Mitigating Churn After Online Financial Fraud: The Value of Blame Attribution

The financial industry is plagued with account-based fraudulent transactions in which perpetrators surreptitiously siphon away money from customer accounts. To address this recurrent problem, service operations teams at financial institutions (e.g., the fraud detection and mitigation teams) spend millions yearly identifying perpetrators, attributing blame, and averting customer churn. However, in the vast majority of cases, the service operations teams cannot trace fraudulent transactions back to the perpetrators, and hence, it remains unclear whether they should continue to expend significant resources into investigating account-based fraud and attributing blame. Employing a wide range of econometric and machine learning techniques on a rich dataset from a US bank and an experiment, we attempt to offer the first empirical assessment of the association between blame attribution, or lack of it, in response to customer-identified account-based fraud and customer churn. The results indicate that relative to the customers that did not experience fraud, those that did and received a resolution lacking blame attribution have 40.69 %Lift (95% confidence interval (CI) = [24.41 %Lift , 56.97 %Lift ]) in churn rate. However, customers that experienced fraud and received a resolution involving blame attribution have −62.45 %Lift (95% CI = [−31.22 %Lift , −93.68 %Lift ]) in churn rate, making them less likely to churn than those that did not experience fraud. The latter result offers one of the first field evidence of the well-known service recovery paradox. Additionally, we observe significant heterogeneity in the findings based on customer tenure and the number of customer-firm interactions and document the long-term effects of attributing and not attributing blame. These insights can assist service operations teams in their postservice failure efforts to mend customer-firm relationships. Overall, the results underscore the importance of blame attribution during service recovery for service operations teams and inform a topical debate on a banking reform proposed by the US Department of Treasury.

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Publication Details

Journal
Production and Operations Management
Published
2025-03-24
DOI
https://doi.org/10.1177/10591478251331125
Citations
3
Primary Topic
Imbalanced Data Classification Techniques
Type
article
Field-Weighted Citation Impact
7.44
Controls
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article

Mitigating Churn After Online Financial Fraud: The Value of Blame Attribution

Sriram Somanchi, Vamsi K. Kanuri, Rahul Telang
3 citations
Production and Operations Management
Imbalanced Data Classification Techniques
7.44
article

Mitigating Churn After Online Financial Fraud: The Value of Blame Attribution

Sriram Somanchi, Vamsi K. Kanuri, Rahul Telang
article en
3 citations

Abstract

The financial industry is plagued with account-based fraudulent transactions in which perpetrators surreptitiously siphon away money from customer accounts. To address this recurrent problem, service operations teams at financial institutions (e.g., the fraud detection and mitigation teams) spend millions yearly identifying perpetrators, attributing blame, and averting customer churn. However, in the vast majority of cases, the service operations teams cannot trace fraudulent transactions back to the perpetrators, and hence, it remains unclear whether they should continue to expend significant resources into investigating account-based fraud and attributing blame. Employing a wide range of econometric and machine learning techniques on a rich dataset from a US bank and an experiment, we attempt to offer the first empirical assessment of the association between blame attribution, or lack of it, in response to customer-identified account-based fraud and customer churn. The results indicate that relative to the customers that did not experience fraud, those that did and received a resolution lacking blame attribution have 40.69 %Lift (95% confidence interval (CI) = [24.41 %Lift , 56.97 %Lift ]) in churn rate. However, customers that experienced fraud and received a resolution involving blame attribution have −62.45 %Lift (95% CI = [−31.22 %Lift , −93.68 %Lift ]) in churn rate, making them less likely to churn than those that did not experience fraud. The latter result offers one of the first field evidence of the well-known service recovery paradox. Additionally, we observe significant heterogeneity in the findings based on customer tenure and the number of customer-firm interactions and document the long-term effects of attributing and not attributing blame. These insights can assist service operations teams in their postservice failure efforts to mend customer-firm relationships. Overall, the results underscore the importance of blame attribution during service recovery for service operations teams and inform a topical debate on a banking reform proposed by the US Department of Treasury.

Production and Operations ManagementVol. 34(10)
University of Notre Dame (US), Carnegie Mellon University (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Imbalanced Data Classification Techniques
7.44
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