Intuit
Overview
As part of our commitment to preventing fraud across all consumer lending products, we are expanding our Fraud Policy team, which utilizes cutting‑edge AI technology to detect and prevent fraud while minimizing impact on good customers. As a Risk Policy Lead, you will collaborate with Risk Operations, Data Science, Product, Engineering and Compliance teams to design and implement fraud mitigation risk strategies. If you’re passionate about solving real customer problems through decision science and analytics, we welcome you to join our talented team.
Responsibilities
Fraud Detection and Investigation: Monitor alerts and analyze real‑time signals to detect suspicious activity (e.g., account takeover, check kiting, synthetic identity, mule activity, ACH fraud, overdraft, remote access tools). Investigate and resolve fraud cases across onboarding, KYC, account funding, and account usage stages. Leverage fraud tools and external vendor data to review high‑risk activity and recommend actions.
Data‑Driven Analysis: Analyze fraud trends and patterns using data analytics tools (SQL, Excel, dashboards) to identify emerging threats or gaps in current detection logic. Support creation and tuning of fraud detection rules, machine learning models, and velocity checks in collaboration with fraud strategy and data teams. Track key fraud KPIs and prepare reports for stakeholders.
Operational Efficiency and Documentation: Respond to fraud‑related escalations from customer support and other internal teams. Assist in refining workflows and automations to improve response time and operational throughput. Document fraud scenarios, case investigations, root cause analysis, and preventive actions.
Cross‑Functional Collaboration: Work closely with compliance, risk policy, customer support, engineering, and external vendors. Participate in projects related to new product launches, fraud tooling enhancements, and regulatory reviews. Provide fraud subject‑matter expertise in discussions related to account security, identity verification, and money movement flows.
Qualifications
5+ years of experience in fraud operations or fraud analytics, preferably in fintech or banking.
Strong understanding of fraud typologies relevant to consumer financial products.
Experience with fraud tools and platforms such as Alloy, Sift, Ekata, Kount.
Proficiency in SQL and/or Excel; familiarity with Looker or other BI tools is a plus.
Familiarity with banking regulations and fraud return codes.
Strong analytical, investigative, and problem‑solving skills.
Excellent communication and documentation skills.
Nice to Have
Experience in fraud for digital banking, challenger banks, or fintech products.
Exposure to fraud rules management or machine‑learning based detection systems.
Prior work with ACH return reason codes, dispute handling, or chargeback processes.
Compensation Intuit provides a competitive compensation package with a strong pay‑for‑performance rewards approach. This position is eligible for a cash bonus, equity rewards, and benefits in accordance with applicable plans and programs. Pay is based on factors such as job‑related knowledge, skills, experience, and work location. To drive ongoing fair pay, Intuit conducts regular comparisons across categories of ethnicity and gender. Expected base pay range:
Bay Area, California: $172,000 – $232,500
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Responsibilities
Fraud Detection and Investigation: Monitor alerts and analyze real‑time signals to detect suspicious activity (e.g., account takeover, check kiting, synthetic identity, mule activity, ACH fraud, overdraft, remote access tools). Investigate and resolve fraud cases across onboarding, KYC, account funding, and account usage stages. Leverage fraud tools and external vendor data to review high‑risk activity and recommend actions.
Data‑Driven Analysis: Analyze fraud trends and patterns using data analytics tools (SQL, Excel, dashboards) to identify emerging threats or gaps in current detection logic. Support creation and tuning of fraud detection rules, machine learning models, and velocity checks in collaboration with fraud strategy and data teams. Track key fraud KPIs and prepare reports for stakeholders.
Operational Efficiency and Documentation: Respond to fraud‑related escalations from customer support and other internal teams. Assist in refining workflows and automations to improve response time and operational throughput. Document fraud scenarios, case investigations, root cause analysis, and preventive actions.
Cross‑Functional Collaboration: Work closely with compliance, risk policy, customer support, engineering, and external vendors. Participate in projects related to new product launches, fraud tooling enhancements, and regulatory reviews. Provide fraud subject‑matter expertise in discussions related to account security, identity verification, and money movement flows.
Qualifications
5+ years of experience in fraud operations or fraud analytics, preferably in fintech or banking.
Strong understanding of fraud typologies relevant to consumer financial products.
Experience with fraud tools and platforms such as Alloy, Sift, Ekata, Kount.
Proficiency in SQL and/or Excel; familiarity with Looker or other BI tools is a plus.
Familiarity with banking regulations and fraud return codes.
Strong analytical, investigative, and problem‑solving skills.
Excellent communication and documentation skills.
Nice to Have
Experience in fraud for digital banking, challenger banks, or fintech products.
Exposure to fraud rules management or machine‑learning based detection systems.
Prior work with ACH return reason codes, dispute handling, or chargeback processes.
Compensation Intuit provides a competitive compensation package with a strong pay‑for‑performance rewards approach. This position is eligible for a cash bonus, equity rewards, and benefits in accordance with applicable plans and programs. Pay is based on factors such as job‑related knowledge, skills, experience, and work location. To drive ongoing fair pay, Intuit conducts regular comparisons across categories of ethnicity and gender. Expected base pay range:
Bay Area, California: $172,000 – $232,500
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