How Advanced Data Analytics Make Credit Decisions More Inclusive

How Advanced Data Analytics Make Credit Decisions More Inclusive

At Aurionpro Fintech, we understand that in the world of lending efficiency, speed, and maximizing results are crucial. Lenders are constantly seeking better, faster, and smarter ways to operate, and rightfully so. Data has always been the cornerstone of sound lending decisions. 

However, as the diversity and volume of available data grow, banks, credit unions, and other lenders must find innovative ways to leverage these insights. This opens the door to significant advantages, including expanding credit opportunities for more consumers.

Embracing advanced data analytics doesn't have to be daunting. Modern technology allows lenders to harness the power of data in valuable ways without requiring massive infrastructure overhauls. Here’s how you can maximize your results and create new opportunities that benefit both consumers and your own bottom lines:

1. Improving Risk Assessment to Broaden Access to Credit

The banking industry has made strides in incorporating new data into lending decisions, but there’s still room for improvement to ensure all consumers have access to fair and affordable credit. Traditionally, lenders review a consumer’s credit profile to assess their creditworthiness. However, this standard approach often excludes millions of potential borrowers.

Research indicates that 106 million Americans, or 42% of the adult population, are either credit invisible, unscoreable, or have a subprime credit score. This traditional method of credit assessment leaves these individuals behind. By leveraging expanded Fair Credit Reporting Act (FCRA) data, lenders can score more consumers and bring them into the mainstream credit ecosystem. This approach allows lenders to expand their applicant pool without compromising risk tolerance, ultimately promoting financial inclusion.

2. Reducing Deployment Timelines for Credit Models

One significant challenge in the banking industry today is the increasing sophistication of credit models, which often leads to longer deployment timelines and higher costs. For instance, while sandbox environments allow lenders to build and test custom models, moving these models into production can be a lengthy process.

According to our research, It takes an average of 15 months to build and deploy a credit decisioning model, with 10 months dedicated to deployment alone. Furthermore, 55% of lenders have built models that never reach production, creating significant inefficiencies.

Modern solutions allow for models created in any popular open-source language or development platform to be deployed and run without additional technical support, significantly enhancing operational efficiency.

3. Automating the Monitoring of Credit Models

In a rapidly changing environment, lenders must be able to adapt quickly to trends in the banking industry. As consumer behavior evolves, so must the models used to make credit decisions. While periodic monitoring for model drift is common, advanced analytics now allow for continuous monitoring without operational strain.

Automation provides significant advantages in this context. Continuous monitoring ensures that credit models remain accurate and fair, reflecting current and predictive consumer behavior. For example, if a consumer misses a payment but subsequently rectifies it, lenders should have near real-time visibility into this change. Similarly, if a consumer applies for multiple loans from different lenders in a short timeframe, lenders should be aware of this promptly.

By leveraging advanced analytical tools, lenders can proactively monitor and track credit model performance, leading to more accurate risk assessments and fairer treatment for consumers.

4. A Win for Lenders and Consumers

In summary, the use of advanced analytics, including AI and ML, helps reduce operational inefficiencies and allows lenders to gain meaningful insights from large volumes of data with speed and accuracy. This technology enables lenders to deploy better predictive models and helps more consumers access fair and affordable credit.

At Aurionpro Fintech, we are committed to helping lenders leverage advanced data analytics to create more inclusive, efficient, and innovative credit decision processes. Together, we can drive better outcomes for both lenders and consumers.

Ready to transform your lending operations with advanced data analytics? Contact Aurionpro Fintech today to learn how our solutions can help you expand credit opportunities and improve operational efficiency.

Experian. (2024). EXPAND AGILITY & INSIGHTS Report: Accelerating model Velocity in Financial Institutions. https://us-go.experian.com. Retrieved August 7, 2024, from https://us-go.experian.com/accelerating-model-velocity-report