How an NBFC Reduced Fraud Losses with Predictive Analytics

Client Background

The client is a fast-growing NBFC offering retail, consumer, and SME loans across multiple regions, serving a diverse customer base through digital channels, branches, and partners. With rising loan volumes and rapid onboarding, the company relied on data from loan systems, transactions, credit bureaus, and third-party tools to manage risk. However, increasing digital adoption brought complex challenges, and despite having vast data, the NBFC lacked advanced analytics to proactively detect and prevent financial losses.

 

Challenges

 NBFC faced several fraud and risk management challenges:

Rising Fraud Losses:
 An increase in identity fraud, application fraud, and transaction anomalies led to financial losses and operational strain.

Rule-Based Detection Limitations:
 Existing fraud controls were heavily rule-driven, resulting in high false positives and delayed identification of sophisticated fraud patterns.

Fragmented Risk Data:
 Fraud-related data was spread across loan systems, transaction platforms, and external data sources, limiting holistic risk assessment.

Delayed Fraud Detection:
 Fraud incidents were often detected after disbursement or transaction completion, increasing recovery

Limited Visibility for Risk Teams:
 Risk and compliance teams lacked real-time dashboards to monitor emerging fraud trends and high-risk segments. challenges.

Solutions

Wisecor Transformations delivered Predictive Analytics and Fraud Intelligence solutions to strengthen fraud detection and reduce losses.

Data Discovery & Risk Assessment:
 Conducted a comprehensive assessment of fraud scenarios, data sources, customer journeys, and existing risk controls.

Unified Fraud Data Model:
 Designed a centralized data framework integrating loan application data, transaction histories, device intelligence, customer behavior, and third-party risk indicators.

Predictive Fraud Analytics Models:
 Developed machine learning models to identify suspicious patterns, predict fraud probability, and flag high-risk applications and transactions in real time.

Fraud Monitoring Dashboards:
 Built role-based dashboards for risk, compliance, and leadership teams to track fraud trends, loss exposure, and intervention effectiveness.

Automated Alerts & Workflows:
 Implemented automated alerts and scoring mechanisms to enable faster investigations and timely preventive actions.

Results

Results / Impact

Through Wisecor’s Predictive Analytics and Fraud Intelligence solutions, the client achieved:

Significant Reduction in Fraud Losses: Early identification of high-risk cases helped prevent fraud before disbursement and transaction completion.
Improved Detection Accuracy: Machine learning models reduced false positives, allowing teams to focus on genuine fraud risks.
Real-Time Risk Visibility: Risk teams gained continuous visibility into fraud patterns, emerging threats, and portfolio risk exposure.
Faster Decision-Making: Automated scoring and alerts enabled quicker approvals, rejections, and investigations without impacting customer experience.

Technology Stack
Consulted & Recommended

Cloud Data Warehouse
Machine Learning & Predictive Analytics Models
Fraud Risk Scoring Engine

Client Testimonial

“Wisecor Transformations helped us move from reactive fraud handling to proactive risk prevention. Their predictive analytics capabilities significantly reduced losses while improving our overall risk management effectiveness.”
— Risk & Compliance Leadership Team
NBFC

Wisecor Transformations empowers financial institutions to mitigate risk, prevent fraud, and scale confidently through data-driven intelligence.

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