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Teachers Federal Credit Union Leverages AI to Revolutionize Lending

The Benefits of AI-Based Lending

The use of artificial intelligence (AI) in lending has long been a topic of debate, with concerns over bias, discrimination, and lack of transparency. However, with the increasing demand for fast and personalized lending experiences, many financial institutions are now embracing AI-based lending as a key differentiator.

  • Speed: AI-based lending allows for instant decisions, reducing the time and effort required for manual underwriting.
  • Personalization: AI models can analyze vast amounts of customer data to provide tailored loan offers, increasing the likelihood of approval.
  • Scalability: AI-based lending enables financial institutions to originate loans at scale, without increasing headcount.

A Case Study: Teachers Federal Credit Union

Teachers Federal Credit Union, a $9.8 billion-asset institution based in Hauppauge, New York, has recently launched an AI-based lending platform to approve credit cards, auto loans, and personal loans.

“For our members and customers in the banking sector, the expectations continue to shift and accelerate, and they demand fast, seamless, personalized experience,” said Brad Calhoun, CEO of Teachers Federal Credit Union.

The credit union began working with Corridor Platforms’ Riskdecisioning.AI software a year ago, and has since automated underwriting for 80% to 90% of loans. Customers fill out standard loan and credit card applications on the Teachers website, while Corridor’s machine-learning models make the loan decisions, which are then validated by human credit experts.

How the AI Model Works

The AI model uses FICO scores and credit bureau data from TransUnion to gain a standardized risk view across borrowers. It also creates a proprietary score for each customer by analyzing credit bureau data alongside customer account data, taking into account member-specific insights such as payment behaviors, job status, and paycheck size.

Key Features
  • Uses FICO scores and credit bureau data from TransUnion
  • Creates a proprietary score for each customer
  • Analyzes customer account data to provide tailored loan offers

Benefits for Teachers Federal Credit Union

The AI-based lending platform has enabled Teachers Federal Credit Union to improve its lending efficiency, reduce manual underwriting time, and increase the number of approved loan applications.

“The models have been trained not only using internal loan performance data, but also enriched with trusted bureau data from TransUnion in our case, so every decision is fully explainable, auditable, and aligned with fair lending standards,” Renganathan said.

Challenges and Opportunities

While AI-based lending offers many benefits, it also raises concerns over bias, explainability, and regulatory compliance. Financial institutions must carefully consider these challenges and opportunities as they implement AI-based lending solutions.

Key Challenges
  • Bias and discrimination
  • Explainability and transparency
  • Regulatory compliance
Key Opportunities
  • Improved lending efficiency
  • Increased approval rates
  • Enhanced customer experience

Conclusion

Teachers Federal Credit Union’s adoption of AI-based lending demonstrates the potential for this technology to revolutionize the lending industry.

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