Regulators are unarguably the primary force behind the growing adoption of XBRL by the banking industry, evident from the initiatives of different bodies, such as the Federal Deposit Insurance Corporation in the U.S., Committee of European Banking Supervisors in the E.U., and the Reserve Bank of India, to name a few. Yet, the idea of using XBRL for internal data management and processing is still largely unexplored. XBRL could potentially find application in several areas within banking organizations, since it is ideally suited to facilitating the exchange, processing or consumption of information by rendering the data system readable, standardized and interoperable. Needless to say, the sooner that banks explore XBRL, the more effectively they can economize their processes.
Let us look at some important operational scenarios where XBRL could play a role.
XBRL enables banks to define the required granularity of data. Once mapped with a unique XBRL tag, the data can be identified during all the stages of a loan life cycle. It would be possible for a customer to provide all loan related documentation, presently submitted in unstructured form, as XBRL data, which can be easily consumed by the banks’ backend systems. Thus, a majority of the steps involved in the loan life cycle become automated and error free.
Enabled with an XBRL-supported report generator tool, the bank can generate reports based on any data cube or parameter at any time. The bank also has the choice of broadcasting the data online (as HTML) or printing it out as documents in MS Excel, MS Word, PDF and other formats, since XBRL is format agnostic. Leveraging XBRL GL, the final reports can be generated from trial balances, ledgers or transactions, with provisions for adjustments, annotations and additional information. Consolidation of data from various branches, departments or even subsidiaries can be automated based on the business rules defined.
As banks move from a product-centric to segment-centric to customer-centric approach to account centric approach they must understand their customers better in order to sustain competitive advantage. An XBRL-enabled analytical application can talk to the source systems within banks, which also have the taxonomy tagged to the relevant fields. The scope of the analytics that can be carried out is immense.
Having considered the relevant use cases, banks may choose to implement XBRL in one of three ways. Taking a big bang approach would achieve the desired result of straight through reporting; however, success would largely depend on the bank’s readiness and adoption of technology. Another approach could be phased implementation. Banks can draw up a plan to adopt XBRL internally in a step-by-step manner, starting with a few departments before moving on to the rest. This is quite useful when various departments in the bank are using diverse applications. Banks could also peg their level of XBRL adoption to that of the regulators. For instance, in India, the adoption could be in sync with the returns specified by the Reserve Bank of India under the XBRL mandate.