Hidden Figures: Identifying High Net Worth Prospects of Color Through Non-Bias Screening Techniques

Despite increasing conversations about diversity, equity, and inclusion in philanthropy, many traditional wealth identification methods continue to overlook high-net-worth individuals of color. Bias in artificial intelligence (AI), limitations in publicly available wealth data, and inequities in financial reporting create blind spots that reinforce systemic barriers to inclusive philanthropy. These challenges are particularly evident in healthcare and higher education fundraising, where AI-driven screenings often fail to account for non-traditional indicators of wealth and giving capacity. This session will explore how data modeling, alternative screening techniques, and culturally competent prospecting strategies can be used to uncover high-net-worth prospects of color. Attendees will learn how to critically evaluate wealth screening tools for bias, navigate gaps in data, and implement equity-focused methodologies that surface overlooked major and principal gift prospects. Through real-world case studies, practical frameworks, and an actionable roadmap, this session will provide fundraisers and data professionals with strategies to conduct non-biased wealth screenings and cultivate more inclusive donor engagement efforts.