How to Ensure You Meet Your Financial Institution’s Regulatory Needs
Financial institutions collect a wealth of information about their customers. But while most banks have systems to store compliance-required information, many of them lack the necessary infrastructure that would enable them to access that information when needed. Digging up data and building reports are often manual, time consuming tasks. Most of the time, data just sits around in warehouses with no hope for ever being used.
If you don’t have easy access to your data, how do you determine if it’s accurate or still relevant? This is a question that financial institutions must think about, as duplicate, expired, or inaccurate data can lurk unnoticed for many years in a data warehouse. Even if you implement data quality practices to prevent bad data from entering your organization, like address or telephone verification, without a full data management program you have little defense against expired data.
Coming out of the financial crisis of 2008, many of the regulations that were applied to the financial industry have a similar objective: to increase the transparency of organizations’ data, in order to monitor and prevent risky decision-making. And good data management is at the heart of this objective. Without a proper data management strategy in place, financial institutions will struggle to deliver the true transparency that regulators require. For financial institutions, bad data can result in hefty fines from regulators and possible litigation, depending on the severity of the infraction.
Many banks attempt to meet burgeoning compliance standards by investing in additional resources and personnel. However, years of shadow IT based data management practices have created data silos that make it hard to compare information across systems. Many financial institutions, including the global and/or domestic systemically important banks (GSIBs/DSIBs) and smaller firms, have legacy systems that need to be modernized to make their data readily available to regulators. In order to meet constantly evolving regulatory requirements, your company needs to be proactive about governing information and managing risks.
The Importance of Information Governance
An organization can have hundreds or even thousands of different systems. Information can come from many places — such as transactions, operations, document repositories and external information sources — and in many formats, including data, content and streaming information. There are often meaningful relationships among the data, wherever it originates.
Unlike a traditional supply chain, an information supply chain has a many-to-many relationship. For example, data about the same person can come from many places — that person may be a customer, an employee and a partner — and the information can end up in many reports and applications. As well, various systems may define the same information differently.
Given this complexity, integrating information, ensuring its quality and interpreting it correctly are crucial tasks that enable organizations to use the information for making effective business decisions. Information must be transformed into a trusted asset and governed to maintain quality over its lifecycle.
An Information Governance Framework
The people, processes, policies, and technology should all combine to create a program where the use of information enables an agile execution of projects. The method of execution is assessed using an information governance framework and method the consistency and supports of the program. Figure 2 depicts the Information Governance Framework Wheel.
Following are key data, and other, initiatives an enterprise data approach toward financial regulatory reporting would require:
- Policies for Metadata define
- Governance Rules
- Data Standards and Metadata:
- Business Terms defined in a Glossary
- Categories within a Glossary
- Data Architecture
- Source, Data Lake Logical Data Model(s)
- Source, Data Lake Physical Data Model(s)
- Data Quality Management
- Data Trace-ability/Lineage
- Workflow Business Processes
- Governance Dashboard
- Organizational Model Implementation Along with Roles and Responsibility
- Change Management
