Case Studies

A large financial institution wanted to grow its consumer lending business without loosening risk standards. With more than 1 million loan applications, it had scale, demand, and data, but its underwriting approach was not capturing the full opportunity.

 

Traditional models and decision rules worked well for standard borrower profiles, but were less effective at identifying creditworthy applicants outside legacy segments. As a result, valuable growth opportunities remained hidden across the application funnel and portfolio.

 

Using pert.AI, the institution uncovered these opportunities, improved decision precision, and generated measurable business impact.

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The Challenge

The institution needed to expand lending responsibly in a competitive market. It wanted to approve more of the right borrowers, improve offer uptake, and grow into new segments without compromising risk or control. Like many large lenders, it faced several structural limitations:

• Traditional underwriting models were too rigid to capture the full value of many applicants

• High-potential underserved segments were not visible through legacy segmentation logic

• Relevant data was spread across multiple systems and formats

• Any new solution had to be fast to implement, explainable, and enterprise-ready

The business did not need more applications. It needed a better way to turn existing data into smarter lending growth.

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The Solution

The institution deployed pert.AI within its existing data environment to optimize consumer lending decisions.

pert.AI integrated diverse data sources, analyzed historical decisions and outcomes, and identified patterns missed by conventional models and business rules. This enabled the institution to move beyond static segmentation and take a more dynamic view of borrower opportunity and risk.

With pert.AI, the lender was able to:

• Expand credit safely within its risk appetite

• Improve alignment between borrower needs and credit offers

• Identify new underserved segments with strong business potential

• Shorten time to value from months to weeks

 

The Results

+14% Credit expansion

+6% Uptake

 

New underserved segments identified
Additional growth opportunities surfaced across the portfolio, to be monetized over time

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6 weeks Time to value

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Why It Matters

For large financial institutions, growth is often constrained not by demand, but by the limits of traditional decision systems. When underwriting logic is too narrow or static, profitable borrowers and attractive segments can remain invisible.

This case shows how pert.AI helps lenders unlock that hidden potential. By turning complex internal data into better lending decisions, pert.AI enables institutions to grow faster, serve more customers, and do so with confidence.