==== Front Innov Aging Innov Aging innovateage Innovation in Aging 2399-5300 Oxford University Press US 10.1093/geroni/igaa057.2459 igaa057.2459 Abstracts Session 6165 (Symposium) AcademicSubjects/SOC02600 Injury of African American Women by Financial Exploitation Jackson Kimethria 1 Smith Patsy 1 Wilson Janet 2 1 University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States 2 University of Oklahoma Health Sciences Center, Reynolds Center for Geriatric Nursing Excellence, Oklahoma City, Oklahoma, United States 2020 16 12 2020 16 12 2020 4 Suppl 1 Program Abstracts from The GSA 2020 Annual Scientific Meeting “Turning 75: Why Age Matters”700 701 © The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America.2020This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.Abstract Financial exploitation (FE) is one of the most common forms of older adult mistreatments. The World Bank defines FE as financial violence and the World Health Organization describes FE as financial or material abuse. Both international organizations recognize that FE causes deprivation/neglect leading to physical and emotional injury to victims. Older African Americans (OAA) are disproportionately affected by FE, impacting their health and welfare. A qualitative phenomenological study explored the lived experiences of FE among OAA. A Community Based Participatory Research approach was used to partner with a predominately African American-faith based community. Participant recruitment (n=12) was through community sponsored seminars that included verbal presentations, group discussions; individual surveys, Older Adult Financial Exploitation Measure (OAFEM). OAFEM data was analyzed to identify risks. Analysis of the interviews included Open and Axial coding, and data categorization. Using NVivo, Stevick-Colaizzi-Keen analysis as modified by Moustakas, five themes emerged.