Anti-Financial Crime Name List Screening
- London, England, United Kingdom
- Permanent, Full time
- Deutsche Bank
- 15 Jan 18 2018-01-15
You'll be accountable for development, tuning and calibration of the name list screening program to ensure that Deutsche Bank maintains a pro-active and risk-based Name List Screening (NLS) program.
Job title: Anti-Financial Crime Name List Screening
Corporate title: Assistant Vice President
Division: Regulation, Compliance and Anti-Financial Crime
You'll be accountable for development, tuning and calibration of the name list screening program to ensure that Deutsche Bank maintains a pro-active and risk-based Name List Screening (NLS) program. A key component of the risk based Anti-Financial Crime (AFC) program is the use of sophisticated AFC models that enable Deutsche Bank to prevent and detect its products and services from being used in financial crime. You'll ensure screening models are effective through assessing the quality of data used in models, soundness of model design, model performance metrics and governance processes and will be responsible for assessing the overall completeness of AFC screening coverage.
- Gathering and documenting business requirements and assessing risk profile which includes definition of the risk being mitigated, historical data or performance from similar rules and solicitation of AFC Subject Matter Expert (SME) input, along with input from external sources
- Supporting the work to identify individual data elements required to execute screening models, examining the data available and collecting statistics and information about that data in order to identify data quality metrics, metadata
- Assessing data and data elements for timeliness, format, consistency, integrity and completeness
- Tracing the path of data from source to target environment to verify that data has been delivered in the correct format to the target environment
- Creating draft documents recording these steps to inform the Rule Configuration process
- Performing baseline tuning exercise pre-production deployment and creating a high level plan including resource identification and schedule
- Creating scripts to be used in System Integration Testing (SIT) / User Acceptance Testing (UAT)
- Performing system tuning and optimisation exercises to ensure screening processes are optimised. This will include Above-The-Line and Below-The-Line testing
- Performing sensitivity analysis and initial baseline configuration which includes executing test cases with tuning parameters and documenting the findings obtained
- Performing impact analysis based on the final configuration settings and documenting all the recommendations based on the analysis
- Executing and performing data mining and analysis to investigate where searches result in unexpected results (e.g. large number of hits created due to list or client changes, false positive analysis)
Skills & Qualifications:
- Excellent knowledge of name list screening systems particularly Fircosoft and / or Safe Banking System (SBS)
- Demonstrable experience in analytics platforms (SAS, R etc) for data mining and statistical analysis
- A strong experience in Financial Crime Compliance, Risk Assessment or Quality Assurance in Financial Services, Banking or Regulatory environment
- Excellent verbal and written English communication skills
- Ability to interpret complex requirements and be a self-starter
- Solid project management and work flow management skills (beneficial)
- Educated to Bachelor's degree level or above in Mathematics, Economics, Computer Science, Data Science, Management Information Systems, Information Management, or Statistics (or equivalent qualification / work experience)
- Good at creating and delivering impactful presentations
Please let us know if you require any adjustments to enable you to apply or attend an interview. If you would like to discuss your requirements, or have any concerns about the application process, please contact your recruiter.
Deutsche Bank is an equal opportunity employer who seeks to recruit and appoint the best available person for a job regardless of marital / civil partnership status, sex (including pregnancy), age, religion, belief, race, nationality and ethnic or national origin, colour, sexual orientation or disability.