Learn how lending leaders are using ethical and explainable AI.


In recent years, financial institutions and other businesses have increased their usage of automated decisions for consumer lending and other applications. While many would like to deploy artificial intelligence (AI) and machine learning more widely, a lack of understanding when it comes to AI’s explainability remains a barrier to adoption. That makes it challenging to comply with laws such as the Equal Credit Opportunity Act (ECOA) – which requires that individual decisions be both transparent and equitable, and that consumers receive clear explanations when lenders take adverse action.

With decades of experience in automating the detection of fraud and the prediction of credit risk, our Experian experts will discuss best practices in building interpretable models. They will share new techniques that keep decisions transparent and fair even with the most modern machine learning algorithms.

Discover how ethical and explainable AI can help organizations of all sizes and levels of sophistication:

  • Make data-driven decisions more responsibly and fairly
  • Reduce bias and improve the customer experience while controlling risk
  • Improve compliance with lending regulations (including GLBA, FCRA, and ECOA) while deploying scores based on machine learning

Speakers

Jim Bander
Jim Bander
Analytics and
Optimization Market Lead
Experian

Jim Bander, PhD joined Experian in April 2018 and is responsible for solutions and value propositions applying analytics for financial institutions and other Experian business-to-business clients throughout North America. Jim has over 20 years of analytics, software, engineering and risk management experience across a variety of industries and disciplines. He has applied decision science to many industries including banking, transportation and the public sector. He is a consultant and frequent speaker on topics ranging from artificial intelligence and machine learning to debt management and recession readiness. Prior to joining Experian, he led the Decision Sciences team in the Risk Management department at Toyota Financial Services.

Brian Duke
Brian Duke
Senior Director of
Fraud Analytics
Experian

Brian Duke is responsible for building and developing analytical solutions for clients in the areas of first- and third-party fraud, synthetic ID, and bust-out. He leads a team of data scientists and analysts devoted to detecting and preventing fraud. Prior to working for Experian, Brian was a data scientist and team leader at Accenture, Bridgepoint Education, SAS Institute, Fair Isaac and Capital One. Throughout his career, he has developed state-of-the-art solutions to detect fraud and credit risk across various industries.

Mark Soffietti
Mark Soffietti
Analytics Consulting
Senior Manager
Experian

Mark Soffietti has over 15 years of experience in the industry transforming data into actionable knowledge for effective decision management. Through a wide range of large engagements, he has participated in all departments of financial institutions. Mark’s experience includes developing solutions for consumer and commercial lending across the credit spectrum – from marketing to collections. His background spans multiple industry sectors including energy, banking, automotive, not-for-profit research and retail.

Discover how ethical and explainable AI can help you.

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