United States onlyOverview:
The Fair Banking Qualitative Risk Manager is responsible for managing and overseeing a team of analytics professionals who perform modeling and qualitative assessments to identify, measure, and mitigate Fair Lending risk across the lending lifecycle. This role ensures compliance with regulatory expectations and internal risk management standards by providing credible challenge, analytical oversight, and governance of statistical methodologies used to evaluate underwriting, pricing, redlining and other aspects of Fair Banking performance. The manager collaborates with Compliance, Risk, and business partners to ensure results are accurately interpreted, communicated, and incorporated into fair and responsible banking practices.
Primary Responsibilities:
- Manage and mentor a team of Fair Lending analysts performing regression modeling, matched-pair analysis, redlining analytics, and comparative file reviews.
- Exercise usual authority of a manager concerning staffing, performance appraisals, promotions, salary recommendations, performance management and terminations.
- Establish priorities, assign projects, and monitor progress to ensure timely, high-quality deliverables aligned with department goals.
- Foster a culture of analytical integrity, professional development and cross-team collaboration between analytics, and business partners.
- Oversee model development and maintenance processes to ensure adherence to regulatory and model-risk expectations.
- Review and approve analytical frameworks, variable selection methodologies, segmentation strategies, and model documentation, to ensure transparency and reproducibility.
- Provide credible challenge to assumptions, controls, and outcomes produced by analysts; ensure the findings are fully supported, statistically valid and risk contextualized.
- Coordinate with Model Risk Management and Internal Audit during validation, periodic reviews, and model inventory updates.
- Oversee development of written analyses, memo, dashboards, and reporting materials for Senior Management, Internal Audit, and regulators.
- Act as a liaison for all Quantitative Risk Management projects for Senior Management related to a diverse portfolio of bank wide divisional areas, external consultants, vendors, and peer banks on facets of quantitative risk management.
- Understand and adhere to the Company’s risk and regulatory standards, policies, and controls in accordance with the Company’s Risk Appetite. Design, implement, maintain and enhance internal controls to mitigate risk on an ongoing basis. Identify risk-related issues needing escalation to management.
- Adhere to applicable compliance/operational risk controls in accordance with Company or regulatory standards and policies.
- Promote an environment that supports belonging and reflects the M&T Bank brand.
- Maintain M&T internal control standards, including timely implementation of internal and external audit points together with any issues raised by external regulators as applicable.
- Complete other related duties as assigned.
Education and Experience Required:
Bachelors’ degree,
OR in lieu of a degree,
A combined minimum of 14 years’ higher education and/or work experience, including a minimum of 10 years’ related experience (inclusive of 4 years supervisory/management experience)
-OR-
Master’s degree in mathematics, Statistics, Quantitative Analysis or another technical discipline and a minimum of 8 years’ related experience (inclusive of 4 years supervisory/management experience),
OR in lieu of a degree,
A combined minimum of 14 years’ higher education and/or work experience, including a minimum of 8 years’ related experience and/or (inclusive of 4 years supervisory/management experience).
Minimum of 10 years’ related experience (inclusive of 4 years supervisory/management experience)
Banking or Financial Services experience.
Experience with SAS, SAS Enterprise Miner and other Statistical Software Packages.
Advanced Knowledge of SQL and Microsoft Office.
Ability to utilize analytics in a collaborative manner across business functions and product lines to derive optimum solutions.
Demonstrated ability to communicate complex concepts.
Demonstrated ability to manipulate and analyze data across large databases.
