The financial industry deals with sensitive and confidential data, including customer information, financial transactions, and risk management data, which need to be properly governed to ensure regulatory compliance, data privacy, and security.
It is well-known that poor data governance can have significant financial implications for financial institutions. This includes errors in data reporting, which can result in fines from regulators and reputational damage. It can also result in operational inefficiencies and increased costs due to the need for manual intervention to correct errors. In extreme cases, bad data governance can lead to fraudulent activity or other criminal behavior.
According to a 2019 report by Gartner, poor data quality costs organizations an average of $15 million (USD) per year in losses, and that figure is likely to be much higher for banks due to the critical nature of their data. However, it is difficult to quantify the exact amount that banks lose yearly to bad data governance as the losses are often hidden and difficult to track.
In the financial industry, data governance is the set of policies, standards, controls, and procedures that are put in place to manage the collection, storage, use, and sharing of data within financial organizations.
8 Must-Haves for Effective Data Governance
Establish clear policies and standards for data management: Financial organizations should have clear policies, standards, and procedures for the collection, storage, use, and sharing of data. These policies should be aligned with regulatory requirements and industry best practices.
Assign data ownership and responsibility: It is essential to assign ownership (or stewardship) and responsibility for the management of data within the organization. This helps to ensure accountability and clear lines of communication.
Ensure data quality and accuracy: Financial organizations should have processes in place to ensure the accuracy, completeness, integrity, and consistency of the data they collect and use. This helps to reduce errors, improve decision-making, and increase efficiency. For example, a study by Experian Data Quality found that poor data quality can cost businesses up to 12% of their revenue.
Protect data privacy and security: Financial organizations must take steps to protect the privacy and security of the data they collect, store, and use. This includes implementing appropriate access controls, encryption, data masking (or obfuscation), and data backup and recovery processes.
Ensure regulatory compliance: Financial organizations must comply with regulatory requirements related to data management, including data retention, reporting, and disclosure. Failure to do so could result in huge fines. For example, fines of up to £17.5 million (GBP) under the UK GDPR and €20 million (EUR) under the EU GDPR, or 4% of annual global turnover can be issued to non-compliant institutions.
Establish a data architecture: Financial organizations should establish a data architecture that defines how data is structured, stored, and used across the organization. This includes defining data models, data flows, and data interfaces.
Establish data access controls: Financial organizations should implement access controls to ensure that only authorized individuals have access to sensitive data. This includes role-based access control, data masking, and data encryption.
Ensure metadata management: Financial organizations should manage metadata, which is data that describes other data. This includes defining data dictionaries, data lineage, and data ownership.
Benefits of Data Governance
Competitive advantage: Effective data governance can be a key differentiator, in the highly competitive financial industry. Financial institutions that are able to manage data effectively can make better decisions, reduce risk, and create new revenue streams, giving them a competitive advantage over their peers.
Enhanced compliance and better risk mitigation: Financial institutions are subject to numerous regulations and compliance requirements, such as KYC (Know Your Customer), AML (Anti Money Laundering), and GDPR (General Data Protection Regulation). Data governance helps ensure compliance by providing a framework for managing data privacy, security, and integrity. Financial institutions face numerous risks, including operational, credit, market, and reputational risks. Risk mitigation helps to identify and mitigate risks associated with data, such as data breaches and data loss. This can help financial institutions to reduce reputational risk and protect the interests of their customers.
Better collaboration: Data governance promotes collaboration across business units, functions, and third parties, enabling stakeholders to work together to manage data effectively. This can improve communication, reduce silos, and foster a culture of data-driven decision-making.
Increased efficiency: Data governance helps to streamline data management processes, reducing duplication of effort, and improving data integration. This leads to increased efficiency and productivity, as employees can spend less time managing data and more time analyzing it.
Improved decision-making: Data governance ensures that data is accurate and timely, which enables better decision-making. This, in turn, leads to improved business outcomes, such as increased revenue, reduced costs, and enhanced customer satisfaction.
Enhanced data security: Financial institutions hold sensitive customer data, such as personal and financial information. Data governance provides a framework for managing data security, including data access controls, data encryption, and data backup and recovery.
Improved data quality: Data governance helps to ensure that data is accurate, complete, consistent, and timely, which improves the quality of the data. This, in turn, leads to better decision-making and reduces the risk of errors and mistakes.
Facilitates digital transformation: In today's AI and digital age, financial institutions need to keep pace with new technologies and customer expectations. Data governance provides a framework for managing data as a strategic asset, enabling financial institutions to drive digital transformation initiatives.
Final Thoughts
Effective data governance in the financial industry is critical to managing the vast amounts of sensitive data that financial organizations collect and use. It requires a comprehensive approach that includes policies, procedures, and technology solutions to ensure that data is accurate, secure, and compliant with regulatory requirements.
In summary, data governance is essential in the financial industry, as it helps financial institutions to manage data as a strategic asset, comply with regulations, reduce risk, and drive business value.
Erisna is an enterprise data catalog and discovery platform that enables organizations and data teams to collaboratively get the most out of their data. Erisna platform helps organizations enforce effective data governance, increase efficiency, reduce compliance and regulatory risks, improve data quality, and have a competitive advantage over their peers. Create your Erisna account and request a demo today! www.erisna.com.