Job description
Come build at the intersection of AI and fintech. At Ocrolus, we’re on a mission to help lenders automate workflows with confidence—streamlining how financial institutions evaluate borrowers and enabling faster, more accurate lending decisions.
Our AI-powered data and analytics platform is trusted at scale, processing nearly one million credit applications every month across small business, mortgage, and consumer lending. By integrating state-of-the-art open- and closed-source AI models with our human-in-the-loop verification engine, Ocrolus captures data from financial documents with over 99% accuracy. Thanks to our advanced fraud detection and comprehensive cash flow and income analytics, our customers achieve greater efficiency in risk management, and provide expanded access to credit—ultimately creating a more inclusive financial system.
Trusted by more than 400 customers—including industry leaders like Better Mortgage, Brex, Enova, Nova Credit, PayPal, Plaid, SoFi, and Square—Ocrolus stands at the forefront of AI innovation in fintech. Join us, and help redefine how the world’s most innovative lenders do business.
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
Life at Ocrolus
We’re a team of builders, thinkers, and problem solvers who care deeply about our mission — and each other. As a fast-growing, remote-first company, we offer an environment where you can grow your skills, take ownership of your work, and make a meaningful impact.
Our culture is grounded in four core values: Empathy – Understand and serve with compassion
Curiosity – Explore new ideas and question the status quo Humility – Listen, be grounded, and remain open-minded
Ownership – Love what you do, work hard, and deliver excellence
We believe diverse perspectives drive better outcomes. That’s why we’re committed to fostering an inclusive workplace where everyone has a seat at the table, regardless of race, gender, gender identity, age, disability, national origin, or any other protected characteristic.
We look forward to building the future of lending together.
