The Use of Artificial Intelligence and Alternative Data in Financial Services: Force for Inclusion?

Just Economy Conference – May 7, 2021


Artificial intelligence and machine learning (AI) have the capability to disrupt many aspects of retail banking. Using models that can see patterns and make conclusions from thousands of points of data, these tools can improve the predictive power of underwriting systems. However, many of the potential benefits of AI remain untested. Does AI support financial inclusion without perpetuating the same divisive and discriminatory practices that have occurred in the past? How should regulation be updated to make sure that these models are based on accurate records, make sensible decisions, and treat everyone fairly? Join this panel to hear an expansive conversation between a fair lending attorney, the head of a research organization studying the explainability and fairness of ML algorithms in credit underwriting, and the CEO of a consulting firm that provides AI-driven services to lenders.

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Redlining and Neighborhood Health

Before the pandemic devastated minority communities, banks and government officials starved them of capital.

Lower-income and minority neighborhoods that were intentionally cut off from lending and investment decades ago today suffer not only from reduced wealth and greater poverty, but from lower life expectancy and higher prevalence of chronic diseases that are risk factors for poor outcomes from COVID-19, a new study shows.

The new study, from the National Community Reinvestment Coalition (NCRC) with researchers from the University of Wisconsin–Milwaukee Joseph J. Zilber School of Public Health and the University of Richmond’s Digital Scholarship Lab, compared 1930’s maps of government-sanctioned lending discrimination zones with current census and public health data.

Table of Content

  • Executive Summary
  • Introduction
  • Redlining, the HOLC Maps and Segregation
  • Segregation, Public Health and COVID-19
  • Methods
  • Results
  • Discussion
  • Conclusion and Policy Recommendations
  • Citations
  • Appendix

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