Credit Risk

How to Predict Bankruptcy Risk and Help Safeguard Your Lending Portfolio

How to Predict Bankruptcy Risk and Help Safeguard Your Lending Portfolio

June 12, 2024 | Tammy S. Vanwambeke

The current dynamic economic landscape presents a complex challenge for lenders. They have relied on traditional credit scores to assess creditworthiness. The increase in bankruptcies and delinquencies may call for a change in approach. Today, lenders need a more comprehensive strategy. 

Credit scores alone are still helpful. But there are more effective ways for lenders to forecast whether someone may become a bankruptcy risk. Alternative data can help lenders make smarter, more informed decisions. It can help lenders tell the difference between people who are financially stable and those who only look like they are. By moving beyond traditional payment history, lenders can better protect their portfolio and get a leg up on their competition.

Student loan repayment, inflation and affordability stressors are squeezing consumers from all sides. By excluding alternative data from their decisions, lenders may not have a complete view of a customer’s financial reality. This includes customers rated prime that are in trouble and could be close to bankruptcy. This is where advanced data science can help. Lenders can use advanced data science to get a holistic view of their customers. It can help lenders predict if a customer will file for bankruptcy.

Benefits of proactive approach to bankruptcy risk management

Lenders who adopt a proactive approach to bankruptcy risk management can:

  • Make more informed credit decisions: Use advanced data and analytics to gain deeper insights into consumer behavior and identify potential risks that might not be clear through traditional credit scores. 

  • Protect their portfolios: Mitigate potential losses and safeguard your financial stability.

  • Navigate challenges with confidence: Provides you the agility needed to react to economic uncertainty.

More on the Power of Predictive Analytics

Embracing predictive analytics allows lenders to gain deeper insights into consumer behavior and identify potential risks that might not be clear through conventional methods. Machine learning and neural networks can analyze vast amounts of data. By analyzing the trended data you can forecast bankruptcy potential with greater accuracy.

Tools like the Bankruptcy Navigator Index (BNI) 5.0 shows the potential of predictive analytics. BNI utilizes sophisticated data science, including NeuroDecisionⓇ Technology, to predict the likelihood of an individual filing for bankruptcy within the next 24 months. This empowers lenders to make more informed credit decisions and proactively manage their portfolios.

The Path Forward

In a time of economic uncertainty, lenders cannot afford to rely only on traditional credit scores. By embracing innovative data science methodologies and leveraging predictive scoring tools, lenders can:

  • Make more informed decisions in their portfolio

  • Confidently navigate challenges

Discover how we are empowering lenders with data and advanced analytics to predict and mitigate bankruptcy risk. 

Learn more. 

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Tammy S. Vanwambeke

Tammy S. Vanwambeke

SVP Financial Services and Enabling Technology

Tammy VanWambeke is a Financial and Technology services executive with leadership experience driving and sustaining growth for Fortune 500 companies. She is currently responsible for leading Equifax’s Financial Services Group inclusive of Mid Market banks, Credit Unions, Retailers, Finance Companies, Sales Agents and E[...]