warning systems
- Timely identification of risk
Early warning systems enable banks to detect signs of financial distress in borrowers well before the situation escalates. This early identification allows institutions to intervene proactively, potentially restructuring loans or offering support to prevent default.
- Enhanced decision-making
By leveraging advanced analytics and real-time data, early warning systems provide valuable insights into the changing creditworthiness of borrowers. This aids in making informed decisions.
- Regulatory compliance
Early warning systems help banks meet regulatory requirements by ensuring timely reporting and management of distressed assets, thereby avoiding penalties and maintaining a good standing with regulatory bodies.
Conclusion
In today’s dynamic financial environment, the importance of managing non-performing assets and credit risk cannot be overstated. Early warning systems offer a robust solution to these challenges by providing timely insights, enhancing decision-making processes, and enabling proactive risk management. By adopting advanced early warning systems, banks can significantly reduce non-performing assets and credit risk, ensuring a healthier and more resilient financial ecosystem.
Authors
Ms. Jaya Vaidhyanathan
CEO, BCT Digital
Ms. Jaya Vaidhyanathan is an independent Director on several Boards and is focused on bringing in the best global corporate governance principles to India. Her work has found coverage in top news websites like The Hindu and The Times of India. Recently, she pioneered award-winning Early Warning Systems for Indian banks, which have found acclaim in the industry and among counterparts.
Shankar Ravichandran
Senior Manager at BCT Digital
His profound expertise in the field of corporate and retail banking spanning across Credit Risk, Transaction Banking, Service Delivery and Product Management is close to decade. He is an MBA graduate from Indian Institute of Management, Bangalore.
Author
Prashanth Belugali N
Principal Product ManagerPrashanth has two decades of experience working with large banks, asset managers, trading & capital markets models and model risk domain. He has worked as a quantitative analyst, delivery manager, and product engineer, and provided bespoke solutions in quants (asset management, trading) and risk management practices (credit risk, market risk, model risk), and data engineering to a global clientele
Author
Shankar Ravichandran
Senior Manager, Credit Risk
His profound expertise in the field of corporate and retail banking spanning across Credit Risk, Transaction Banking, Service Delivery and Product Management is close to decade. He is an MBA graduate from Indian Institute of Management, Bangalore.