Aman Saxena

Merchant Risk Scoring Revamp: Led a project to revamp the merchant risk scoring model, improving predictive accuracy by 20% and reducing false positives by 30%. Early Detection System: Implemented an early warning system that flagged suspicious merchant behavior, reducing financial losses from chargeback by 40% Quarter to Quarter. Risk Dashboard Implementation: Built an executive dashboard that visualized merchant risk exposure and key performance indicators across the portfolio. Segment Risk Optimization: Conducted a segmentation analysis of merchant verticals, leading to customized risk policies and better portfolio diversification. Compliance: Ensured adherence to regulatory guidelines, risk appetite frameworks, and internal controls.

Real-time Transaction Monitoring System: Implemented a Real-time Transaction Monitoring System leveraging comprehensive analysis of account behavior, profiles, and transactional data. Achieved a notable 35% reduction in unauthorized transactions through proactive identification and mitigation strategies. Advanced Fraud Prevention: Engineered a proactive system utilizing advanced data analysis techniques to scrutinize account behavior, transactions, and profiles. This initiative led to a significant 25% decrease in law enforcement complaints, demonstrating the effectiveness of leveraging data-driven approaches for improved outcomes. Customer Segmentation: Implemented Risk Rating and Enhanced Risk Rating analysis on customer profiles, systematically identifying and mitigating fraudulent activities to bolster security measures. Achieved operational cost savings of approximately 1.2 million INR through the implementation of efficient automations. Dynamic Risk: Engineered a cutting-edge Risk Categorization scoring model by integrating demographics, device data, and transaction behavior. Employed iterative optimization techniques like ad-hoc analysis and hypothesis testing to refine its efficacy continuously. This approach yielded a notable reduction in the fraud to sales ratio to an unprecedented low of 0.5 basis points. Dashboarding And Alerting Mechanism: Implemented 15+ dashboards to streamline MIS review, covering flows like UPI, bank transfers, AEPS, onboarding, and wallet transactions. Dashboards track trends including FTS and rejection rates from risk strategies. Integrated alerting mechanisms for operations team review of problematic actors. Automation: Implemented automation for regulatory reporting by integrating system APIs, resulting in a reduction of manual resources and annual operational cost savings of $2 million. Designed the system to generate alerts and flag suspicious accounts using diverse data models

Enhanced Reselling Monitoring Framework: Revamped Reselling Monitoring Framework leveraging advanced data analysis techniques, resulting in a 20% decrease in fraudulent orders and lowering the fraud to sales ratio to an impressive 0.8 bps. Cashback Abuse Detection System: Implemented a Cashback Abuse Detection System incorporating advanced data analysis methodologies, particularly utilizing clustering techniques. This initiative led to monthly savings of 2.5 million by effectively preventing policy exploitation. Strategic Merchant Profiling: Utilized comprehensive data analysis techniques to conduct merchant profiling, examining various parameters such as profiles and transaction behavior to glean insights on credibility and identify potential risks. Effectively eliminated malicious entities from the system, resulting in operational cost savings of approximately 1.6 million through automation. Merchant Credit Limit Framework:- Developed a sophisticated credit limit system for allocating Paytm Postpaid services to our merchants, leveraging data analysis techniques to consider multiple factors including transaction history, profiles, demographics, and central bureau data.

Generated and analyzed reports from large datasets, providing actionable insights for decision-making Developed forecasting dashboards, enhancing business insights and predictions Supported enterprise-wide, data-driven decision-making by transforming raw data into strategic initiatives.