Hero FinCorp
Rising
Hero FinCorp is a non-banking financial company specializing in commercial lending and consumer finance businesses.
- Open roles
- 33
- New role every
- ~3.5 days
- Posting trend
- 0.6× vs prior 90d
Company signals
Score: 80
Wikipedia
Yes
GitHub org
Yes
New cities (90d)
17
SEC Form D filed
never
HN mentions (90d)
0
Job facts
- Location
- Gurugram, India
- Type
- Permanent
- Department
- CRO Unit
- Posted
- Aug 18, 2026
Last verified live 1 month, 2 weeks ago · checked directly on the company's Darwinbox
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Sr. Associate - Fraud Analytics
at Hero FinCorp
Key Responsibilities:
- Analyze end-to-end lending lifecycle data (application, onboarding, bureau, repayment, device) to identify fraud patterns and high-risk segments
- Track key fraud indicators such as First Payment Default (FPD), Early Payment Default (EPD), and abnormal delinquency trends
- Perform deep-dive analyses and root-cause investigations on fraud spikes, portfolio deterioration, and channel-level risks
- Support development, testing, and optimization of fraud rules, score cut-offs, and risk triggers to balance fraud capture and customer experience
- Build and maintain analytical datasets (feature marts) by combining internal and external data sources for fraud detection and monitoring
- Collaborate with Fraud Control Unit (FCU), Risk, Credit, and Business teams to provide data-backed insights and investigation inputs
- Develop and maintain fraud monitoring reports and dashboards using tools such as SQL, Python, and Power BI
- Assist in exploring new data sources (bureau, alternate data, device, telecom, etc.) and contribute to their evaluation for fraud use cases
- Support development of machine learning models and analytical frameworks for anomaly detection, behavioural segmentation, and fraud risk prediction
- Leverage basic Generative AI tools (LLMs, prompt-based workflows) for exploratory analysis, summarisation of fraud cases, and signal identification
- Participate in POCs and pilot programs to evaluate new fraud detection techniques, models, and data capabilities
- Translate identified fraud patterns (e.g., synthetic identities, mule accounts, sourcing fraud) into actionable analytical features and rules
- Present insights, findings, and recommendations to stakeholders in a clear and structured manner
- Strong analytical experience in fraud/risk analytics for digital or retail lending portfolios.
- Ability to work with large datasets and derive actionable insights for fraud detection and risk mitigation.
Work Experience:
• 1+ years of Banking experience
• 3+ years of work experience with SQL
• 3+ years of experience in Strategy/Planning
• 3+ years of work experience with Python (Programming Language)
• 1+ years of experience in Analyst