VP, Risk (Fraud Strategy & Analytics)
Concora Credit · Beaverton, OR · 1 mo ago
FinanceFull-time
Responsibilities
- Lead the fraud strategy analytics and modeling team to enhance Concora Credit’s capabilities in the fraud risk space.
- Guide, coach, and motivate the team, consisting of different skill levels from Analysts to a Director.
- Own fraud strategy for identity fraud and for existing account fraud (transaction fraud, payment fraud, and account takeover) in the credit card and private label business space.
- Have a strong sense of ownership guided by the objective of minimizing fraud losses while driving continuous customer experience improvements.
- Design and enhance the fraud strategy roadmap for the organization.
- Partner with risk leadership, different business and operational organizations, and drive rapid change across the organization.
- Effectively be on top of and communicate the state of fraud and updates/recommendations to key stakeholders.
- Be well-versed in the latest data, modeling techniques, technologies, and solutions effective in fighting fraud.
- Evaluate and implement new data/solutions to improve fraud defenses.
- Have cutting-edge knowledge of all fraud-related items (past, present, and how the future is likely to evolve) in the consumer credit space.
- Be familiar with statistical/ML modeling techniques leveraged in fraud risk modeling and be able to guide the data scientists and analysts towards optimal outcomes.
Qualifications
- Bachelor’s degree or equivalent experience.
- Advanced degree in Statistics, Econometrics, Mathematics, Engineering, Financial Engineering, Operations Research, Physics, or Technology preferred.
- 10+ years’ experience in the consumer lending industry.
- 5+ years of hands-on experience with fraud strategy and analytics, preferably in the consumer credit space.
- 5+ years of experience/familiarity with statistical analysis tools and data software languages such as SAS, R, Python, SQL, and Excel.
- 5+ years of experience managing a team with analysts and data scientists.
- Solid understanding and knowledge of retail or consumer lending businesses.
- Very strong analytical, strategic and white space thinking skills.
- Ability to communicate effectively and influence others across functions.