FairPlay AI

Do lenders have to trade accuracy for fairness? "'This is the thorniest, most difficult question in algorithmic fairness right now,' said Kareem Saleh, founder and CEO of FairPlay AI, a company that conducts fairness testing on AI models. 'What you see in the impasse is actually two really thoughtful groups trying to grapple with this question.'" Read the full article here in American Banker:

Last week the Consumer Financial Protection Bureau sent a spicy letter to the Treasury Secretary about AI in financial services. Here’s the scoop: First, if your business model depends on side-stepping a regulation, it’s an immediate red flag. Case in point: Earned Wage Access? Now treated as loans. Buy Now, Pay Later? Consider it a credit card. 🤖 Generative AI: The CFPB is giving it major side-eye, at least in consumer-facing applications. They're worried about misinformation, flimsy dispute resolution, and a Pandora's box of privacy and security risks. Handle with care! 🔍 Fairness First: The CFPB is cracking down on bias in everything from fraud detection to servicing, debt collection, and valuation models. They want regular testing for disparate treatment and impact. And they’re serious about searching for Less Discriminatory Alternatives (LDAs)—they mentioned it twice. 👀 ❌ RIP sandboxes and no-action letters.  No more regulatory relief for "innovative" companies.The CFPB says these programs “fell short of their intended purpose.” Apparently, waivers and approvals were misrepresented as stamps of endorsement. 🔓 Open Banking: The CFPB says competition should be based on product quality, not data lock-in. The future is open! 🛒 Comparison Shopping Tools: If you're displaying multiple offers to consumers and manipulating results, collecting kickbacks, or using dark patterns—be warned. The CFPB sees these practices as anti-competitive and potentially illegal. 📱 Big Tech Beware: If you’re a major player in digital wallets or payments—looking at you, Google, Apple, Samsung—get ready to be supervised like a bank. And whistleblowers? The CFPB wants to hear from them! In short, AI and Big Tech are squarely in the CFPB's sights. The message? Follow our rules, or face the music. https://lnkd.in/g-CMQp3D

At FairPlay, a key strength of our team lies in each individual’s wide set of experiences, from fine artists to nuclear engineers. We also strive to operate by one of our core values: doing your part to help create a society that works for everyone. This goal requires not just excellent mission-driven work but also service – to our customers, our communities, and our country. One of our team members, Adrian Lai, has embodied this value of service throughout his career. Since graduating from the Naval Academy, he has served multiple times abroad including in the Western Pacific and the Middle East. Now, Adrian once again has been called to serve his nation abroad. We honor his service and sacrifice, as well as the sacrifice of his family, while he is away.  We're proud to support team members like Adrian who answer the call to duty and reflect FairPlay’s values both at work and beyond. Good luck, Adrian. We eagerly await your safe return once your mission is complete.

Imagine: You're a public interest lawyer in rural Arkansas, the kind who spends their days battling predatory lenders, landlords and fighting for the forgotten. One day, calls start flooding in. Quadriplegics, individuals with severe cerebral palsy, and people who rely on in-home care for basic medical services all share the same chilling news: the state is cutting their lifeline – no more (or dramatically reduced) in-home medical care. When they ask why, the reply is a cold bureaucratic shrug: The computer said so. Without the benefit of in-home care, people develop painful conditions like bed sores, miss vital medical treatments, and are at higher risk of hospitalization. At a loss for what to do, you file suit against the state. Your argument? A reduction in home care without adequate explanation violates the constitutional right to due process. This isn't fiction. It's the real-life story of Kevin De Liban, a public interest attorney with Legal Aid of Arkansas who launched a David vs. Goliath battle against an unfeeling algorithm – and won. After years of litigation, in August 2023, The Arkansas Department of Human Services agreed to a historic settlement and to implement significant changes to the program, including providing explanations for algorithmic decisions that adversely affect consumers. This isn’t just a legal victory; it's a blueprint for change. Kevin is now launching Techtonic Justice, an organization that will train other public interest lawyers to fight for a future where technology empowers, not excludes. This vital initiative needs support. Kevin is raising funds to expand Techtonic Justice's reach and impact. So, hive mind, I need your help. What philanthropic organizations should Kevin turn to to support this important work and the launch of TechTonic Justice? You can read more about Kevin’s work and the lawsuits he’s filed in the links below. https://lnkd.in/gJt7JuaV https://lnkd.in/gzSZrn2u https://lnkd.in/gaaYtqEf

The news is out! FairPlay AI is partnering with LendingPoint™ to incorporate FairPlay’s Fairness-as-a-Service Solutions, thus enhancing LendingPoint's algorithmic qualification and automated funding decisions and furthering its mission of providing one-stop financing solutions for consumers and lending institutions. “LendingPoint takes a modern approach to credit by considering a broader range of factors to assess creditworthiness, focusing on an applicant’s complete financial picture,” said Shawn Stone, LendingPoint’s Chief Executive Officer. “We are excited to utilize FairPlay’s Fairness-as-as-Service solutions to help ensure our models continue to provide financing options fairly.” Read the full details here:

Today, we are excited to welcome LendingPoint™ to the FairPlay family. As a leader in point-of-sale and personal lending, LendingPoint has originated billions in loans and served hundreds of thousands of customers across the U.S. They will join the ranks of other premier names in FinTech that rely on FairPlay’s Fairness-as-a-Service solutions to automate their fairness testing and optimization. We look forward to working with Shawn Stone, Mark Lorimer, Greg McLaughlin, Amanda Flashner, Karen Louis, Don Abraham, and Arun Kumar to support LendingPoint’s continued success and next phase of growth.

I recently joined Vikas Raj of ResilienceVC on the PNYX podcast to debate hot topics in AI.  Three issues and themes we discussed: AI's Clear and Present Dangers: We explored the surge in AI-driven misinformation, deepfakes, and surveillance, as well as persistent bias affecting marginalized communities. AI as the Great Equalizer: We envisioned a world where AI dramatically reduces the cost of expertise. Imagine a Stanford education or personalized healthcare costing pennies, or having AI tutors, financial advisors, and mental health support at your fingertips for minimal cost. The Regulatory Tightrope: We debated the delicate balance between fostering AI innovation and preventing AI misuse. I shared insights from a recent conversation with Senator Chuck Schumer, who admitted that crafting effective AI regulation is one of the most challenging issues he's faced. Intrigued? Tune into the full episode for a deeper dive into how AI could reshape our society, economy, and daily lives. Link here: https://lnkd.in/gqCHEFqd

Banks and Fintechs: Federal financial regulators recently released a joint statement and RFI on bank arrangements with third parties, raising questions about the fairness of such arrangements for deposit products and payment services. This increased scrutiny comes at a time when the likelihood of algorithmic bias in deposit and payments products grows as financial institutions increasingly rely on third party technologies to offer and automate their deposit and payments-related processes. Disparate impact in deposit and payment products is likely to be regarded by regulators as a UDAAP violation—an unfair and/or deceptive practice—even for non-lending financial products. To guard against this, FairPlay performs fairness testing of: ➡ Account denial processes ➡ Fund availability policies (holds on deposits and disbursements) ➡ Fee waiver practices ➡ Exception handling ➡ Transfer limitation criteria (e.g., Zelle and ACH limits) ➡ Dispute resolution procedures ➡ Identity verification and Customer Identification Programs (CIP) ➡ Fraud detection systems Why is this important now? The joint statement and RFI from the regulators signals a new era of scrutiny for third-party arrangements in banking, including fair treatment of consumers across all banking activities. Want to ensure the fairness of your deposit and payment products? FairPlay is here to help! https://lnkd.in/gEdYJ24E

Gallagher Re, one of the world’s largest global reinsurers, has released a report this morning on the growing role of AI in the insurance industry, particularly in risk selection, pricing, underwriting, and portfolio management. The report features several case studies and profiles of InsurTech companies, including – you guessed it – FairPlay! The report provides optimistic growth projections for the InsurTech sector, driven by continued AI innovation and increasing adoption of digital solutions. It also offers strategic recommendations for insurers adopting AI, emphasizing transparency, fairness, and privacy in AI systems. FairPlay helps some of America’s biggest brands explain, de-bias, stress-test, and monitor AI-powered risk models. It's an exciting time for InsurTech, and we're thrilled to be at the forefront of this innovation! Thank you Andrew Johnston for recognizing our work. Are you ready to harness the power of AI responsibly? Check out the Gallagher Re report and let’s connect!

Who would have thought that a British cricket enthusiast would revolutionize fair lending? Meet Lloyd Shapley, an unlikely hero of fairness analytics in the AI era. His inspiration? A love for cricket and a keen interest in how to fairly attribute points in multi-player games. His question: In a team sport, how do you fairly attribute credit (or blame) to individual players? This cricket conundrum led Shapley to develop what we now call "Shapley values" — a concept that would revolutionize game theory and, decades later, transform fair lending analytics. Shapley’s curiosity led him to create a method that disaggregates each player's contribution to a team’s overall success by considering every possible combination of players. Fair lending compliance officers face a similar challenge: figuring out how different variables contribute to a loan being approved or denied. While many fair lending pros still rely on regression analysis to grapple with this problem, the cutting-edge approach now embraces Shapley's cricket-inspired innovation. Let's break it down: Regression analysis aims to quantify how changes in independent variables (like income, credit score, race) affect a dependent variable (like loan approval), helping isolate factors contributing to disparities. Shapley Values aim essentially to do the same thing, but work differently. Imagine if we treated each factor in a lending decision like a player in Shapley's beloved cricket match. (Or, let’s be real — few of us understand cricket so let’s use basketball). Shapley values consider all possible "lineups" of players (variables), determining each one's contribution to the final "score" (the lending decision). Key advantages of Shapley values: Handling complexity: They capture non-linear and interaction effects that regression might miss, much like how a basketball’s player's performance might depend on who else is on the court. Accuracy in attribution: Just as Shapley ensured every cricket player got due credit, Shapley values consider all possible combinations of variables, enabling a more accurate understanding of the impact of each variable. Model-agnostic: Shapley values work with any model, from simple linear equations to complex machine learning algorithms - it's like being able to analyze any sport, not just cricket! Interpretability: Shapley values offer clearer insights into how each factor contributes to the final decision, making it easier to explain to stakeholders. The shift to Shapley values in fair lending is supported by recent research, including studies by FinRegLab and the public monitorship of Upstart Inc. These studies show that Shapley's cricket-inspired idea provides more accurate and nuanced insights into complex decisioning systems. Are your fair lending analytics stuck in a pre-Shapley world? FairPlay can help you score big at fair lending compliance – just don't ask us to explain cricket!