Chrissy Sievers

Approach

Reducing friction for our customers while detecting (and removing) bad actors requires fast yet accurate detection methods. Using a blend of methods required a 10,000 foot view strategy and execution deep dives to balance risk reduction with improved customer outcomes. Some of the experiences I led included:

• Developed fraud detection proof of concepts including the use of voice and facial biometrics. This resulted in a 90% success rate in detecting bad actors through call center volume and a self-serve flow “selfie” customer verification flow.

• Designed and built enterprise-level fraud adjudication platform, increasing agent decision accuracy by 5%, efficiency by 20%, and improving agent usability scores by 19 points.

• Supplemented existing fraud detection tools with tech capabilities and enhancements that increased the accuracy of our mobile image capture flow, reducing friction with our legitimate customers by 10%.

• Supervised the company’s largest onboarding of 47M subscribers to a new claims platform, furnishing them with risk identification and mitigation tools such as machine learning-powered claim linking and adjudication suggestions.

• Rapidly scaled a B2B customer verification experience, globally, resulting in the stoppage of an international fraud ring.

• Data analysis on user scenarios and forecasting of expected experiences and results throughout POC development and trials/tests.

• Integration upgrades, improving user experience and providing more sophisticated UI interactions.

• Robust usability studies and consistently applying qualitative data alongside quantitative studies for more informed decision making.

• Trained, coached, and expanded product team to 3 Fraud Product PMs, fostering psychological safety and bolstering product team performance.