Fraud
Analytics

Fraud is an escalating threat for banks. Technological advancements and changing customer preferences have opened up new avenues of banking for modern consumers. But these channels of convenience have also attracted massive threat from fraudsters. With criminals and fraudsters continuously coming up with new ways to dupe financial institutions, financial firms now face ever increasing challenges of detecting criminal activities and fraudsters to protect themselves and their customers. Fraud is primarily categories into 3 groups:

• Identity (third-party fraud) – stolen identity, victim etc.
• First-party fraud (i.e. never pay, first payment default) – true identity fraud, no intent to pay etc.
• Credit risk – erratic payments, attempts to pay etc.

Financial Institutions are exposed to Fraud at different stages of customer life cycle. We provide analytical solutions to our clients to predict these frauds.

• Origination - Identity Fraud, Application Fraud, Sleeper or Bust Out Fraud
• Customer Management – Money Laundering, Transaction Fraud & Account Takeover Fraud
• Collections – Non-collectable Debt Fraud, Repayment Avoidance Fraud

Our experts help the clients in detecting fraud and criminal activities by providing analytics such as:

• Customer Profiling
• Predictive Analysis
• Behavioural Analysis
• Network Analysis

We use Big Data analytics extensively to help our clients for real time scenario generation and real-time analysis for identifying potentially fraudulent transactions or criminal activities. Big data based services are contingent on the system capabilities of the clients. We support our clients to embed big data analytics IT capabilities for managing fraud.