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NCJ Number: 251227 Find in a Library
Title: Computers Learn To Detect Financial Abuse of the Elderly
Corporate Author: National Institute of Justice (NIJ)
US Department of Justice
Office of Justice Programs
United States of America
Date Published: October 2017
Page Count: 2
Sponsoring Agency: National Institute of Justice (NIJ)
Washington, DC 20531
Sale Source: National Institute of Justice (NIJ)
US Department of Justice
Office of Justice Programs
810 Seventh Street NW
Washington, DC 20531
United States of America
Document: HTML
Type: Program/Project Description; Research (Applied/Empirical)
Format: Document; Document (Online)
Language: English
Country: United States of America
Annotation: This paper presents a summary description of NIJ-funded research that determined whether data from cases of suspected elder abuse can be supplied to a computer program that can determine whether financial abuse of the elderly person has occurred (“pure“ financial abuse), as well as whether financial abuse may have been accompanied by physical abuse (“hybrid” financial abuse).
Abstract: The research team used a statewide dataset of 8,800 confirmed cases of elder abuse in Texas that had been investigated by adult protective services agencies. The data were randomly split 80/20. The larger dataset was used to program the computer to detect patterns for financial exploitation and also differentiate between “pure” financial exploitation and “hybrid“ financial exploitation. The smaller dataset was used to test the computer models on accuracy in classifying the cases of financial exploitation. The researchers determined that the computer algorithms they developed were reliable in predicting clients who had experienced financial exploitation compared with those who had experienced other forms of elder abuse. The main factors that distinguished the financial exploitation from other abuse types were misuses of financial assets. In distinguishing between “pure” financial exploitation and “hybrid” financial exploitation, the computer algorithms made modest improvements in prediction accuracy compared to chance. The most significant factor that distinguished between “pure” and “hybrid” financial abuse was the presence of an apparent injury, such as bruises and skin tears. The researchers anticipate the data algorithms being transformed into web-based applications.
Main Term(s): Elderly victims
Index Term(s): Computer aided investigations; Computer aided operations; Computer software; Crime detection; Elder Abuse; Financial fraud; Multiple victimization
Note: The research described in this article is based on research funded under NIJ grant 2013-IJ-CX-0050 awarded to the University of Texas Health Science Center at Houston.
To cite this abstract, use the following link:
http://www.ncjrs.gov/App/publications/abstract.aspx?ID=273407

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