As lenders start catering to newer borrower pools with innovative products such as BNPL, credit lines, purchase financing and instant term loans, they are seeking ways to sustainably grow their loan books while limiting risk exposure.

Meet Monish, Risk Head at a legacy lender, who is currently pivoting towards new-age lending products. One of his key responsibilities is to maximise revenue and customer retention and mitigate risk while facilitating the pivot. 

He is looking for a tool that offers a holistic view of the borrower's financial health and, in turn, mitigates credit risk .

To help Monish and other decision makers like him, we've compiled a list of four broad steps to implement a credit risk mitigation strategy in any lending organisation. 

What is Credit Risk Mitigation?

Credit risk mitigation refers to a set of measures lenders take to minimise the risk of losing their money due to defaults on interest and principal repayments. 

The outcomes of defaults can range from minor to significant revenue loss for lenders. Therefore, risk-based pricing, covenant insertion, post-disbursement monitoring and limiting sectoral exposure strategies are some of the key tactics implemented to mitigate credit risk . 

Credit risk mitigation is lending institutions to avoid a surge in defaults and non-performing assets (NPA), which can negatively impact their financial performance. By implementing solid credit risk mitigation practices, lenders can protect their loan books while achieving financial stability. 

What Are the Benefits of Credit Risk Mitigation For Lenders?

There are several benefits of credit risk mitigation for lenders. Most of these benefits are based on the 5Cs of credit : character, capacity, capital, collateral and conditions. 

These 5Cs help assess a borrower’s creditworthiness, resulting in the following:

1. Lowered Credit Risk Exposure and Improved Risk Management Efficiency

Lenders can reduce their exposure to credit risk, which leads to improved risk management efficiency. Lenders can manage their risk exposure better and make more informed lending decisions. They may also be able to reduce their capital requirements and obtain capital relief .

This can be achieved by:

By provisioning for NPLs, lenders can set aside funds to cover potential losses from these loans. 

Lenders can write off NPLs that are deemed unrecoverable through active portfolio reductions, which can involve sales and/or write-off of provisioned NPL exposures. 

2. Reduced Cost of Lending

Credit risk mitigation helps lenders protect their capital but also helps them reduce the cost of lending by lowering instances of default. This, in turn, allows lenders to offer competitive interest rates and other incentives to borrowers, increasing the chances of successful loan repayment.

For example, by using risk-based pricing techniques, lenders can set lower interest rates for borrowers with lower risk, making for a better lending experience.

3. Improved Market Reputation

A well-structured and implemented credit risk mitigation strategy can help lenders boost their reputation in the market as they become known for their ability to manage credit risk. This will help them gain investor confidence, increasing the chances of gaining additional investments.

How can Lenders Use a Comprehensive Data Pool to Aid In Underwriting?

A comprehensive data pool can help lenders gain valuable insights into borrowers' profiles and past repayment patterns. 

By analysing data points like income, assets, debt, and property holdings, lenders can create a risk-scoring model that assesses each potential borrower’s creditworthiness.

Additionally, lenders can use this data to automate the underwriting process and reduce manual intervention in loan origination. By doing this, lenders can make quicker decisions regarding loan approvals and rejections and bring down the overall cost of origination.

By monitoring potential borrowers’ credit history and financial statements, lenders can detect any suspicious behaviour or activity that could lead to fraud and take necessary precautions.

3. Best Credit Risk Mitigation Strategies For Lenders

In India, the NPL ratio stood at 5.8% in March 2022. This indicates that despite credit risk mitigation and risk management efforts, there is still a need to implement better strategies among lenders and banks.

When it comes to credit risk mitigation, lenders have several available approaches. However, most strategies can be broadly divided into four categories: 

• Machine learning-based credit scoring models

• Real-time data analytics for credit risk assessment

• Automated fraud detection and prevention mechanisms

• Dynamic credit limit setting

Let's take a closer look at these four strategies to mitigate credit risk for lenders.

1. Machine Learning-based Credit Scoring Models

By leveraging advanced algorithms, machine learning-based systems can analyse borrowers’ financial data and predict their ability and intent to service future EMI payments. This credit risk analysis based on real-time data helps lenders identify potential loan defaults, allowing them to take proactive measures before they become problematic.

An example of a machine learning-based scorecard is the FinBox Inclusion Score, which is trained on India’s largest pool of new-to-credit borrowers. 

2. Automated Fraud Detection and Prevention Mechanisms

Automated fraud detection and prevention mechanisms can help lenders identify potential fraud activities before they become problematic.

Lenders can use AI-powered fraud detection systems to analyse customer data and identify potential risks before the fraud takes place. Proactive fraud detection and monitoring can improve lenders’ confidence in their borrower pool and reduce the possibility of financial and reputational loss.   

3. Dynamic Credit Limits 

One of the most important tools in a lender’s arsenal to improve their overall risk preparedness is to introduce flexibility into the product. Hence, products like overdrafts or credit lines through BNPL, etc., can take advantage of a dynamic credit limit - whereby the lender can increase or decrease the limit for each borrower based on their overall solvency and other financial metrics. 

This helps lenders not only delight good borrowers with automatic increases in their credit limits but also limits risk as banks can reduce exposure to delinquent borrowers. 

A way to do this is with a product like FinBox's DeviceConnect - an in-device, alternate data-based risk engine. The product helps lenders access 5,000+ alternate parameters, which can help assess risk better and thus aid in determining the appropriate loan amount, repayment period, and monthly instalments. 

Hence, the lender can not only decide whether a loan should be given or not, but it can also continuously change the credit limits based on the borrower’s repayment trends and other factors. 

How Can FinBox Help You With Credit Risk Mitigation?

DeviceConnect helps implement credit risk mitigation by providing enriched scorecards that add depth to risk underwriting. It is an in-device risk engine that looks at various data points to flag high-risk and potentially fraudulent applications, which lenders should verify before disbursal. 

DeviceConnect sifts through millions of data points to produce the FinBox Inclusion Score (FIS), which merges with existing underwriting workflows to supercharge risk assessment and reduce credit losses. 

This is especially useful for borrowers who are new to credit or have limited formal credit history, as it helps them get access to credit easily. 

DeviceConnect is an SDK installed into the lender's mobile app. It requires two integrations: one on the Android/iOS app from which users can share data and another on the backend to fetch predictors responsible for making decisions. The entire journey works on highly secure, anonymised, and encrypted pipes ensuring that privacy and data security are always prominently addressed. 

By leveraging FinBox’s artificial intelligence and machine learning-powered underwriting capabilities, lenders can extend credit even to MSMEs with a thin-to-no credit history. It can also create an early warning system, streamline the credit risk management process, and explore cross-sell possibilities for digitally acquired portfolios.

Request a demo today for DeviceConnect for a seamless lending experience.