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Data governance: Key to growth and risk mitigation in Banking
Banking Frontiers
|October 2016
Data has become the new currency.Businesses that learn to extract the right kind of information and harness it for competitive advantage will be profitable in the Data Economy.
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For this, it is imperative to have a holistic picture of all the data, so that it can be accurately analyzed to derive meaningful business insights. Banks offer numerous services to retail and corporate customers. While most Banks have successfully implemented Core Banking systems, there are still data silos. Sometimes, different systems are maintained for loans, mortgage, credit cards, savings accounts, NRI banking, investment banking, treasury, and the other services provided. It is shocking to note that often, customers are undefined, unknown, untracked and unmanaged.
Customers move and the continuity of their addresses evaporates. Combine that with complex profiles in which a customer is, at the same time, an individual, a corporation, a borrower and an investor - and consider how difficult it is to establish and track risk exposure, their financial activities and accountability. Factor in other critical elements required for maintaining capital requirements, providing for security, prevention of fraud, or accurately rendering consolidated post-acquisition financial statements, and the extent of the data challenge becomes obvious.
It sounds like complete chaos and discord. In a highly competitive banking environment, with strict regulations, improving governance, retaining customers and improving customer experience becomes a key imperative. If customer data is stored in separate, non-integrated repositories, how is a bank able to uniquely identify a customer and get a single view of all customer data? How can it offer personalized services without having a thorough understanding of customer profiles? And without a single consolidated view, how can a bank resolve customer disputes in a timely manner?
The solution to resolving this chaos lies in good data governance, achievable through a combination of best practices, specialized technology platforms, policies, and processes.
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