Credit & Risk

How To Assess The Value Of AI-Driven Lending

Zest AI team

August 25, 2021

Lenders everywhere are breaking their dependence on legacy credit scoring and switching to AI-driven credit underwriting models. Why? AI-driven models are more accurate, more fair and transparent, and deliver a wide range of business improvements.

Among them:

  • Higher revenue and profit
  • Increased efficiency and decisioning speed
  • Enhanced market competitiveness
  • Increased automation
  • Improved customer & member experience

But getting AI-driven lending right means doing your homework. You have to get an accurate ROI assessment. So, to help your organization think through the variety of value-for-money decisions and squeeze the most out of an investment in artificial intelligence and machine learning (AI/ML), we put together “Doing The Math,” a free guide to assessing the value of AI-driven lending.

Download your free Zest Guide, "Doing The Math: How To Assess The Value Of AI Lending."

The guide is organized based on the way Zest's experts present our business analysis to clients. It’s a format honed over a few years to ensure that models and results come across in a comprehensive and easy-to-understand fashion. You’ll learn how to judge the statistical performance of AI models (see chart below) against your current benchmarks and test the durability of the models' decisions over time. You’ll also understand how to translate that performance into business impact and how to factor in the benefits to your wider underwriting operation (e.g., greater automation and faster decision making).

This chart shows how models built using Zest improve statistical accuracy over generic credit scores when trained to predict delinquencies older than 60 days within 24 months.

ML’s  ability to price across risk tiers more precisely and effectively allows you to implement risk-based pricing programs that boost yield significantly. More accuracy also means more instant approvals and faster decisions can lead to higher booking rates. Whatever economic gain you arrive at, remember to factor in the value of  timely decision-making. One credit union we’re working with ran a financial  analysis that showed an increase of $1 million in incremental profit per month  from switching to an ML model. You can use that kind of immediate ROI to fund  a host of other digital transformation initiatives. Why wait?

The guide is packed with helpful charts and graphics that put the numbers into better light. It's free of technobabble and jargon, designed to be something you can share with your entire lending team.

Download your free copy of the Guide, "Doing The Math," today.



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