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SMBC Group is a top-tier global financial group. Headquartered in Tokyo and with a 400-year history, SMBC Group offers a diverse range of financial services, including banking, leasing, securities, credit cards, and consumer finance. The Group has more than 130 offices and 80,000 employees worldwide in nearly 40 countries. Sumitomo Mitsui Financial Group, Inc. (SMFG) is the holding company of SMBC Group, which is one of the three largest banking groups in Japan. SMFG’s shares trade on the Tokyo, Nagoya, and New York (NYSE: SMFG) stock exchanges.

In the Americas, SMBC Group has a presence in the US, Canada, Mexico, Brazil, Chile, Colombia, and Peru. Backed by the capital strength of SMBC Group and the value of its relationships in Asia, the Group offers a range of commercial and investment banking services to its corporate, institutional, and municipal clients. It connects a diverse client base to local markets and the organization’s extensive global network. The Group’s operating companies in the Americas include Sumitomo Mitsui Banking Corp. (SMBC), SMBC Nikko Securities America, Inc., SMBC Capital Markets, Inc., SMBC MANUBANK, JRI America, Inc., SMBC Leasing and Finance, Inc., Banco Sumitomo Mitsui Brasileiro S.A., and Sumitomo Mitsui Finance and Leasing Co., Ltd.

The anticipated salary range for this role is between $213,000.00 and $235,000.00. The specific salary offered to an applicant will be based on their individual qualifications, experiences, and an analysis of the current compensation paid in their geography and the market for similar roles at the time of hire. The role may also be eligible for an annual discretionary incentive award. In addition to cash compensation, SMBC offers a competitive portfolio of benefits to its employees.

Role Description

The Director of Wholesale Risk Grading Modeling will lead the design, development, and implementation of advanced risk rating models (PD, LGD, EAD) to support underwriting, capital allocation, and regulatory compliance (e.g., Basel III/IV, SR 11-7). This role requires expertise in statistical modeling, governance frameworks, and collaboration with credit officers to ensure risk ratings drive data-driven decision-making for commercial and wholesale portfolios.

Role Objectives

+ Risk Rating Model Development

+ Lead the end-to-end development and calibration of wholesale risk grading models (PD, LGD, EAD) for use in internal ratings-based (IRB) approaches, pricing, and portfolio management.

+ Design methodologies (e.g., machine learning, econometric models) to improve risk differentiation for complex exposures (e.g., corporates, project finance, CRE).

+ Ensure alignment with Basel III/IV requirements, internal risk appetite, and business strategies.

+ Collaborate with Model Risk and Validation (MRV) and model owners to address validation findings and ensure timely remediation.

+ Model Governance & Monitoring

+ Establish robust monitoring frameworks to assess model performance (e.g., rank-ordering accuracy, stability testing, population drift analysis).

+ Document model assumptions, limitations, and governance processes to meet audit and regulatory standards.

+ Implement controls to maintain model integrity and recalibrate ratings as portfolio or economic conditions evolve.

+ Regulatory & Business Integration

+ Support regulatory submissions (e.g., ECB TRIM, Basel III monitoring) and respond to regulatory feedback on risk rating methodologies.

+ Partner with credit officers and underwriters to operationalize risk grades into loan approvals, limit-setting, and management reporting.

+ Work with IT teams to automate risk rating workflows and integrate models into production systems (e.g., loan origination platforms).

+ Team Leadership & Innovation

+ Mentor junior staff and promote knowledge-sharing on emerging trends (e.g., climate risk integration, AI-driven rating tools).

+ Stay current with industry best practices (e.g., PD calibration for low-default portfolios) and regulatory updates.

+ Stakeholder Engagement

+ Present model outputs, limitations, and strategic recommendations to senior leadership and credit committees.

+ Collaborate with portfolio management and finance teams to align risk ratings with capital planning and stress testing frameworks.

Qualifications and Skills

Education:

+ Master or PhD degree in Quantitative Finance, Statistics, Economics, or a related field.

Experience:

+ 8+ years in wholesale credit risk modeling, with 3+ years leading model development teams.

+ Proven track record in building Basel III/IV-compliant IRB models for commercial/wholesale portfolios.

+ Experience resolving model validation findings and addressing regulatory scrutiny (e.g., ECB, OCC).

Technical Skills:

+ Advanced proficiency in Python, R, or SAS; expertise in machine learning frameworks (e.g., scikit-learn, XGBoost).

+ Deep knowledge of statistical methods (logistic regression, survival analysis, clustering) and data tools (SQL, Spark).

+ Familiarity with credit risk platforms (e.g., Moody’s RiskCalc, CreditEdge) and cloud infrastructure (AWS, Azure).

Certifications (Preferred):

+ FRM, CFA, or CRC.

Soft Skills:

+ Ability to translate technical model outputs into actionable business insights.

+ Strong project management skills with a focus on regulatory deadlines and stakeholder priorities.

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SMBC’s employees participate in a Hybrid workforce model that provides employees with an opportunity to work from home, as well as, from an SMBC office. SMBC requires that employees live within a reasonable commuting distance of their office location. Prospective candidates will learn more about their specific hybrid work schedule during their interview process. Hybrid work may not be permitted for certain roles, including, for example, certain FINRA-registered roles for which in-office attendance for the entire workweek is required.

SMBC provides reasonable accommodations during candidacy for applicants with disabilities consistent with applicable federal, state, and local law. If you need a reasonable accommodation during the application process, please let us know at [email protected].