Precision and accuracy are two vitally important characteristics that contribute to the viability of financial service organizations. Small errors cannot be tolerated and minor mistakes can quickly become extremely expensive. Sliding that little decimal point over just one place to the right changes things drastically. A simple blunder can be seen as a windfall or a disaster depending on which side you are on.
Who wouldn’t like a rebate check that was an order of magnitude greater than expected? Especially if when you called the organization responsible for the mistake to question it you were assured that their records show it is correct. So I guess that means you can keep it? Of course, a similar error in the other direction would not be appreciated.
In both cases, a lot of money can be at stake over very small errors made by financial services companies.
This is a minor example of the types of errors that can occur in the financial services sector. More egregious problems result from mishandling the sensitive and personal information that financial organizations store regarding their customers.
A data breach at a credit card company or bank can expose information on millions of individuals. A case in point is the March 2017 Equifax data breach in which hundreds of millions of records were stolen by hackers who were active in the company’s network for 76 days before being discovered. The repercussions of the compromised data were felt by the company and its customers long after the specific issue was resolved.
Data governance is essential for financial services, helping to safeguard valuable data assets while enabling their effective use across the organization. This article explores the significance, benefits, and specific challenges of data governance in the financial sector.
In the interest of implementing better safeguards on data resources, many organizations have turned to the concept of data governance. Having an organizational-wide understanding of the information contained in corporate databases is a critical factor in designing the framework necessary to keep it secure.
Confusion over data definitions that can propagate from a siloed perspective is a disaster waiting to happen.
A robust data governance program allows the whole enterprise to treat data in the same way and greatly reduces the probability of mistakes that can lead to a data breach. It breaks down the silos that exist between departments and allows everyone in the organization to be on the same page regarding enterprise data resources.
This enables the information to be used more productively and protected more effectively.
Financial services organizations have to deal with some specific industry trends that make it even more important to institute comprehensive data governance.
Strategic demand is rising for relevant customer data that can be used for analytics and data mining. The goal is to develop marketing and customer retention strategies that require accurate and integrated data resources.
Productive use of this customer data can spell the difference between a successful launch of a new product or its dismal failure.
Trustworthy data is required by new and existing regulatory standards. Financial institutions in the United States have to comply with complex requirements such as the Dodd-Frank Wall Street Reform and Consumer Protection Act and the Bank Secrecy Act.
This is in addition to maintaining compliance with regulations concerning the protection of personal data mandated by the GDPR and other related legislation.
Incorporating new technologies and mobile data streams can affect data quality. The financial industry is moving toward using more smartphone apps and allowing customers to directly input data that previously had to be vetted by bank employees.
Securing these data channels and the veracity of the information obtained through them requires data management strategies that can be enacted through data governance.
Developing and implementing data governance is not a trivial exercise. It needs to be done in a structured manner to be successful and needs all parts of an organization to be on board. Defining the common language around data assets that drives a governance program is a necessary first step in the process.
This is a collaborative effort that demands the use of the right technologies and tools for effective implementation.
IDERA’s ER/Studio Enterprise Edition is the perfect tool for developing the foundational data language that a governance program demands. It enables teams throughout the organization to share data models and metadata from a central repository, eliminating sources of confusion that can percolate through processes and procedures.
The tool facilitates the creation of naming standards, data dictionaries, and global business glossaries to maintain data consistency across an enterprise.
ER/Studio can help any organization implement data governance to assist in taking better care of their data assets. As the importance of enterprise data resources continues to grow, using them effectively and securely will need to be addressed by businesses in all market sectors.
The potential for catastrophic errors makes the financial services industry a prime candidate for strong data governance policies.
