VP, Risk Management & Analytics
Vice President, Risk Management & Analytics
WebBank (the "Bank") is headquarter in Salt Lake City, Utah and is an FDIC insured, Utah state chartered bank. WebBank is a leading national provider of online consumer and small business loans made in partnership with finance companies, OEMs, retailers and financial technology companies.
WebBank Corporation seeks a Vice President, Risk Management & Analytics in New York City.
Oversee model risk management and risk analytics.
- Oversee the model development, validation, and governance frameworks and assess the risk modeling methodologies, outputs, and processes across the various industry-leading Fintech lending and retail partners associated with the Bank. Ensure that all the models built using various software such as SAS, E-Miner, SQL, R, Knowledge Seeker, and Excel are accurately built, estimated, and correctly deployed (15%).
- Understand relevant business processes and portfolios associated with model use, including technical issues in econometric and statistical modeling and apply these skills toward assessing model risks and opportunities (15%).
- Develop and implement statistical and machine learning based quantitative models used in underwriting strategies, loss forecasting, and capital calculations as well as explore alternative approaches to assess model design and advance future capabilities (5%).
- Plan and manage validation projects, manage model inventories and the model governance process, and communicate clearly and concisely both verbally and through written communication via model memos, validation reports and presentations. Ensure that model validation practices carried out across the firm are in line with best in class industry practices and credit risk modeling guidance from the OCC (Office of the Comptroller) and FDIC (Federal Deposit Insurance Corporation), as well as OCC 11-12 and SR 11-7 model risk guidance (15%).
- Present model validation process, methodologies, and techniques to regulators (5%).
- Manage and head the Bank's Financial Review Committee to review and assess the Bank's financial health, asset performance, loss reserve allocation, as well as performance vis-a-vis the budget; develop and drive analysis of portfolio health through modeling as well as valuation techniques to drive best investment decisions (10%).
- Analyze existing strategic partner programs from credit risk standpoint, evaluate asset management strategies, as well as drive new partner deals via risk evaluation of programs and associated due diligence (10%).
- Oversee the development, administration and maintenance of the Bank's enterprise data warehouse (5%).
- Develop and enhance the analytics strategy of the Bank including the development and enhancement of business intelligence solutions that assist Bank personnel in identifying, monitoring, and evaluating KRIs (Key Risk Indicators) and KPIs (Key Performance Indicators) (5%).
- Support the data analytics needs of the various information consumers across the Bank and work with the Bank's partner programs, internal teams, and external consultants to ensure seamless integration of disparate data sources into the enterprise data warehouse (10%).
- Collaborate with the technology team to maintain and enhance analytics infrastructure and technology strategy including backup & recovery, data storage, security, and governance (5%).
- Such other related duties and responsibilities as assigned.
- Master's degree in Statistics, Economics, Mathematics, Engineering (Financial, Industrial, Mechanical, Electrical), Operations Research, Physics, Computer Science, or close related field.
- No less than 5 years of experience [acceptable job titles; VP, Risk Management & Analytics; Senior Manager Operation Risk Modeling; Manager Model Risk Management; Project Manager Decision Management; and related positions].
- Demonstrated experience in jobs that involve quantitative analysis, statistical modeling, and/or data analytics.
- Demonstrable working knowledge and understanding of: a) consumer lending-based modeling; b) advanced statistical modeling techniques including machine learning techniques used across various domains of consumer banking and lending such as underwriting, fraud, collections etc.; and c) data visualization and dashboard development - including advanced Excel, SQL, and other tools.
- Demonstrable working knowledge and understanding of credit risk modeling guidance from the OCC (Office of the Comptroller of the Currency) and FDIC (Federal Deposit Insurance Corporation) as well as OCC 11-12 and SR 11-7 model risk guidance.
- Demonstrated ability to: a) develop analysts; and b) work in a matrix organization.
- Demonstrated proficiency with statistical and data software languages and packages including SAS, R, Knowledge Seeker, VBA and E Miner.