4 Big Insights On the Future of Credit Risk Management in a Post-COVID World

With over 20 million recorded cases, and nearly 750 thousand deaths (as in mid-August 2020), COVID-19 is here to stay. Economies across the world are in different stages — from complete shutdowns to partial reopening to back-to-normal— but everyone is facing a new, unfamiliar environment. 

Lending institutions are no exception to this general upheaval. According to S&P, the COVID-led recession is likely to affect credit metrics well into 2023. As the economic situation changes rapidly across the globe, banks and NBFCs find themselves in an unforeseen situation. The rules of the game have changed overnight, and they now have to monitor and manage credit risk in the face of limited access to reliable data and limited visibility. 

Having said that, the way forward is already becoming clearer. New approaches are emerging — and nimble banks and NBFCs have already started implementing them. Based on our conversations with multiple stakeholders in the lending game — from banks to new-age NBFCs to fintech startups — certain patterns have emerged. Here are the most important ones:

Determining credit risk is now a whole different ball game

Most risk managers today have a very hazy idea about the risk levels of their current portfolios. Credit history, which was the primary factor in assessing credit risk in the pre-COVID days, is no longer the only factor at play. Today, credit risk is being affected by a host of dynamic issues. 

For starters, the pandemic is affecting different sectors in a very different way, which is now going to play a big role in real-time credit risk assessment. Here’s a look at how different sectors have been affected with very different intensity:

Source: McKinsey

Apart from this, there’s also the pace of reopening. Different subsectors of the economy are reopening at a different pace across different geographies. Then there’s always the risk of a new wave of the disease — which can stall things and delay the recovery. 

On top of that, things like the financials and business models of individual households and companies will become more important than before. A borrower’s financial status and future prospects will also play a big role — especially in microlending. 

All this just goes to show that the existing credit assessment frameworks require some rapid transformation. And the financial institutions that want to stay on top of the problem are already implementing these changes. 

Feeding crisis data into the decision engine

Given the complexity of the situation, financial institutions are using high-frequency analytics to transform their existing decision engines. When it comes to credit underwriting, there has been a rapid shift toward using real-time business data in both analytics and decision-making. 

This real-time data includes very detailed analyses at the subsector level. In fact, even within subsectors, there’s the fact that different geographies will recover at different rates, depending on how they’re coping with the pandemic. Then there’s data on individual resilience within a subsector — how equipped is the borrower to ride out the crisis. This will depend largely on factors like financial stress and operational flexibility. 

In other words, most leaders in the space have pressed the accelerator on building a more real-time, AI and ML-based decision engine. This is expected to be more than just a temporary trend. There is now going to be a permanent shift towards data science-driven practices to manage credit risk.  

Better infrastructure to monitor the existing portfolio and credit book

With the credit scenario changing so quickly, financial institutions are focussing on setting up the right monitoring infrastructure. This will become crucial to manage credit risk, both in the short and long run. 

Most banks and NBFCs are trying to figure out which segments of the credit book are really important to monitor at this time. These would include:

  1. Customers who’ve been laid off
  2. Customers who are unemployed or underemployed
  3. Customers who’ve seen pay cuts
  4. Those customers who are employed in high-risk sectors and sub-sectors
  5. Customers who aren’t making any long-term credit card purchases since the crisis

Microcredit will see an upsurge

As people’s disposable incomes get impacted, and consumers struggle to maintain their current lifestyle, microcredit will see a big surge. Microcredits will not only be used for buy-now-pay-later type solutions but could also be used for more basic expenses like payment of utility bills. 

The extent to which a financial institution can take advantage of this trend will depend on two things. The first is their focus on process automation — things like e-KYC, automated loan offerings, and contactless lending. The other is how effectively they’ve been leveraging technologies like AI, ML, and Big Data analytics to assess credit risk. 

New-age NBFCs and fintech startups that focus on digital micro-loans will win big if they are able to incorporate the complexity of the current environment into their current credit risk algorithms. 

The bottom line

In the current environment, banks and NBFCs have to walk a tight rope. They need to firefight and minimizing the downside risk, while also building capabilities that will accelerate the rate of recovery in the medium term and create a strategic advantage in the long run. The shift towards more complex, real-time data analysis — backed by emerging technologies like AI and ML — will create a much more data-forward and differentiated credit underwriting ecosystem.

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