Fraud Analyst

23 hours ago

Gurgaon, Haryana, India Ocrolus Inc. Full time ₹ 9,00,000 - ₹ 12,00,000 per year

Summary

As a Fraud Analyst at Ocrolus, you will play a pivotal role in strengthening our Detect product by reviewing machine-generated fraud signals, identifying gaps in detection logic, and recommending improvements grounded in real-world fraud behaviors. Collaborating closely with product, engineering, and ML/data science teams, you will help ensure our fraud detection models are accurate, scalable, and trustworthy for financial services clients. We are seeking a sharp, investigative professional with 3–5 years of document-centric fraud risk experience ideally within fintech, lending, or banking where detecting synthetic identities and reviewing financial documents such as paystubs, bank statements, and W-2s are central to risk workflows.

Key Responsibilities
  • Review machine-generated fraud signals to evaluate accuracy, false positives, and missed detections.
  • Design and test detection rules and thresholds for identifying document-based fraud (e.g., tampering, synthetic documents, inconsistencies).
  • Validate performance of fraud detection models against known fraud patterns and client-flagged cases.
  • Provide domain-specific feedback on fraud trends across bank statements, paystubs, tax documents, and IDs.
  • Annotate and classify documents to improve supervised training datasets.
  • Collaborate with Product and Engineering teams to refine scoring logic, severity classification, and signal design.
  • Contribute to ongoing model retraining cycles, testing initiatives, and data quality initiatives.
  • Analyze edge cases and ambiguous documents to refine fraud detection boundaries and reduce gray zones.
  • Research emerging fraud techniques and document forgery trends (including AI-generated fakes) to inform system enhancements.
  • Maintain a fraud knowledge base, including signal definitions, fraud playbooks, and annotation guidelines.
  • Support customer success and operations teams by investigating escalated fraud cases and explaining system decisions.
  • Assist in evaluating third-party fraud signal vendors and benchmarking their performance against internal systems.

Preferred Qualifications
  • 3–5 years of experience in fraud or risk analysis, preferably in a fintech, banking, or credit/lending environment ideally spanning
  • Exposure to Intelligent Document Processing (IDP) flows that involve tamper detection or metadata scrutiny.
  • Experience in working with AI/ML-driven fraud tooling, anomaly detection, and risk scoring systems across the financial ecosystem.
  • Synthetic identity fraud, document forgery detection, and KYC/AML procedures.
  • Strong understanding of financial documents such as W-2s, 1040s, paystubs, bank statements, and identity forms.
  • Familiarity with fraud typologies (document forgery, synthetic identity, income misrepresentation, etc.)
  • Experience using fraud detection tools, case management systems, or decision engines.
  • Ability to interpret model outputs, scoring systems, and signal-based decisioning frameworks.
  • Detail-oriented with strong analytical, written, and communication skills.
  • Bonus: Experience working with OCR, metadata forensics, or document verification tools.
Why Join Us?
  • Join a fast-growing AI-focused fraud team tackling real-world financial crime
  • Opportunity to shape the future of document fraud detection
  • Cross-functional exposure to Product, Engineering, ML and Data Scienceke a measurable impact on fraud prevention and trust in financial systems

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