Credit Risk Modeling & Database Manager - Vice President

Sumitomo Mitsui Banking Corporation•New York, NY

1d•Hybrid

About The Position

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. Role DescriptionSMFL is seeking a Credit Risk Modeling & Database Manager. Credit risk models play a crucial role in credit decisioning by helping financial institutions evaluate the creditworthiness of borrowers. These models quantify the potential risks associated with lending, enabling informed decisions and mitigating potential losses. They are essential for assessing the probability of default, estimating potential losses in the event of default, and determining appropriate interest rates. Credit risk models can be based on financial statement analysis, default probability, or machine learning techniques. They are used to determine the level of credit risk associated with extending credit to a borrower, ensuring that lenders make informed decisions and manage their credit risk exposures effectively. The process of credit risk modeling involves data collection, preprocessing, modeling techniques, model validation, and compliance with regulatory requirements. It is a structured approach that ensures the models are robust, transparent, and high performing, supporting better decision-making and compliance with evolving standards. SMFL utilize two types of models: the Quick Decision Model (Scorecard) and G- Grade model which is based on a Probability of Default Model (Moody’s’ RiskCalc) in determining the creditworthiness of borrowers. Credit Risk Modeling Analyst role is to monitor, validate and maintain credit risk models to predict default probability and potential losses and to be in compliance with SMBC Model Risk Governance Policy and to be in compliance with Regulatory Guidance SR 11-7.

Requirements

Bachelor’s degree in quantitative fields such as Mathematics, Statistics, or Computer Science.
Experience with machine learning algorithms and techniques.
Proficiency in programming languages like vb.NET, SQL, C#, R or SAS.
Strong understanding of financial markets and investment principles.
Experience with data visualization tools (e.g., Tableau, Power BI).
Excellent problem-solving and analytical skills.
Strong communication skills to explain complex models to non-experts.
Familiarity with database management.
Proven experience in quantitative modeling and data analysis.
Strong mathematical and statistical foundation.
Ability to work independently and manage multiple projects simultaneously.
Attention to detail and a high level of accuracy.
Strong organizational skills.
Knowledge of data mining and predictive modeling techniques
Two plus years in Financial Sector having Model Risk or Database Management experience.

Responsibilities

Monitoring and managing SMFL credit models and adhere to the Model Risk Management Policy of SMBC and SR 11-7 Fed Guidance
Analyzing complex data sets to identify patterns and trends- Development data vs Actual data
Presenting findings to stakeholders and making recommendations based on the data
Monitoring and validating model performance and updating models as needed and preparing Model Monitoring reports in collaboration with SMFL HQ
Staying current with economic conditions and regulatory changes that may impact risk models
Collaborating with other departments, such as Finance and Operations, to understand the company’s risk exposure
Documenting all processes and methodologies used in risk modeling for transparency and future reference
Providing training and guidance to other team members on risk modeling techniques and strategies
Ensuring compliance with all industry regulations and standards for risk modeling
Monitor the gradings process such as internal Risk rating /JP and US Reg classification ratings, update applicable scorecards, monitor limits, oversee data accuracy to ensure compliance with business and institutional guidelines and ensure data integrity in the credit systems.
Manage database for model monitoring purposes specifically for G grade model and if required for QDM scorecard.
Prepare and present updates on Portfolio Reviews to business management and Risk when requested and support the portfolio analysis trends and reporting and analytics.
Participate in new credit products approval and grading methodologies at the beginning. E.g., Structured finance leases, Synthetic Leases etc.
Work with Internal Control in managing and monitoring the Model Risk Management and Risk Appetite metrics for Credit and escalating the breachers to Senior Management.
Participate in Policy and Procedure updates related to Credit Risk Models and grading and amendment annually and approval process.
Develops close working partnerships with the Leasing sales team, operations and other internal company staff to ensure open communication channels are available to handle issues associated with data-driven requests. Responds to calls and requests for information from the team.
Able to design databases that are efficient, reliable, and scalable. Should be capable of logical and physical design of databases and be able to implement best practices in different database architectures. Should be able to perform data analysis and inform decision-making based on data interpretation and visualization. Should be proficient in using database languages such as vb.NET. SQL, Oracle, and C# MongoDB,
Comply with SMFL internal control standards and SMBC compliance at all times.
Develop Credit Scoring Models using advancements in technology, machine learning algorithms in credit scoring.
Bring initiative in AI technology to current SMFL database structures to make process efficiencies.
Carry out any other duties that management assigned in addition to what is allocated above.