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Salmon Group

Anti-Fraud Analyst

Posted an hour ago
2-5 years experience
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AI Summary

The Anti-Fraud Analyst will own the end-to-end fraud detection layer and provide analytical support to the underwriting function. Responsibilities include building data pipelines, developing performance dashboards, and identifying process inefficiencies through deep-dive analysis.

We’re looking for a strong, product-minded Antifraud Analyst to support our growing motorcycle lending portfolio by providing dedicated analytical and data support to the Underwriting function while owning the fraud detection layer end-to-end.

This isn’t a “run the report and hand it off” role - you’ll independently analyze how fraud and underwriting processes work, build new controls from scratch, help them scale efficiently alongside the business, and continuously ask, How can we make this better?

If you approach fraud systems the way a product manager approaches a feature, you’ll fit right in.

Your Future Responsibilities Await:

  • Develop and maintain reports and dashboards covering underwriting performance, approval rates, turnaround times, productivity, and other key KPIs.

  • Build and maintain data pipelines and analytical datasets required for underwriting monitoring and reporting.

  • Perform deep-dive analysis of underwriting processes, customer segments, approval/decline patterns, and portfolio performance.

  • Support Product and Underwriting teams with data-driven insights and ad hoc analysis.

  • Identify process bottlenecks, inefficiencies, and opportunities for automation.

  • Monitor data quality and investigate discrepancies in underwriting data and reporting.

  • Develop automated monitoring and early-warning indicators for significant changes in underwriting performance.

  • Support new product launches and process changes by defining metrics, reporting requirements, and analytical controls.

  • Work closely with Product, Risk, Data, Technology, and Operations teams on data and system improvements.

 

What we expect from candidate:

  • Strong SQL expertise - mandatory, including complex joins, CTEs, window functions, aggregations, and working with large datasets.

  • Strong analytical and problem-solving skills.

  • Experience building reports, dashboards, analytical datasets, and data pipelines.

  • Ownership mindset and proactive approach

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