A Bank is an Information Enterprise
Data is one of the most valuable assets a bank has, and it needs to be managed and maintained consistently across the entire bank. A recent study found that banks who effectively manage their data can increase their Net Interest Income (NII) by 10-20% through more precise decision making, better capital management and improved product pricing.
Having high quality governed data is a key to successful banking. Almost all decisions regarding profitability, capital, liquidity, pricing, compliance, customer service and risk management are based on data driven analytics and reporting.
However, often banks have data problems such as
Missing or incorrect data resulting in limited ability to perform meaningful analysis and forecasts.
Not being able to quickly and accurately evaluate opportunities for organic growth, mergers, and acquisitions.
Difficulty in responding to regulatory matters because of missing or difficult to find data
Data exist in silos throughout the organization and there is no single source of truth.
Too much time and effort are spent on gathering data, reconciling, and analyzing data.
Regulators Recognize Data is a Key Banking Asset
Banking regulators understand the importance of governing data. Specific regulations such as New York’s DFS504, BCBS239, FATCA, CCAR and CECL all emphasize the need for a stronger Data Quality & Governance Program. The large banks put a great deal of emphasis on getting their data right. Regulators are also recognizing the need for banks of all sizes to get their data right, especially when banks are seeking to grow through acquisition or merger.
How to Establish a Governance Program
The keys to establishing an effective Governance Program and increase the value of data as an asset include:
Establishing organizational accountability and responsibility (e.g., business vs IT, policies, standards, data quality, metadata, risk management, and regulatory compliance)
Addressing data issues methodically and consistently, ensuring that issues are reviewed, resolved and have visibility to leadership.
Establishing a governed common enterprise data environment for use of all parts of the organization.
We have found that there are seven essential steps to establishing an effective Enterprise Governance Program:
Executive Sponsorship is required to ensure success of DG program. Funding, policies, oversight and program review and measurement are key to establishing a successful program. Many banks have established a Chief Data Officer (CDO) role as the key executive function to lead and guide the data shared service. Another article will cover the role and reporting function of the CDO.
Assessing Organizational Data Governance Maturity level is a measure of where the bank’s current data governance capabilities measured against industry best practices.
Vision and Strategy document the approach to enterprise data governance.
Target Operating Model is an important tool used to show visually the implementation components work together (e.g., policies, business strategy, business processes, training, domain implementation, reports, metrics, roles and responsibilities, scorecards, and roadmap).
Oversight is the data governance structure that prioritizes and addresses escalated data issues impacting quality, security, solutions, etc. and provides management oversight and best practices to ensure data is managed as an asset across the bank.
Operating Procedures are playbooks for data governance stakeholders to use to ensure data governance processes and procedures are executed consistently across the data governance team and are aligned to data governance vision, strategy, and roadmap.
KPIs and Metrics are used to measure the effectiveness of the DG processes and its components (e.g., policies, data quality, metadata, stewardship, etc.).
Benefits of an Enterprise Governance Program
There are multiple benefits that come from having a successful Data Governance Program:
Data is trustworthy. Stakeholders feel they can trust that the data that is collected and made available for operations, and regulatory compliance is accurate because there is quality in data.
Data is consistent. Data is uniform across the enterprise and business stakeholders have access to data they need to meet their business requirements and priorities.
Data has ownership. Users know who to go to when they have questions or issues with data, in other words, data has accountability. .
Data policies and standards are established. Policies and standards establish a president on the management and governance of critical data and data assets.
Better decision making. Governed data is more discoverable, making it easier to find useful insights.
Improved data understanding and lineage. Data governance tools provide a comprehensive view of critical data along the data lifecycle showing the who, what, where, why, when and how of data.
KPIs and metrics. Data Governance KPI and metrics demonstrate a return on investment by showing data value and insights on quality issues.
Getting Started with a Governance Program
The first place to start is to perform a Strategic Data Assessment. In the Strategic Data Assessment, the firm will take inventory of your data management and governance policies, understand your data pain points, what is causing you the most concern about your data, identify what data is critical to the business, and know your company’s business goals. At FinResults we have the methods, experience and tools to help you implement an effective Enterprise Data Quality & Governance Program and to perform the Strategic Data Assessment.
FinResults is an innovation partner for banks, founded by bankers with years of digital and data management implementation experience. We can bring not only experience but also the technical resources, agile implementation, experience with digital transformation and advanced data environments to help your bank be successful with its transformation initiatives.
For Further Information
For more information, please contact us at info@finresults.com or +1 (561) 288-6548.
About the Authors of this Article Tangie Louis, Data Governance Principal at FinResults, Inc. Tangie has over 20+ years’ experience in data management. She is a data governance Subject Matter Expert (SME) who works with clients to customize and develop data governance strategies, programs, organization structures, data governance council, and roadmaps. Tangie can be reached via email at tangie.louis@finresults.com Denis Kosar is a Data Governance Principal at FinResults, Inc. Denis specializes in data governance readiness assessments, establishment of data governance, as well as education and training within the financial services industry. He has over 30 years experience in banking, brokerage, and insurance. He is a longtime President of the Data Management Association of New York City where he directs the organization to provide professional training and education to their data management membership. Denis can be reached via email at denis.kosar@finresults.com. Michael Andrud, President of FinResults, Inc.. Michael has been a midsized bank Chief Information Officer, a large bank Chief Data Officer and head of the data practice for a large consultancy. Michael can be reached via email at michael.andrud@finresults.com or at +1 (561) 288-6548.
FinResults is a consulting and technology professional services firm located in Boca Raton, FL, focused on helping small and midsized companies succeed with digital, data and process transformation.