Manages the bank’s model risk management program and a team of model validators; validates quantitative models used for BSA/AML, Asset Liability Management, Interest Rate Risk Stress Testing, Commercial Loan Risk Rating, and CECL. Leading development of MRM guidelines and validation procedure around Generative AI technology.

Manages the bank’s model inventory; validates quantitative models used for BSA/AML, Fraud detection, Credit Loss for AFS, and CECL.

Provide advisory services to financial institutions on strategy and solution to address the latest accounting regulatory challenges, CECL/IFRS9 implementation, through working with customers’ senior management and senior executives:• Identify challenges, build business cases and develop technology roadmaps• Select suitable methodologies according to banks’ lending portfolios and in-house capabilities• Develop repeatable production processes to optimize investments in technology and people through streamlining the model execution, data aggregation and reporting process• Leverage and harmonize data, loss forecasting models, and processes built for stress testingParticipate in design and development of risk solutions that solve challenges of risk and finance integration and transformation for bank utilizing expertise in model risk management, credit risk modeling, risk analytics and experience in risk regulations like SR11-7, DFAST / CCAR, and accounting standard like CECL/ IFRS9.

Created and delivered high-value model risk management collateral through independent work, coupled with the application of regulatory guidance so as to promote strengthened internal controls on models within the bank and offer improved model methods for general use within the industry.Accomplishments include:• Led or conducted various model validations/review for high profile credit risk models used in CCAR Stress Testing, ALLL, pricing and acquisition or BAU risk monitoring; Consistently exceeded expectations for meeting challenging timeline for business-critical deliverables• Identified and covered gaps in vendor work on high profile CCAR stress testing projects• Led effort in addressing regulatory concerns around third party behavior scoring system TRIAD, and identified calculation errors in supporting documentation provided by vendor• Promoted a new data analysis procedure to identify data input issues; initiated/developed a review procedure of models that were recently validated• Managed seventeen summer interns and assisted with process design and implementation to streamlining issue resolution and validations/reviews for low risk models

• Worked with LOB managers in evaluation and improvement of current and developing fraud detection strategies, quantifying loss avoidance and implementing decisions • Analyzed Credit Card, ATM and Check Deposit fraud from a global perspective, aggregating fraud data across channels and identifying common characteristics to mitigate fraud loss caused by fraud rings • Built statistical models to aggregate and consolidate similar strategy rules in order to prioritize out-sort cases for review

• Developed, implemented and validated statistical models utilizing risk analysis and stochastic simulation to predict transgenic product performance using MATLAB and R• Conducted sensitivity analysis on population genetics model parameters of transgenic product features, creating archive files using VB, R and Excel• Developed multivariate predictive models to analyze product effects by comparing the test and control groups using Logistic Regression for responses with rating scores; analysis involved SAS DATA steps, SQL, Macros, and base/advanced procedures such as GLM, MIXED, MEANS, SORT, TABULATE, REPORT, etc.• Performed data extraction and customization for large data set; generated various graphs and tables for data visualization using Excel, JMP and SAS; enhanced series of SAS codes and Macros to automate the output process for standard reporting.