Vice President - Risk

Lobel Financial•Anaheim, CA

16h•Hybrid

About The Position

The Vice President of Risk will lead Lobel Financial’s enterprise risk function and modernize how the company measures, predicts, and manages risk. The role owns credit risk strategy, risk analytics and modeling, portfolio performance, and the risk technology stack. The Vice President will balance growth and loss performance while maintaining strong governance and regulatory compliance. This is a hybrid position based at the company’s headquarters in Anaheim, California, and reports through the Chief Investment Officer. The leader will set the vision and multi-year roadmap for the risk function, lead and develop teams across credit risk, analytics, modeling, and risk operations, and advise executive leadership and the Board on risk appetite, loss forecasting, and portfolio strategy. The role also owns underwriting strategy and credit policy, monitors portfolio performance, and partners with Collections and Servicing on loss mitigation and recovery. The Vice President will drive adoption of modern risk technologies and data, including machine learning, AI-driven scorecards, alternative data, cloud-based analytics, automation, and real-time decision engines. They will strengthen fraud detection and model risk management, ensure policies and models support fair lending and adverse action requirements, and work with Compliance and Legal on regulatory exams, audits, and changing consumer finance regulation. The role partners across Sales, Dealer Relations, Operations, and Finance to balance growth with credit quality, and translates risk insights into clear business recommendations.

Requirements

Bachelor’s degree in Statistics, Mathematics, Economics, Finance, Data Science, or a related quantitative field.
12+ years of experience in consumer lending risk management, including at least 5 years in a senior leadership role.
Track record of modernizing a risk function, such as deploying machine learning models, new data sources, or automated decision engines into production.
Deep knowledge of credit scoring, underwriting strategy, loss forecasting, and portfolio analytics.
Working knowledge of modern analytics tools and platforms such as Python, R, SQL, SAS, and cloud data environments.
Strong understanding of model risk management and consumer lending regulation, including fair lending and adverse action requirements.
Demonstrated ability to lead change in an established organization and build buy-in across teams.
Excellent communication skills, including experience presenting to executive leadership and Boards.

Nice To Haves

Experience in auto finance, including indirect lending through a dealer network.
Subprime or non-prime auto lending experience and understanding of the segment’s risk dynamics.
Familiarity with auto-specific risk drivers, including deal structure, LTV, payment-to-income, vehicle valuation, dealer performance, repossession, and remarketing.
Experience with dealer risk monitoring and fraud prevention in auto lending.
Advanced degree (MS, MBA, or PhD) in a quantitative or business discipline.
Experience leading a risk technology migration or vendor selection for decisioning, data, or modeling platforms.

Responsibilities

Set the vision and multi-year roadmap for the risk function in alignment with company modernization goals.
Lead, develop, and grow teams across credit risk, analytics, modeling, and risk operations.
Advise executive leadership and the Board on risk appetite, loss forecasting, and portfolio strategy.
Own underwriting strategy, credit policy, and approval criteria across the full credit spectrum.
Monitor portfolio performance, including delinquency, charge-offs, roll rates, recoveries, and vintage trends.
Partner with Collections and Servicing to optimize loss mitigation and recovery strategies.
Lead adoption of modern risk tools, including machine learning and AI-driven scorecards, alternative and bureau-plus data, and real-time decision engines.
Modernize risk data and analytics infrastructure in partnership with IT and Data teams, including cloud platforms and automation.
Introduce champion/challenger testing and rapid experimentation to improve decisions.
Strengthen detection of identity, synthetic, and income/employment fraud.
Maintain model risk management practices for validation, monitoring, and documentation.
Ensure models and policies support fair lending, explainability, and adverse action requirements.
Partner with Compliance and Legal on regulatory exams, audits, and evolving consumer finance regulation.
Work with Sales, Dealer Relations, Operations, and Finance to balance volume growth with credit quality.
Translate complex risk insights into clear recommendations for business leaders.