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About the Role
Position Title: Global Financial Crimes Design, Tuning and Optimization
Corporate Title: AVP
Internal Title: Manager
Reporting to: Vice President
Location: Bangalore
Job Profile
Purpose of Role
This position will be responsible for the design, calibration, optimization, and ongoing validation of trade surveillance and transaction monitoring (TM) scenarios across securities products. This role ensures the effectiveness of surveillance controls in detecting market abuse, financial crime risks, and anomalous trading behaviors, while balancing alert productivity, regulatory expectations, and operational efficiency.
The individual will work closely with Compliance, Surveillance Operations, Technology (e.g., Actimize/Siron/KX), and Model Governance teams to enhance detection capabilities through data-driven tuning, scenario refinement, and advanced analytics.
Main Responsibilities
- In coordination with Global and Regional Financial Crimes–
- Perform periodic tuning of AML transaction monitoring and trade surveillance scenarios (e.g., spoofing, layering, wash trades, insider trading, front running).
- Analyze alert volumes, false positives, and productivity metrics to recalibrate thresholds and parameters.
- Conduct back testing and sensitivity analysis across historical datasets to assess scenario performance.
- Identify over-/under-triggering scenarios and propose data-driven tuning recommendations.
- Support scenario de-scoping, consolidation, or enhancement based on risk coverage and efficiency.
- Design, implement, and optimize securities-focused TM scenarios covering: Equity, fixed income, derivatives, and structured products.
- Ensure monitoring coverage across key risk typologies (e.g., market abuse, AML risks, sanctions evasion, cross-border trading risks).
- Perform deep-dive analysis on transaction datasets to assess behavioral patterns and anomalies by leveraging advanced analytics.
- Develop and test experimental designs, sampling techniques, and analytical methods in order to monitor new typologies and emerging risks.
- Conduct BTL (Below-the-Line) and ATL (Above-the-Line) testing to assess detection effectiveness and missed risk.
- Develop data mining methodologies, including logistic regression, random foresr, xgboost and Bayesian networks
- Support the development of policies and procedures for AML transaction monitoring life cycle, including reviews of scenario validation, segmentation and optimization tools.
- Recommend customer segmentation and optimization for MUFG’s GFCD monitoring system across multiple lines of business.
- Develop KPIs/KRIs to measure surveillance effectiveness (e.g., hit rate, conversion rate, review time).
- Partner with Operations to balance alert volumes with investigative capacity.
- Identify opportunities to automate surveillance processes and reporting (e.g., dashboards using Tableau).
- Pilot advanced techniques such as: Machine learning–based anomaly detection and LLM-based data enrichment or pattern extraction
Candidate Profile
- Skills and knowledge
- Ability to apply mathematical principles or statistical approaches where needed to solve problems
- 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.
- Strong knowledge about model risk management and associated regulatory requirements
- Prior experience in designing compliance program tuning and configuration methodologies, including what-if detection scenario analytics, excess over threshold, and sampling ATL/BTL testing.
- Ability to code using R or Python for customer segmentation and data analytics preferred.
- Familiarity with vendor models like Hotscan, Actimize SAM/WLF, KX , Siron , Search Space, RDC, Bridger Insight, ACE Pelican, TCH OFAC Screening (EPN), FICO Credit/Debit, Guardian Analytics, and Threat Metrix.
- Ability to perform parameterization and threshold calibration of existing scenarios through analysis of underlying trades/orders/quotes data, alerts closure data, feedback from internal and external stakeholders
- Design new scenarios and/or modify existing scenario logics to enhance coverage, drawing lessons from enforcement cases, gap analyses of industry publications e.g., internal and external feedback
- Drive enhanced surveillance via enablement of automated monitoring via our monitoring system, fine-tuning filters, parameter thresholds to improve the quality of alerts generated
- Ability to implement customer segmentation using clustering algorithm for optimization of alert generation
- Experience in alert risk scoring project to risk rate the alerts generated in order to reduce false positives
- Ability to work with country teams to roll out customised anti-money laundering and fraud scenarios covering corporate banking and wealth management across thirteen countries in Asia Pacific region
- Ability to recommend and manage changes to thresholds deployed for all scenarios found on transaction monitoring systems
- Conceptualize and implement analytical solutions within the AML Transactions Monitoring framework or Trade Surveillance platform, including streamlining the detection scenarios review process and threshold optimization.
- Perform review and optimization on the Transaction Monitoring(Bank/Securities) or Trade Surveillance detection scenarios for efficient risk events
- Perform and Propose Segmentation and Rules for the implementation of the Transaction Monitoring in several countries.
- Strong understanding of Securities trading lifecycle (trade execution to settlement) or Market abuse typologies and AML risks.
- Knowledge of regulatory frameworks (e.g., MAR, SEC, FINRA, FATF guidance) preferred
- Proven experience in-
- Proposing a Threshold Tuning approach for countries with small number of active customers and Recommended thresholds for 7 scenarios in 13 countries in accordance with global risk guidance
- Reducing the time required for ATL Threshold Tuning by 70% by automating the process using SAS macros
- Enabling Volume optimization and Risk mitigation for one entire line of business by developing a Case Risk Scoring tool using logistic regression. This helps FIU in prioritizing focal entity review for SAR filing.
- Developing scenario simulator with 100% accuracy by coding the logic specified in the TSDs
- Conducting Initial Threshold settings for new scenarios for multiple countries
- Performing KPI driven tuning analysis for two regions by analyzing all the artefacts of transaction monitoring framework and Proposed recommendations for changes in thresholds/segments/scoring tools accordingly
- Performing extended Random Client analysis (eRCA) for monitoring the risk in Below-the-line region
- Working on Extended Segmentation Review that involves assessing the efficiency of existing customer segment to identify if any changes are required in the segmentation logic
- Education & professional qualifications
Bachelor's degree in statistics, mathematics, quantitative analysis, economics, computer science, data and technology Sciences or related fields is required. Advance degree a plus.
10-15 years’ experience designing, analyzing, testing and/or validating BSA/AML models, and/or OFAC sanctions screening models
5-10 years of experience in Trade surveillance, transaction monitoring, or market abuse detection or Securities operations or capital markets
Hands on experience with surveillance platforms such as Actimize, KX , NICE, Nasdaq SMARTS, or equivalent
Mitsubishi UFJ Financial Group (MUFG) is an equal opportunity employer. We view our employees as our key assets as they are fundamental to our long-term growth and success. MUFG is committed to hiring based on merit and organsational fit, regardless of race, religion or gender.
