fraud management in banking and financial services
Read More Fraud management in the finance industry: The threat landscape
Fraud is one of the biggest threats faced by many financial services organisations. According to estimates, losses caused by fraudulent financial transactions is growing at more than 25% year on year. One of the major reasons is an increase in the adoption of digital channels, which has led to rise in fraud losses. Compromised credentials, leakage, and theft of personal information through social engineering, such as fake emails and calls, have further accelerated it. Fraud management in banking combines analytics, detection, and prevention into one continuous cycle: assessing losses, alerting on suspicious transactions, and investigating cases before losses compound.
Fraud types we help banks and financial institutions fight
Our bank fraud management coverage spans the threats accelerating across digital channels:
- Account takeover through compromised credentials
- Phishing and social engineering, including fake emails and calls
- Payment and transaction fraud across digital channels
- Identity theft and leakage of personal information
- New and unknown fraud patterns identified across transaction footprints
Our fraud prevention solutions in finance industry
Our fraud analytics in banking span the full cycle, from loss assessment to case investigation:
Fraud loss assessment
Estimate and forecast the fraud losses for better planning
Fraud alerting models
Develop adaptive models to identify suspicious transactions
Precision and recall improvement
Identify new rules and simulates fraudulent scenarios
Entity/Linked identification
Manage the relationship between entities and accounts across boundaries
Unknown pattern identification
Identify patterns across transaction footprints to generate insights into new fraud patterns
Data platform integration
Integrate data from disparate systems to develop and integrate new features
Case visualization
Develop intuitive dashboards to enhance the efficiency and effectiveness of case investigation
Fraud detection and prevention in banking: From alerts to action
Fraud detection in banking works when alerts convert into confirmed cases efficiently. Our adaptive alerting models, precision and recall improvement, and case visualization dashboards reduce false positives and improve the alert-to-fraud ratio, so investigation teams focus on genuine threats instead of noise.
Why Infosys BPM - fraud prevention and risk management solutions for finance and banking industry?
We bring in deep domain, data science, data, and visualisation skills to develop and deploy analytics solutions tailored to drive business outcomes. Through our Fraud Detection and Prevention solutions for Finance And Banking Industry, we help reduce fraud losses, decrease false positives and improve alert-to-fraud ratio.
Fraud management BPO and managed services
As a fraud management BPO partner, Infosys BPM combines domain, data science, data, and visualisation skills into managed services for banks and financial institutions. Analytics solutions are developed, deployed, and run as one accountable service, targeting lower fraud losses, fewer false positives, and a better alert-to-fraud ratio.
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Case Study
Challenges and solutions - fraud management in banking
Because the threats outpace static defenses: losses from fraudulent financial transactions are growing at more than 25% year on year, driven by digital channel adoption, compromised credentials, and social engineering. Fraud management in banking counters this as a continuous cycle: assessing losses, adapting alerting models, and investigating cases before losses compound.
Through data platform integration: a fraud management system in banking connects data from disparate systems, applies alerting models and rules to transactions, and routes suspicious activity to investigators through intuitive case dashboards. Infosys BPM builds and runs these capabilities as an analytics-led service.
Precision and recall improvement identifies new rules and simulates fraudulent scenarios, while adaptive alerting models learn to separate suspicious transactions from normal behavior. Together they decrease false positives and improve the alert-to-fraud ratio.
Investigations slow down when analysts chase relationships manually across accounts and entities. Entity and linked identification maps those relationships across boundaries, and intuitive case visualization dashboards enhance the efficiency and effectiveness of case investigation.
Yes. Fraud management BPO combines fraud analytics, operations, and reporting into one managed service, bringing domain, data science, and visualisation skills without building an in-house analytics team.
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