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The Importance of Effective Data Governance for Banks

April 20, 2016
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With the pressures of changing regulations and data security continuing to increase, banks and credit unions must remain vigilant when it comes to their data. This is increasingly important in regards the FASB’s move to the current expected credit loss (CECL) model. Ensuring that data is of high quality, accessible and secure is key to keeping up with this changing environment. In addition, institutions should determine how they can make better use of the data already being collected.

A key topic that has been brought up by FASB, regulators, associations, and vendors is the need for loan-level data to more accurately project life of the loan loss estimate. A 2018 National Survey of Community Banks revealed that over half of bankers (56.3 percent) are in the data collection and analysis phase of their transition to CECL.

Preparing for a regulatory change like CECL is a great opportunity to improve data processes and procedures across the institution.

Learn more about navigating the CECL transition.

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An article by Crowe Horwath’s Mohammad Naser and Christopher Sifter, “Establishing Effective Data Governance in Your Bank,” highlighted some of the impacts facing institutions with poor data quality, access or security. Here are a few of the top impacts:

• Inability to deliver accurate forecasts
• Reduced productivity across the institution
• Exposure to risk and regulatory compliance issues, including inaccurate credit assessments and higher compliance costs
• Financial performance, including delays in cash flow, higher IT expenses and potential missed opportunities

To minimize those impacts, Naser and Sifter recommended three pillars to establish effective data governance.

Pillar 1: People and Organizational Structure
In the article, Naser and Sifter mention that everyone in the institution is responsible for “maintaining accurate, accessible and secure data in support of business needs and priorities.” They recommend dividing key stakeholders into two groups. The first group contains individuals responsible for establishing the vision and strategy for data governance, while the second is responsible for execution.

Pillar 2: Data Governance Processes
When institutions establish data management policies and procedures, it is recommended that all four phases of the data management life cycle are addressed.

1. Collection
2. Management
3. Protection
4. Delivery

Pillar 3: Data Governance Technology
For data governance to be effective, the institution must have the tools and technology to maintain and manage the data so it is accessible and reliable. Naser and Sifter mention that in many banks, “data technology consists of a disconnected series of one-off applications and solutions, each designed to meet a specific need, with no centralized and consistent governance.” Data platforms and frameworks should provide accountability and transparency, regardless of if they are internally-developed or from third-party vendors.

Overall, Naser and Sifter suggested an effective data governance program should include four critical criteria: trust, consistency, commitment, and clarity.

To learn more about data requirements for CECL, access the CECL Data Prep Guide.

About the Author


Raleigh, N.C.-based Sageworks, a leading provider of lending, credit risk, and portfolio risk software that enables banks and credit unions to efficiently grow and improve the borrower experience, was founded in 1998. Using its platform, Sageworks analyzed over 11.5 million loans, aggregated the corresponding loan data, and created the largest

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