Braviant

Fintech

SeniorFraudRiskAnalyst

Dallas, Texas, United States FULL TIME Remote Friendly
The Brief

“Senior Fraud Risk Analyst at Braviant. Skills: Fraud risk analysis, Fraud detection strategy development, Data analysis using SQL and Python. Analyze application and early performance data to identify fraud patterns, including synthetic identity, first-party fraud, and credit abuse.. Develop and implement fraud detection strategies, including rules, thresholds, and decisioning logic.”

What You'll Achieve.

Protect the business from identity fraud, first-party fraud, and credit abuse.; Directly impact early loss performance and portfolio quality.; Improve approval quality and reduce early loss.

Industry & Context.

Fintech
Problems you'll solve

Analytical skills; Distill complex problems

What They're Looking For.

Must Have

Degree in Data Science, Applied Mathematics, Statistics, Economics, Computer Science or a related field, 4–6 years of experience in fraud, risk, or analytics, preferably in fintech, lending, or financial services, analytical skills with experience using SQL, Python, Excel, or similar tools to analyze large datasets, Understanding of key fraud types, including synthetic identity and first-party fraud and familiarity with fraud tools (i. e. identity verification, device fingerprinting, consortium data), Experience identifying fraud patterns or working with fraud detection strategies (i. e. credit washing etc.), Ability to translate analysis into clear actions (rules, controls, strategy changes) and exposure to A testing, experimentation frameworks, or champion/challenger strategies

Nice to Have

Experience in subprime consumer lending, fintech, payments, or another regulated financial services technology environment., Hands-on experience applying AI to fraud management

What You'll Do.

Analyze application and early performance data to identify fraud patterns, including synthetic identity, first-party fraud, and credit abuse., Develop and implement fraud detection strategies, including rules, thresholds, and decisioning logic., Monitor early performance (e.

, FPD, zero-pay accounts) to identify potential fraud-driven losses., Distinguish fraud risk vs credit risk, improving approval quality and reducing early loss., Evaluate and optimize third-party fraud tools and data sources (e.

, identity verification, device intelligence, consortium data)., Design and execute tests to evaluate fraud strategies and improve detection performance., Work with Product and Engineering to implement fraud rules and ensure accurate execution in production systems., Investigate emerging fraud trends and proactively recommend changes to controls and policies., Collaborate with Operations or servicing teams to improve fraud identification post-origination.

How You'll Work.

Team & Collaboration

Work closely with Credit, Product, Operations and Engineering to ensure fraud risk is properly identified and separated from credit risk in decisioning.; Collaborate cross-functionally with other departments to ensure decisions align with business goals and risk appetite.; Collaborate with Operations or servicing teams to improve fraud identification post-origination.

Communication Scope

Translate analysis into clear actions; Distill complex problems and analysis into a clear and concise narrative

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