Rishabh Goel, CEO & Co-founder of Credgenics

 An IIT-Delhi alumni turned into a Co-founder and CEO, Rishabh has done his certifications in FRM and CFA, both of which empower his business acumen while enabling him to keep a track of the technological updates and improvisations required for the Credgenics platform. Before this idea of a SAAS-based platform came to him, he gained experience in the Banking sector and loan repayment processes prevalent while working with Deutsche Bank and Blackrock.


Chronological orders play a substantial role in our understanding of the history. With each crisis we see societal and sociological changes. But with this humanitarian crisis called COVID-19, the economic impacts have been global. Yet the possible end of this disease is not within sight, nor do we know what all variants and the many waves that could give us further jolts. Under the given circumstance, it becomes challenging for the economies to see a stable revival, and the Indian economy is no exception.

In 2020, the way the world came to a standstill with the first wave, the magnitude of impact could not have been foretold. Especially now that we are quickly moving towards the end of another fiscal year, we should think about defense mechanisms to be put in place for the immediate future and the longer term. The banking and financial ecosystem needs to put disproportionate focus on credit risk management. Risk analysis has been fundamentally built on top of historical data and associated trends. In the latest of unique data points, moratorium benefits and Loan Restructuring reliefs availed by borrowers can enrich existing risk models for predictive analysis. Job recession and associated repayment challenges had also made it difficult for the lenders to understand repayment capacity in the near term, but can serve as useful insights for pressure test on credit capacity for individuals. Simultaneously, the borrowers are also finding it difficult to keep up with the frequent changes in policies from the cream financial institutions, governing bodies and the judiciary. In a way, 2020 can be touted as the year that has provided fresh and unusual data points for future analysis.  

The Reserve Bank of India, in its nomenclature for credit risk management has already instructed a few rudimentary steps, such as the credit risk policies and strategies to be curated and revised “regularly”. It also states that, and we quote ‘The document should include risk identification, risk measurement, risk grading/ aggregation techniques, reporting and risk control/ mitigation techniques, documentation, legal issues and management of problem loans.’ 

Before we suggest how we can control risks in a tumultuous scenario, we can implement some quick remedies in the early stages itself. In the onboarding, and transaction initiation stage, clear lending criteria and verification strategies should be drawn. This can significantly control the deviations observed during portfolio management, leading to a smaller size of the problematic loans. In the larger scenario, however, we must have critical warning systems built on data from large recessions and economic depressions. They can help flag the potential stress in the portfolio, should a similar economic catastrophe were to occur in the present. A proactive management of metrics that follow, could help reduce the time taken for policy restructuring and reviving portfolio health for a brisk recovery. For instance, if the recovery risks had well ben formulated, there would have been enough and ample technology support system already in place to prevent bad assets from bloating.

This warning system is also going to prove a major help with the distressed borrowers. As soon as potential distress accounts are identified, lenders can get into proactive communication with those accounts. Timely communication and flagging of risk to the borrowers themselves, can prevent such an occurrence.  It is a win-win situation for both parties and helps solidify trust through positive solutioning while avoiding the need for any harsh recovery efforts.

As a thriving financial ecosystem, we need to understand how important it is for us to manage our data. The latest status of a particular case needs to be monitored closely and recovery strategies framed accordingly. Predictive analysis complemented with this data would help us find more solutions for even the probable risks. A good data management system would also help in understanding the efficacy of the recovery efforts and building case studies / playbooks for the financial ecosystem that we are a part of. With increased visibility on overall risk and reduced stress in the portfolio, the consequential recovery efforts would also reduce with visible improvement in associated time and cost deployed. The data management however has to be technology driven, with proper cyber security measures in places. Yes, the drive towards technology has begun and the government is also supporting technological advancement but things need to be paced and processes be expedited.

Smart borrower segmentation is another topic that lenders have yet to address. In the COVID reality, it is important to know which account is viable, which is non-viable, and which are viable but distressed owing to circumstances. This way, the recovery mode can be channelized effectively. This is just like setting up a chatbot for the simpler problem-solving situations – segmentation can help streamline recovery efforts. The analogy might seem unfit, but look at it like this, chatbots help in focusing better on unusual issues, so the lenders also need better effort management in understanding the circumstantially distressed accounts. The data for the three segments above can be set and efforts be regulated accordingly. For instance, while the litigation angle be approached without much delay for the truly non-viable ones, offers such as reduced installments or periodic moratorium can be provided for the viable but distressed accounts.

Communication would be the key. The changes in risk management policies and norms that we discussed, and the finding from data management should be communicated properly – to all teams, branches, offices and borrowers. Graphical presentations, simplified communication, brief lists can help circulate this information with borrowers and internal users effectively. Transparent communication with borrowers would also result in a overall healthy relationship with the bank / FI. Communication helps as much with the feeling of being included as with the uncertainty associated with opaque risk practices. 

The last basic step for better credit risk is establishing a proper team or committee that would make the policies, watch the trends, ensure periodic revisions and trigger the communication. Credit risk management needs to be treated as a profile that would be increasingly important in the current evolutionary stage of our economy. We need better professionals and processes. Ultimately any risk can be managed well if we give enough importance to the building strong foundations, transparency and proper communication.

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