In this second of two episodes with Kareem Saleh, Founder and CEO of FairPlay AI, host Vince Passione continues the conversation on how AI, to date, has fallen short of its potential to deliver a fairer lending environment for all consumers, but how addressing historical bias in the learning data can create a more equitable future.

Key takeaways:

0:00 Intro

1:00 How historical data–the data that AI is typically trained on–contains bias, and therefore can perpetuate bias in the future.

2:27 The challenges for lenders of using historical data that contains bias, but also has valuable insights, such as an individual’s repayment performance.

3:25 Sometimes lenders have to “test and learn” into new markets to define their risk parameters.

5:26 Racial and ethnic minority groups are often wrongly stereotyped as always being underserved and/or in need of fundamental financial services.

6:44 The more financial stimulus to enable lending in under-represented populations, the greater the opportunity to remove long-term bias from data sets and have a fairer AI-driven underwriting system in the future.

8:21 A detailed overview of FairPlay AI, the algorithms it uses to pursue fairer lending for all, and its outputs and outcomes.

13:02 The double-risks posed to lenders by climate change: The risks to their members and the commodities borrowed against, and the physical risk to lenders’ collateral.

14:47 How climate change also represents a powerful opportunity for credit unions to grow and deliver on their mission.

16:14 The lending opportunities for credit unions interested in addressing climate change.

16:48 The NCUA has made it clear they are hyper-focused on fair lending, particularly in the auto market.

Resources Mentioned:

• https://fairplay.ai/ Fairplay AI
• https://www.novacredit.com/ Nova Credit
• https://www.lendkey.com/podcast/credits-new-frontier-cross-border-records-and-the-role-of-cash-flow-data/ Misha Esipov episode
• https://www.cooperaconsulting.com/ Coopera Consulting
• https://www.lendkey.com/podcast/service-or-stereotypes-can-credit-unions-engage-multicultural-consumers/ Victor Corro episode
• https://www.filene.org/reports/the-changing-climate-for-credit-unions The Changing Climate for Credit Unions
• https://ncua.gov/regulation-supervision/regulatory-compliance-resources/consumer-compliance-regulatory-resources/fair-lending-compliance-resources Fair lending resources from the NCUA

Thanks for listening to the 22 Minutes in Lending podcast. If you enjoyed this episode, please leave a 5-star review to help get the word out about the show and be sure to subscribe so you never miss another insightful conversation.

#CreditUnions #FairLending #AI #Lending

In this first of two episodes with Kareem Saleh, Founder and CEO of FairPlay AI, host Vince Passione takes a deep dive into the world of AI underwriting: How it’s been used in the past, how it has fallen short of its potential to remove bias in lending decisioning, and how the pioneering concept of Fairness-as-a-Service may yet revolutionize the AI lending game.

Key takeaways:

0:00 Intro

2:06 How the murder of George Floyd compelled Kareem Saleh to look for ways he could more effectively change the system he operates in, and increase fairness for everyone.

3:08 Machine learning is capable of learning, but also of learning the wrong things.

3:55 Financial services regulators have clearly defined definitions of “fairness”: One focusing on disparate treatment, the other focusing on disparate impact.

5:18 One of the core challenges (and/or failures to-date) for using AI to mitigate bias is that it can only learn from the data it is trained on; and that typically over-represents certain populations.

8:49 Traditional logistic regression models don’t always work because they assume credit behaviors are linear. In reality, an individual’s financial behaviors are non-linear.

9:31 Unfairness can be born out of AI-driven models when seemingly independent variables interact with one another in a way that most humans wouldn’t interpret, but machines do.

10:01 Underwriting regulation and compliance hasn’t yet caught up with the technological capabilities of our AI-driven world.

11:56 Why monitoring an AI model’s fairness trends is critical.

14:40 Examples of ways seemingly disparate or arbitrary variables can interact with one another to bias an outcome–and how personal attributes are still being leveraged to a greater or lesser extent in decisioning models.

19:53 Concerns vs. regulatory comfort with using personal attributes like age and gender in decisioning.

22:44 The privacy implications, particularly in light of 1033, and how finding a way to share your personal information in some way–even if it’s just through the census–will help contribute to a fairer credit system.

Resources Mentioned:

• https://fairplay.ai/ Fairplay AI
• https://www.fdic.gov/system/files/2024-06/iv-1-1.pdf Fair lending rules and regulations
• https://www.justice.gov/crt/equal-credit-opportunity-act-3 Equal Credit Opportunity Act
• https://www.justice.gov/crt/fair-housing-act-1 Fair Housing Act
• https://www.lendkey.com/podcast/modern-credit-reporting-can-old-tech-handle-new-data/ Christian Widhalm, Bloom Credit, episode

Thanks for listening to the 22 Minutes in Lending podcast. If you enjoyed this episode, please leave a 5-star review to help get the word out about the show and be sure to subscribe so you never miss another insightful conversation.

#CreditUnions #FairLending #AI #Lending

In this episode, Misha Esipov, co-founder and CEO of Nova Credit, joins host Vince Passione to discuss the millions of “Credit Invisible” people in the country, and how innovations in credit reporting can help more lenders reach and serve them.

Key takeaways:

0:00 Introduction

1:29 Millions of people arrive in the U.S. each year, many of whom have been credit-worthy in their respective nations but the U.S. credit system doesn’t recognize their credit history.

2:19 There are around 100 million Americans whose credit data is inaccurate or incomplete and are missing out on loan opportunities as a consequence.

5:04 An overview of Nova Credit’s three core products: Cash Atlas, Income Navigator, and Credit Passport.

8:10 How, as a credit reporting agency (CRA) Nova Credit furnishes data to lenders and other credit bureaus.

9:00 The three core swimlanes of Nova Credit’s operations: data collection, analytics, and FCRA compliance.

9:48 The challenges preventing cash flow data from being recorded in traditional credit reporting bureaus' data–and the benefits for consumers and lenders when it is captured and used.

13:35 How government stimulus incentives issued through the pandemic may have skewed consumer credit information, and is leading to long-term underperformance on certain loans.

15:57 How Buy Now Pay Later transactions remain under-reported.

18:47 Augmenting underwriting with cash flow information is a journey. Any step towards it is progress.

21:09 Key takeaways from the inaugural Cash Flow Underwriting Summit, held in September 2024.

Resources Mentioned:

• https://www.novacredit.com/ Nova Credit
• https://www.unfcu.org/ United Nations Federal Credit Union
• https://www.novacredit.com/cash-atlas Cash AtlasTM
• https://www.novacredit.com/income-navigator Income Navigator
• https://www.novacredit.com/credit-passport Credit Passport®
• https://www.cashflowunderwritingsummit.com/ Cash Flow Underwriting Summit 2024

Thanks for listening to the 22 Minutes in Lending podcast. If you enjoyed this episode, please leave a 5-star review to help get the word out about the show and be sure to subscribe so you never miss another insightful conversation.

#CreditUnions #Lending #CreditReporting