Banking Data Governance Training Course

Banking Data Governance Training Course

Introduction

Banking is undergoing a rapid digital transformation driven by Artificial Intelligence (AI), Data Governance, Data Quality, Regulatory Compliance, Digital Banking, Cloud Computing, Data Privacy, Risk Management, ESG Reporting, Real-Time Analytics, Data Security, Data Lineage, Data Architecture, and Master Data Management (MDM). Financial institutions generate massive volumes of structured and unstructured data across retail banking, corporate banking, digital payments, lending, treasury, fraud monitoring, and customer relationship management. Effective Banking Data Governance has become a strategic priority to ensure trusted, secure, compliant, and high-quality data that supports business intelligence, regulatory reporting, operational efficiency, and customer-centric innovation. 

Banking Data Governance Training Course equips professionals with practical knowledge and globally recognized best practices for designing, implementing, and sustaining enterprise-wide data governance programs. Participants will learn how to establish Data Governance Frameworks, Data Stewardship, Data Ownership, Metadata Management, Data Cataloging, Data Lineage, Data Quality Management, Data Security, Data Ethics, AI Governance, Cloud Data Governance, Regulatory Reporting, Data Risk Management, and Enterprise Data Strategy. Through real-world banking case studies, hands-on workshops, governance templates, and industry scenarios, participants will gain practical skills to transform data into a strategic business asset while ensuring regulatory compliance, operational excellence, cyber resilience, and digital innovation.

Course Duration

5 days

Course Objectives

By the end of this course, participants will be able to:

1. Understand the principles of Enterprise Banking Data Governance. 
2. Develop a Data Governance Framework aligned with global banking regulations. 
3. Implement BCBS 239 principles for effective risk data aggregation and reporting. 
4. Strengthen Data Quality Management using modern quality assessment techniques. 
5. Design effective Data Stewardship and Data Ownership Models. 
6. Implement Master Data Management (MDM) strategies across banking operations. 
7. Improve Metadata Management, Data Cataloging, and Data Lineage capabilities. 
8. Apply AI Governance and Responsible AI principles in banking analytics. 
9. Enhance Data Privacy, Cybersecurity, and Information Security Governance. 
10. Manage Cloud Data Governance for hybrid and multi-cloud banking environments. 
11. Develop Regulatory Reporting and Compliance Data Management strategies. 
12. Build Enterprise Data Risk Management and operational resilience capabilities. 
13. Create a sustainable Data Governance Roadmap supporting digital transformation and business growth. 

Target Audience

• Chief Data Officers (CDOs) 
• Chief Information Officers (CIOs) 
• Data Governance Managers 
• Risk Management Professionals 
• Compliance & Regulatory Officers 
• Data Architects and Data Engineers 
• Business Intelligence & Data Analytics Professionals 
• Banking Digital Transformation Leaders 

Course Modules

Module 1: Banking Data Governance Fundamentals

• Introduction to Banking Data Governance 
• Data Governance Principles and Frameworks 
• Banking Data Lifecycle Management 
• Data Governance Operating Model 
• Roles and Responsibilities 
• Case Study: Developing a Data Governance Framework for a multinational commercial bank.

Module 2: Banking Regulations and Compliance

• BCBS 239 Compliance 
• Basel III Data Requirements 
• AML/KYC Data Governance 
• GDPR and Data Privacy 
• Regulatory Reporting Best Practices 
• Case Study: Improving regulatory reporting accuracy through governance controls.

Module 3: Data Quality Management

• Data Quality Dimensions 
• Data Profiling Techniques 
• Data Cleansing Strategies 
• Data Validation Controls 
• Continuous Data Quality Monitoring 
• Case Study: Reducing loan processing errors using Data Quality Management.

Module 4: Metadata Management and Data Lineage

• Enterprise Metadata Management 
• Business Glossary Development 
• Data Catalog Implementation 
• End-to-End Data Lineage 
• Impact Analysis 
• Case Study: Implementing Data Lineage for financial reporting compliance.

Module 5: Master Data Management (MDM)

• Customer Master Data 
• Product Master Data 
• Reference Data Management 
• Data Integration 
• MDM Governance Framework 
• Case Study: Single Customer View implementation for digital banking.

Module 6: Data Security, Privacy and AI Governance

• Banking Data Security Framework 
• Data Privacy Compliance 
• Cybersecurity Governance 
• AI Governance Principles 
• Ethical AI in Banking 
• Case Study: Protecting customer data while deploying AI-powered credit scoring.

Module 7: Data Risk Management and Cloud Governance

• Data Risk Assessment 
• Operational Risk Data Governance 
• Cloud Data Governance 
• Third-Party Data Risk 
• Business Continuity and Data Resilience 
• Case Study: Governing cloud-based banking data platforms during digital transformation.

Module 8: Implementing Enterprise Data Governance

• Data Governance Roadmap 
• Governance KPIs and Metrics 
• Data Stewardship Program 
• Change Management 
• Continuous Improvement Framework 
• Case Study: Enterprise-wide Banking Data Governance implementation in a global financial institution.

Training Methodology

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.