Data governance within financial services institutions has largely been guided by regulations. Motivations for governance programs have centered around not running afoul of regulations as opposed to extracting business value or improving operational efficiency. Although not determinative, regulators have considerable influence over the activities and initiatives pursued by organizations.
Historically, many financial institutions leveraged a mixture of teams, including consolidated and report specific,to manage data sets and the production of reports. Invariably, this has led to “turf wars” concerning ownership and management of data, general accountability, how data is used, who is responsible for quality assurance, etc. In short, people are managing data and creating reports in siloed worlds to make decisions.
Managing disparate data across an organization can be daunting. Regulators require the tracking and management of countless data points. Organizations must ask themselves
“How are we going to derive value out
of the management of this data”
Traditionally, organizations have used a centralized group to manage data. However, this approach has typically not been effective due to: