Global Financial Crimes - Sanctions Screening, Tuning & Optimization, AVP
Job Summary:
Reporting into the Head of Financial Crimes Transaction Monitoring, this new position has been created for the purpose of establishing GFCD Operations Intelligence & Analytics capabilities for BTMU.
One of several key positions in the new Global Financial Crimes Division Operations function, this position will be responsible for (1) helping to identify detection scenarios, (2) provide analytics support for developing, tuning, optimizing and modifying segmentation to improve transaction monitoring and screening systems, (3) customer segmentation (4) helping to coordinate the implementation of scenarios, which detect financial crime and (5) create statically representative samples to ensure that risk is not missed below the threshold. The incumbent is responsible for supporting leadership to ensure a globally consistent effort that enables continuing improvement to the transaction monitoring capabilities and further mitigate potential financial crime.
Major Responsibilities:
In connection with the Global Financial Crimes program
Develop mathematical or statistical theory to interpret customer KYC data and historical transaction data to group customers and non-customers into segments in order to monitor their activity in the correct thresholds
Identify relationships and trends of historical transactional data for clustering for AML transaction monitoring
Analyze the clusters/relationships and present the information to Senior Managers in the data visualization tools
Create statistical representative samples for ATL/BTL testing in order to validate that the transaction monitoring model is effective and functioning accordingly.
Process large amount of data for statistical modeling and graphic analysis.
Perform model validation, memorializing model selection rationales and defined assumptions.
Develop and test experimental designs, sampling techniques, and analytical methods in order to monitor new typologies and emerging risks.
Develop data mining methodologies, including logistic regression, random foresr, xgboost and Bayesian networks
Help develop of models involving tuning, calibration, segmentation and optimization.
Support the development of policies and procedures for AML transaction monitoring life cycle, including reviews of scenario validation, segmentation and optimization tools.
Support large strategic optimization and segmentation program to enhance and tune MUFG 's GFCD Transaction Monitoring Program.
Recommend customer segmentation and optimization for MUFG 's GFCD monitoring system across multiple lines of business.
Coordinate with regional Intelligence & Analytics teams to implement on the global model.
Work collaboratively across functional teams within GFCD to ensure effective and efficient operations with clearly defined roles and responsibilities.
Experience/Skills
Knowledge of mathematics particularly statistics.
Ability to code using R or Python for customer segmentation and data analytics.
Ability to solve problems through mathematical and deductive reasoning.
3-5 years ' experience designing, analyzing, testing and/or validating BSA/AML models, and/or OFAC sanctions screening models.
Familiarity implementing, testing or evaluating performance of financial crime and compliance systems.
Proven track record of strong quantitative testing and statistical analysis techniques as it pertains to BSA/AML models, including name similarity matching, classification accuracy testing, unsupervised/supervised machine learning, neural networks, fuzzy logic matching, decision trees, etc.
Familiarity of current compliance rules and regulations of the FRB, SEC, OCC, FATF, FinCEN, OFAC, and familiarity with USA PATRIOT Act, BSA/AML and OFAC screening regulations.
Prior experience designing compliance program tuning and configuration methodologies, including what-if detection scenario analytics, excess over threshold, and sampling above/below-the-line (ATL/BTL) testing.
Working knowledge of one or more of the following programming platforms: SAS, Matlab, R, Python, SQL, VBA, etc.
Familiarity with vendor models like Hotscan, Actimize SAM/WLF, SearchSpace, RDC, Bridger Insight, ACE Pelican, TCH OFAC Screening (EPN), FICO Credit/Debit, Guardian Analytics, and ThreatMetrix.
Strong knowledge about model risk management and associated regulatory requirements
Experience interacting with the Executive Committee Leadership, control function leadership, and compliance subject matter experts
Proven excellence in execution in complex and demanding situations
Collaborative with strong interpersonal communication skills
Systemic thinker across enterprise
Process oriented coupled with a strong ability to develop appropriate program enhancing strategies
Detail-oriented and organized execution
Executive level presentation skills
An Enterprise Risk Management perspective
Additional skills:
Experience interfacing with banking regulators and enforcement staff
Thorough understanding of an effective financial crimes risk management framework
Demonstrated ability to manage multiple projects simultaneously
The ability to interact effectively at all levels of the organization, including Bank staff, management, directors and prudential regulators
Ability to work autonomously and initiate and prioritize own work
Ability to work with teams of project managers
Solid judgment, strong negotiating skills, and a practical approach to implementation including knowledge of Bank systems
Ability to balance regulatory requirements with the best interests of the Bank and its customers
Ability to prepare analytical reports and visual representation of information.
Ability to apply mathematical principles or statistical approaches where needed to solve problems.
Education:
Bachelor's degree in statistics, mathematics, quantitative analysis, economics or related field is required. Advanced degree preferred.
The typical base pay range for this role is between $85k - $105k depending on job-related knowledge, skills, experience and location. This role may also be eligible for certain discretionary performance-based bonus and/or incentive compensation. Additionally, our Total Rewards program provides colleagues with a competitive benefits package (in accordance with the eligibility requirements and respective terms of each) that includes comprehensive health and wellness benefits, retirement plans, educational assistance and training programs, income replacement for qualified employees with disabilities, paid maternity and parental bonding leave, and paid vacation, sick days, and holidays. For more information on our Total Rewards package, please click the link below.