There has been quite a lot in the news lately regarding the use of models, algorithms, AI, and evolving technologies in the banking industry. But there is more to it than just AI – financial institutions are increasingly using big data in their operations.
This includes information that is not traditionally considered financial in nature. It could be information from a consumer’s social media profile, web surfing habits, and more. And this information is available from an increasing number of third parties.
The benefits are obvious – more effective marketing, more efficient underwriting of credit, and just an overall sense of better knowing the customer. But there are two sides to every coin. There are significant risks to using AI and non-traditional data when dealing with customers and prospects.
The regulatory agencies (as well as Congress and the Administration) are keenly focused on these risks and are looking very carefully at what the industry is doing. We have fintechs to thank for many of these advancements, but they are not regulated the same way as traditional banks, thrifts, and credit unions, so usage of these exciting tools and strategies must be monitored carefully.
In this webinar, we’ll discuss these concerns and risks, so that you can properly monitor and establish controls for these technologies so you can best manage regulatory expectations as you succeed.
What You’ll Learn
- The use case for AI in banking: pros and cons
- Where you’re already using it right now
- New administration = new priorities and expectations: where do we stand now?
- What are examiners looking for? Where might we be sued?
- Algorithmic discrimination: what is this and how can we monitor it?
- Digital redlining: promoting your products in the digital world
- The White House’s “Blueprint for an AI Bill of Rights” – is this even valid anymore?
- The Facebook settlement: case study in digital advertising, including lessons learned
- Regulatory agency and FTC guidance on the issue: many to-do’s and recommendations
- Machine learning and related risks
- AI Framework from the National Institute of Standards and Technology
- Chatbots and customer service applications
- FHA: algorithm-based tenant screening
- Automated Valuation Model (AVM) final rule: bias in the evaluation process
- Joint statement on AI-based discrimination from CFPB, DOJ, FTC, and EEOC
- Fintech-bank partnerships
- Vendor responsibilities: model validation and more
- How can we use it to make our jobs easier?
- 2 truths and 1 lie
Who Should Attend
This interactive session is ideal for anyone in the institution involved in the marketing, management, and servicing of retail products. As these technologies are pervasive throughout the product lifecycle, most anyone, board members included, will benefit from this information.