artificial intelligence

After discussing the current state of the regulators’ knowledge about artificial intelligence and machine learning (ML) in underwriting models, we examine the regulators’ key areas of focus for ML models (explainability/accuracy in adverse action notices, potential hidden bias, testing for disparate impact), discuss how to test for and counteract disparate impact and how to search

In what could be an important step towards needed regulatory updating to accommodate the growing use of artificial intelligence (AI) by financial institutions, the CFPB, FDIC, OCC, Federal Reserve Board, and NCUA issued a request for information (RFI) regarding financial institutions’ use of AI, including machine learning (ML).  Comments on the RFI must be received

The CFPB recently published a blog post titled, “Innovation spotlight: Providing adverse action notices when using AI/ML models.”

The blog post primarily recycles information from the Bureau’s annual fair lending report issued in May 2020.  The Bureau indicates that artificial intelligence (AI) and a subset of AI, machine learning (ML), is an area

Andrew Smith, Director of the FTC Bureau of Consumer Protection, has written a blog post, “Using Artificial Intelligence and Algorithms,” in which the FTC “offer[s] important lessons about how companies can manage the consumer protection risks of AI and algorithms.”

The blog post makes the following key points:

  • Transparency.  Companies that use AI tools,

On February 12, 2020, the House Financial Services Task Force on Artificial Intelligence will hold a hearing titled, “Equitable Algorithms: Examining Ways to Reduce AI Bias in Financial Services.”

The Committee Memorandum flags a number of issues that could be the focus of comments and questions from lawmakers.  Those issues include the potential

In this podcast, we are joined by Scott Ferris, CEO of Attunely, a provider of machine learning (ML) and artificial intelligence (AI) technology to the debt collection industry.  We look at how changes in consumer behavior have impacted collections, technology’s role in collections, state law’s/GDPR’s impact on ML/AI and compliance strategies, how ML/AI can improve

Tomorrow, October 18, the House Financial Services Committee’s Task Force on Artificial Intelligence is scheduled to hold a hearing entitled “AI and the Evolution of Cloud Computing: Evaluating How Financial Data is Stored, Protected, and Maintained by Cloud Providers.” There will be a live webcast of the hearing.

The Committee Memorandum and related legislation can

In this podcast, we look at the opportunities for lenders to provide access to credit to “credit invisible” consumers through the use of AI underwriting tools.  We discuss these consumers’ characteristics, how AI can increase approval rates but not credit risk, risks of alternative data, the need for explainability of AI, and real world results

The House Financial Services Task Force on Artificial Intelligence will hold a hearing entitled, “The Future of Identity in Financial Services: Threats, Challenges, and Opportunities,” at 9:30 a.m. on Thursday, September 12, 2019, in room 2128 of the Rayburn House Office Building.

The memo to the FSC Majority Staff indicates the hearing will focus on

A new CFPB blog post titled “An update on credit access and the Bureau’s first No-Action Letter” provides a boost to lenders using alternative data and machine learning in their underwriting models.

The Bureau issued its first (and so far only) no-action letter in September 2017 to Upstart Network Inc. stating that the