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Hero FinCorp

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www.herofincorp.com

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