From CRM to CECL – Why Data Governance Is Imperative for Your Bank

Webinar Recording

2/20/2018

Key takeaways from the data governance in banking webinar

  • Data governance helps banks maintain and improve data quality.
  • There are seven key principles of data governance that enable banks to produce trustworthy data.
  • Implement data governance in banking in a series of structured steps to ensure success.

Data governance in banking

Data governance is the foundation of all data management services. In this on-demand webinar, Chris Sifter explains what banking data governance is and introduces root causes for data governance issues, critical use cases for data governance disciplines, and practical ways for your company to get started with implementing effective data governance in banking.

What is bank data governance?

Data is a critical asset to any organization. Because of that, there are protocols in place, referred to as data governance, to ensure that a company is able to effectively maintain and improve data quality. Data needs to be trusted, meaning there should be no question of whether the data is accurate, up to date, organized, and secure. Data governance in banking addresses all of these areas of concern.

Key principles of data governance for banks

Ultimately, data governance is all about being able to trust your data. There are seven principles for bank data governance that every company needs to abide by to ensure that their data is trustworthy:

  • Data is an asset
  • Data is shared
  • Data is accessible
  • There is accountability for quality
  • There is a common definition of data
  • There is clear data lineage in place
  • Data is secure and controlled

Implementing data governance in banking

Implementation of data governance should always focus on people, processes, and tools. It is important to examine an organization to identify any current data management issues before a data governance system can be put into place. Companies also need to look ahead to find potential future issues that can be avoided with proper data management practices.

It is important to establish an organizational structure prior to implementing data governance tools. Once that structure is in place, this roadmap of steps can help streamline the implementation of data governance:

  • Name the people in the organization that will be in control of data governance
  • List the organization’s priorities
  • Use those priorities to choose an endpoint, then determine what data is needed to get there
  • Create a roadmap for steps to reach the endpoint
  • Put that roadmap in place, only putting resources toward steps to reach the end goal

As you create your roadmap, be sure to establish measurements. Frequently evaluate the progress of implementation by using those measurements as a guide for any adjustments that need to be made.

Crowe data governance in banking

Contact Crowe today to learn more about how data governance in banking can make your data more trustworthy and your organization more efficient.