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Practitioner perspectives on what works in preventing fraud against older adults

Mark Button ; Vasileios Karagiannopoulos ; David Shepherd ; Annie Kirby ; Julak Lee ; Joon Bae Suh ; Jeyong Jung ; Chol Soo Koh (2026) — Journal of Economic Criminology

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DOI: 10.1016/j.jeconc.2026.100213 (opens in a new tab)

Type:   Journal Article
Country:   Global
Tags:   Bank Staff, Banking Fraud, Banking Security, Crime Policy, Digital Defences, Education, Expert Perceptions, Experts Perceptions, Older Adults, Prevention, Public Policy, Public Private Partnerships, Technology Tools, Third Party Intervention, Third Party Interventions
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Synopsis

            
The study combines a literature review, 17 interviews with professionals in policing, government, NGOs, and prevention firms, and a survey of 334 practitioners. Findings are organized into a four-part taxonomy of prevention-digital technology, education, third-party control, and partnerships-and rated by experts on a 1-5 effectiveness scale, collapsed into effective vs ineffective/neutral. About 90% of respondents considered local and national fraud-prevention partnerships important, but about two-thirds were unaware of such partnerships.

          

        
                  

            
Identified Gaps

            
Explicit gaps identified include a lack of high‑quality evidence on what works to prevent fraud against older adults; existing guidance relies on expert perceptions rather than causal evaluation. The study notes limited generalisability due to a predominantly UK-based, non‑random sample. There is insufficient robust field testing across scam types, populations, and settings, and little evidence on long‑term effectiveness of prevention tools. The authors call for targeted funding and rigorous testing to determine causal impacts, broader cross‑national testing, and better alignment of evaluation methods with real‑world prevention outcomes.

          

        
                  

            
Methods

            
The study combines a literature review, 17 interviews with professionals in policing, government, NGOs, and prevention firms, and a survey of 334 practitioners. Findings are organized into a four‑part taxonomy of prevention—digital technology, education, third‑party control, and partnerships—and rated by experts on a 1–5 effectiveness scale, collapsed into effective vs ineffective/neutral. Analysis compares UK and overseas responses and highlights top‑rated methods such as bank staff interventions, targeted age‑specific alerts, and tailored educational approaches, with ethical approval obtained and data collection conducted 2022–2024.

          

        
                  

            
Limitations

            
Limitations include limited generalisability due to a non‑random, primarily UK‑based expert sample; reliance on expert perceptions rather than causal, real‑world evaluation; potential response biases and unequal representation across regions and agency types; cross‑sectional design and potential shifts in scam landscapes; taxonomy constraints that may overlook certain prevention modalities; and potential ethical/perspective biases in respondents' views. These factors mean findings should guide rather than dictate policy, and underscore need for more rigorous, diverse testing.

          

        
                  

            
Future Work

            
Future research should secure funding for robust evaluations of fraud prevention for older adults, prioritising high-quality methodologies (e.g., field tests, quasi-experimental designs, or randomised trials) and testing interventions across diverse jurisdictions and scam types. The agenda should standardise outcome measures, compare digital technologies with targeted education, and assess the scalability and ethics of third‑party controls and partnerships. Researchers should collaborate with banks, health and social care providers, and local authorities to build longitudinal evidence on effectiveness and cost‑benefit to inform policy and practice.

          

              

    
    

        
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