Senior Credit Risk Analyst

Responsibilities

• Develop and optimize credit policies, underwriting rules, approval thresholds, credit limits, and pricing for personal loans.
• Conduct deep dive analysis on application fraud, firstparty risk, and early delinquency signals.
• Review complex manual underwriting cases and set escalation frameworks.
• Perform vintage analysis, roll rate analysis, and cohort forecasting to predict credit losses.
• Track core risk KPIs including but not limited to: approval rate, default rates, day past due, roll rates, and loss given default.
• Build automated dashboards and weekly/monthly risk MI for leadership and investors.
• Identify emerging risks, early warning indicators, and portfolio concentration; recommend mitigation actions.
• Conduct stress testing and scenario analysis under changing economic conditions.

• Design and measure A/B tests for credit rules, data sources, and customer segments.
• Evaluate new alternative data to improve predictiveness.

• Ensure alignment with local lending regulations, fair lending, and responsible lending standards.
• Support internal audit, risk reviews, and investor due diligence on credit policies and performance.
• Document policies, decision logs, and model governance materials.

• Advise product and engineering on credit risk features and decision engine logic.
• Partner with operations to streamline verification and reduce friction.
• Support funding partners and capital markets with portfolio risk reporting.

• 5–7 years of handson credit risk experience in personal loans, consumer finance, fintech, or NBFC/bank retail lending.
• Proven track record building credit strategies, or underwriting policies for lending business.
• Strong SQL and Excel proficiency; experience with Python/R or analytical tools (SAS, Tableau, Power BI) is required.
• Deep understanding of risk metrics: PD, LGD, EAD, vintage analysis, roll rates, loss forecasting.
• Experience with A/B testing, decision engines, and credit bureau data.
• Knowledge of regulatory compliance in consumer lending (local laws, data privacy, fair lending).

• Exposure to alternative data and machine learning in credit decisioning.
• Strong stakeholder management and presentation skills.
• Experience in an Ontario fintech startup or high-growth alternative lender.