2014-04-27 18:44:36 - According to the company, though the goal of data governance is to ensure the quality, availability, integrity, security, and crucially, the usability of data within an organisation; many banks today struggle in practice with traditional approaches to data governance.
Meta Byte Technologies, an execution-oriented, management and technology consulting firm based in Dubai, UAE, has said that there is an urgent growing need for data governance in banks in this region. The company states that banks today face a challenge in terms of organizational and regulatory changes. They are struggling to keep up with such changes and competitive market dynamics. Since they are built on data, data governance should be a critical business concern. They also have new ways of generating data and regularly add new data sources. Due to this, they frequently encounter a variety of data quality, accessibility and security challenges. This leads to a complete disconnect in between business and IT resulting in a lack of accountability.
Thus, banks need a comprehensive data governance structure and a well-executed strategy which can enable business to be accountable and IT to be agile and make informed decisions whilst efficiently responding to business changes with appropriate authorizations.
"Banks in the region have started realizing that the overwhelming amounts of data they are accumulating is unstructured in nature and have no insights in terms of where and who can access what. In order to gain these insights, the data needs to be transformed into information process that is comprehensive, consistent, correct and current. This challenge can very well be addressed through deployment of a data governance program that can allow banks to treat its data as a corporate asset by enforcing consistent definitions, rules, policies and procedures," explains Salil Dighe, the CEO of Meta Byte Technologies.
Over the past few months, Meta Byte Technologies has had dialogues with leading banks in the region. Through these interactions the company has been able to identify the worst practices and pitfalls banks need to avoid. “For one, data governance program is often perceived as just paying for Consultation services and adding employees to a governance committee. While that is a great first step, banks need to do more,” adds Dighe. “Banks need to create data definitions, business rules and KPIs to be used in their business processes, or they face not producing any business value from their data governance effort. Entitlements and compliance is then to be reviewed, with updates to these as and when the business needs change.”
The company clearly identified that the most prominent governance goal for Banks is the availability of reliable and accurate data for risk aggregation and reporting, including data accountability and traceability. They also find that although IT enables and reviews rules of Data Governance they are struggling to keep up with these processes manually. In addition, banks are realizing that data governance should not be an IT initiative. In order for a data governance program to be successful and sustainable, the mandate must come from the business, providing direction and steering the initiative, with IT objectives driving the plan for successful execution. IT then needs to have innovative approaches on how to reduce its own overhead and not be overwhelmed with business and helpdesk requests.
“We advise that organizations that are able to envision a disciplined data governance which encompasses people, processes, architecture and technology will be successful,” says Dighe. “Data governance should be automated within the corporate frame work,” says Dighe. ”Hence, Meta Byte Technologies uses its unique framework to work with banks in the region, in order to plan out a successful data governance strategy to help them draft a step-by-step approach to comply with their respective DG policies”.
Dighe concludes “It is helpful to visualize the data governance structure as a comprehensive framework that rests on four pillars: the collection, management, protection, and delivery of critical data. These four components will form the foundation for an effective data governance model for banks to reduce operational risk and costs, and improve controls and compliance, along with the ability to leverage data as a true critical asset and deliver real business value. "