Data Governance in Financial Services & the Impact of Global Regulation
Driven by the massive increase in the global regulatory environment, Data Governance in Financial Services & the Impact of Global Regulation is a comprehensive non-technical review of the key terms, concepts, functions, roles and the importance of Data Governance and Data Management at Banks/Financial Services firms as the seek to meet the requirements of major regulations such as BSA/AML/KYC; Dodd-Frank/CCAR, Basel III/BCBS 239.
Heavily focused on Risk Management and Compliance, financial services firms have realized the critically of managing data as a “corporate asset" and the imperative for establishing enterprise-wide data programs and governance organizations. This course will explore the key responsibilities of a data governance organization; the role of the Chief Data Officer (CDO); the basic data management functions; what Regulators expect and why.
This course is best suited for participants with:
- General knowledge and understanding of banking products (e.g. Loans, Deposits, Mortgages, Payments, etc.).
- Basic understanding of the Risk, Finance and Compliance functions at financial institutions, what they do, how they do it.
- Some familiarity with the major regulations impacting banks/financial services firms (e.g. BSA/AML; Dodd-Frank Act).
Module 1: Data Governance & Data Management – Definition and Importance
- The Definition of Data Governance, Data Management; how they differ from Information Technology (IT)
- Why most financial services firms are launching “enterprise” data programs; establishing data governance organizations; hiring experienced professionals
- So many “data” terms in the marketplace; the basic “definitions” and what you need to know (e.g. Big Data, Master Data, Data Lineage, Data Profiling, Data Transformation, Metadata, Data Science, Data Architecture, Key Data Indicators, and many more.)
- Examples of how major firms are embracing Data Governance, Data Management
Module 2: Data Impact of Major Global Regulations
- Overview of the most significant financial services regulations that necessitate Data Governance:
- Bank Secrecy Act (BSA) /Anti-Money Laundering (AML)/Know Your Customer (KYC)
- Dodd-Frank Act Stress Testing (DFAST)/Comprehensive Capital Analysis and Review (CCAR)/ Enhanced Prudential Standards (EPS)
- Basel III (Basel Committee on Banking Supervision)/ Principles for effective Risk Data Aggregation & Risk Reporting (BCBS 239)
- EU Revised Payment Services Directive (PSD2)/Revised Markets in Financial Instruments Directive (MiFID2)
- Role and importance of Data Governance in meeting regulatory requirements; what is a G-SIF, D-SIF, IHC, FBO
- How Regulators measure and monitor compliance; what is an MRA, MRIA; examples
Module 3: Data Governance - Organization; Basic Functions; Roles & Responsibilities
- Major components of a typical Enterprise Data Governance Program
- How Data Governance is typically aligned and managed organizationally
- Basic functions performed by Data Governance
- Major roles and responsibilities (e.g. Chief Data Officer (CDO); Head of Data Governance; Data Owners, Data Stewards and Data Custodians)
- Example of Data Governance in action
Module 4: Key Concepts of Data Management – Data Quality; Remediation; Lineage; etc.
- Typical responsibilities of Data Management defined:
- Data Standards - Measuring and monitoring compliance
- Data Quality - How data quality improvement is achieved, measured, reported
- Data Remediation – Different types of data “cleanup” projects; expectations, tracking results
- Issue Management & Resolution – The basics of setting up an issue tracking process; reporting on resolution
- Data Lineage - Defined; why it is so important to understand, a basic example
- Metadata Management – A simple definition; how it is implemented and why
- How Data Management progress/issues/results are reported to Management, Board, Regulators, etc.
Module 5: Practical Do’s & Don’ts of Implementing Data Management & Governance
- Do - Ensure proper organizational alignment, commitment, resources
- Do – Start with a comprehensive Current State Assessment
- What to look for in a Current State Assessment
- 3rd Party Assessment Methodologies
- Don’t - The top 10 mistakes when implementing a Data Governance program
- Why tools (i.e. new systems) alone are not sufficient for a successful program