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All About Artificial Intelligence | ICE Mortgage Technology Experience 22

Updated: Nov 8, 2023

Last month, the financial services and mortgage lending industry saw the return of ICE Mortgage Technology’s annual user conference live and in-person for the first time since 2019! ICE Experience 22 gave us an opportunity to see old friends and reconnect with peers, technology experts, and mortgage leaders from across the ecosystem.

“Our goal remains to host an impactful event that showcases digital innovation across the industry, shares out technology roadmap, offers best practices, as well as creating networking opportunities so attendees can maximize their time together,”
-- Joe Tyrrell, President, ICE Mortgage Technology.

Joe and the entire team at ICE MT did not disappoint! Over 3,000 mortgage, technology, and industry professionals descended on Las Vegas for an opportunity to gain insight into current and future trends and garner skills to maximize investments in digital mortgage solutions – be it related to cutting-edge digital trends, automation, data, borrower engagement or compliance.

Personally, I had the opportunity to be a part of a panel with Brian Stucky, Chris McEntee, and Courtenay Dunn, Moderator, to talk about artificial intelligence and how it can help lenders remove unintentional bias.

With bias in home valuation, gender-based, and race-based bias recently in the news and on the regulators’ priority list, this was a very timely topic, focusing on several key topics including:

  • What IS artificial intelligence (and what isn’t)?

  • Disparate impact, and fair lending practices.

  • Ethical and/or responsible artificial intelligence.

  • Artificial intelligence “black box”.

  • “Algorithm bias” and how does that occur.

  • Data, machine learning and the impact on underwriting decision.

  • Current artificial intelligence trends in the mortgage industry.

  • Governance and recent regulatory developments.

  • Methodologies that lenders and fintechs can implement now to remediate unintentional bias and reduce consumer harm.

  • Best practices to educate, evaluate, and scale the optimal artificial intelligence solutions for each organization.

  • Real-world examples and future trends in artificial intelligence.

According to a recent Harvard Business Review article, artificial intelligence should be seen to support three important business needs: automating business processes, gaining insights through data analysis, and engaging with customers and employees. It truly is imperative for companies to look at artificial intelligence through the lens of business capabilities rather than technologies. Furthermore, the selection and adoption of artificial intelligence initiatives must be a deliberate, incremental, and iterative process. Companies must understand how an artificial intelligence system will interact with its ecosystem; and while the risks of artificial intelligence are very real, the appropriate benchmark is not perfection but finding the best available alternative to solve your most challenging problems.

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