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Lead Quantitative Analyst for Credit Risk
2 months ago
Reporting to the Director of Credit Risk Modeling, this position is responsible for spearheading and overseeing a quantitative modeling team within the Commercial Credit domain. The primary focus is to address data, systems, and modeling requirements for Commercial Risk Rating models, including Scorecards and Behavioral models, essential for effective credit risk management and various enterprise initiatives. This role may also contribute to model development efforts related to loss forecasting, CCAR (Comprehensive Capital Analysis and Review), stress testing, and economic capital practices. The individual will guide both daily operations and long-term strategic objectives of the team to align with business goals and regulatory compliance.
Key Responsibilities:
- Steer the Credit Risk Management Framework by establishing quantitative analytics and modeling strategies utilized in the risk rating framework across the organization.
- Recruit, mentor, and develop a team of modelers and quantitative analysts, providing guidance and leadership to achieve desired business outcomes.
- Oversee the creation, execution, and upkeep of Commercial Probability of Default (PD) and Loss Given Default (LGD) credit risk models, employing both internal and external data sources, advanced technologies, and agile modeling methodologies.
- Act as a liaison with key internal stakeholders, including Technology, Enterprise Data, Finance, Product, and Regulatory Affairs, to prioritize firm-wide initiatives.
- Coordinate the analysis of underwriting, behavioral, market, and economic data relevant to the bank's clientele, portfolios, and products. Interpret findings, formulate recommendations, and present insights to senior leadership.
- Engage with a diverse range of internal clients, including executive management, to elucidate the advantages, constraints, assumptions, and requirements associated with proposed scorecards and modeling strategies.
- Assist less experienced managers during the model development review process with the Model Development Working and Oversight Groups.
- Support internal business units in formulating and executing strategies for optimal pricing, underwriting, or funding, aimed at maximizing organizational profitability.
- Manage the establishment and implementation of performance metrics, reporting, and analyses to facilitate data-driven decision-making and forecasting for the firm's clientele, products, and portfolios.
- Incorporate automation and machine learning techniques, data frameworks, and implementation platforms to develop scalable modeling solutions across data mining, segmentation, back testing, reporting, and ongoing monitoring, thereby expediting the model development process.
- Exhibit organizational expertise in Rating scorecard deployment while collaborating with relevant committees to ensure all models are validated, presented, and communicated effectively to all stakeholders.
- Assess the need for redevelopment or recalibration based on shifts in market conditions, regulations, or strategy, and guide the redevelopment initiatives accordingly.
- Maintain an up-to-date understanding of standard concepts, best practices, and procedures in current behavioral and econometric modeling practices, as well as credit risk management, applying this knowledge to internal practices as necessary.
- Exercise managerial authority regarding staffing, performance evaluations, promotions, salary recommendations, performance management, and terminations.
- Comprehend and adhere to the company's risk and regulatory standards, policies, and controls in alignment with the organization's Risk Appetite. Design, implement, maintain, and enhance internal controls to mitigate ongoing risks, identifying issues that require escalation to management.
- Foster an inclusive environment that reflects the values of M&T Bank.
- Uphold M&T internal control standards, ensuring timely implementation of internal and external audit findings, along with any issues raised by external regulators as applicable.
- Perform other related duties as assigned.
The Commercial Scorecard group plays a vital role in the Credit Risk Management Framework. Risk Ratings are integral to numerous areas within the bank and significantly influence enterprise-level decisions, such as the Allowance for Loan and Lease losses, Approval Authority levels, and Asset Quality Metrics. This role is inherently technical and quantitative, necessitating meticulous attention to detail, execution, and follow-through on various initiatives within Credit. The ability to identify, analyze, rationalize, and communicate complex business challenges while recommending viable solutions is crucial for success in this position. Success in this role requires leveraging analytics collaboratively across multiple functions and products to derive optimal solutions to business challenges. This position interacts extensively with various business and functional areas of the bank, as well as with vendors, risk management consultants, and regulatory bodies. Additionally, the role involves occasional informational and educational engagements with internal and external stakeholders. The position communicates with executive management and regulatory authorities on all matters related to scorecard and behavioral modeling, as well as loss forecasting and stress testing, ensuring their awareness of significant issues. Furthermore, the position actively participates in assigned risk governance committees.
Supervisory/Managerial Responsibilities:
Direct management responsibility for a team of 3 to 10 Quantitative Credit Risk Management Analysts and Modelers, with potential direct management of other Quantitative Risk Managers.
Education and Experience Required:
Bachelor's degree and a minimum of 11 years of relevant experience, or in lieu of a degree, a combined minimum of 15 years of higher education and/or work experience, including at least 11 years of relevant experience.
A minimum of 4 years of managerial experience.
Strong understanding of quantitative analysis, econometric modeling, statistics, and related mathematics, along with commercial bank balance sheet management.
Advanced knowledge of risk analytics, including the development, implementation, and utilization of all relevant technologies and methodologies within an operationally and regulatory compliant framework.
Exceptional quantitative, model development, financial, economic, and statistical skills, including proficiency in statistical programming and data structures.
Familiarity with banking products and behaviors related to credit, interest rate risk, liquidity risk, stress testing, and economic capital management.
Excellent verbal and written communication skills, strong cross-functional collaboration abilities, leadership capabilities, and presentation skills.
Education and Experience Preferred:
3+ years of experience in developing sophisticated modeling frameworks utilizing cutting-edge techniques (e.g., ML, Python, PySpark, R).
Strong understanding of quantitative analysis, econometric modeling, statistics, and related mathematics, particularly in the context of commercial bank ratings frameworks.
Advanced knowledge of risk analytics, including the development, implementation, and utilization of all relevant technologies and methodologies within an operationally and regulatory compliant framework.
Proven track record of gathering, matching, and processing large datasets across various data types (structured or unstructured).
Knowledge of model development and governance standards within the banking sector, especially concerning credit card and consumer lending.
Excellent verbal and written communication skills, cross-functional collaboration skills, leadership skills, and presentation skills.
A PhD in Mathematics, Statistics, Quantitative Analysis, or another technical discipline is a plus. Financial Risk Manager (FRM) or Chartered Financial Analyst (CFA) designation is also advantageous.
Demonstrated ability to work both autonomously and collaboratively within a team environment.
A strong desire to learn and contribute to the team.