It will be difficult to remember the last time we spoke to a real banker or visited the local branch for a transaction. Telephone conversations with the bank agent also happen rarely in today’s world. The days of operating physical branches with real workers to greet and service customers are increasingly being replaced. Modern mobile applications now allows for a customer friendly banking environment from making deposit checks on the phone, to applying for a loan and signing and closing documents electronically – in short, bringing banking to the fingertips. The need to go to an ATM is being eliminated gradually with mobile payment solutions like Apple Pay, PayTM and various mobile wallets. Banks and credit unions are changing their branch and customer channel strategies to meet the demands of the digitally savvy customer.
The shift to modern forms of banking is currently a dominating market trend and is developing as one of the strongest items in the CEO and CIO agenda in today’s banking industry. At the recent Asian Financial Services Congress 2015 in Singapore, the digital journey for the next generation bank was a major point for discussion. According to IDC Financial Insights, global banks will invest USD31.5 billion in core banking modernization to enable new digital services, improve operational efficiency, and position these banks to better compete on technology and convenience across markets. However, core banking modernization projects are often complex, costly, and fraught with risks and multiple levels of data management challenges.
Complexity: Most legacy core banking platforms are on average 15-20 years old, and even older for larger firms in established markets. In addition, many home-grown systems have had custom features added to them over the years to support new services, products, and deliver a competitive differentiation in the market. These systems are often inter-connected with other front, mid, and back office systems hence making the replacement drive a huge effort regardless of the size of the institution. Core banking replacement projects can often take years to complete and requires the ability to gain access to required data locked away in proprietary databases. Source data can often be cryptic to understand and migrating data that has to live in the new system has to be translated, transformed, and cleansed to ensure it is fit for use by the business.
Costly: The data migration and conversion processes of any core banking project is expensive. Converting legacy formats, mapping code tables from old to new, cleansing data quality errors, consolidating and conforming data values into the new system is a lengthy process. In many cases, there may be more than one core banking system to migrate for firms who have gone through mergers and acquisitions where those systems were left alone to run. The migration work required often involves an army of developers, business analysts, and operations teams who need to spend weeks if not months to figure out what data exist and determine where it needs to go from there. Unfortunately, most of that work and costs, in fact over 30% of the work associated with the USD31.5 billion in legacy modernization investments, will be tied to hand coding these processes using COBOL scripts, PL SQL, and other coding languages. This equates to USD9.45 billion in wasted IT spend versus adopting purpose-built tools to help automate the data migration, consolidation, and synchronization processes.
Risky: There can be many risks associated with large core banking modernization projects, including cost overruns caused by hand coding and delays in launching the new system which will be disruptive to business operations. One area of risk that is often ignored until the inevitable happens is the need to protect sensitive data during the testing and development process conducted by IT “off-shoring” or “in-sourcing”. Test data from legacy systems can contain Personally Identifiable Information (PII) and Non-Personally Identifiable Information. According to the latest regulatory rules in the United States, every breach of record will cost financial institutions USD194*. Though most banks do mask sensitive data used for testing, many resort to custom processes using scripts to mask sensitive data that often loses the relationships between data that is related or derived from each other. For example, masking a 16 digit credit card number is important however the BIN or first 6 digits needs to be equally masked with the same logic to allow banks to analyze the BIN and product descriptions for the credit card customers they serve.
In closing, the new era of digital banking is already here. Great data that is clean and safe for banks to use, can only happen by design. As banks replace their core banking systems to meet market needs, they will need to invest in the right data management solutions to avoid the cost of hand coding and the dire consequences associated with data breaches.
*2014 Ponemon Research Institute
The author is a Senior Director at Informatica’s department for Global Industry Marketing.