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Can XBRL ease big data headache?

Banks led the way in standardizing data collection, retrieval

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  • Written by  Richard Jones
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Can XBRL ease big data headache?

Too much of a good thing can be bad for you, and this is especially true when it comes to data. Companies, particularly banks, have a wealth of information at their fingertips, but until recently they lacked a basic method to harness this data and put it to better use.

The Securities and Exchange Commission recognized this untapped potential and, in 2009, mandated that all publicly held companies disclose their financial information using eXtensible Business Reporting Language (XBRL)—a standardized method of data collection and reporting. XBRL could facilitate more accurate comparisons across companies to improve business performance, investment analysis, and decision-making. However, to this point, most companies see the XBRL mandate as a compliance headache rather than a value-added tool for analysis. An exception is the banking industry, which presents an excellent example of how XBRL can ease the big data headache through the creation of high quality, consistent data.

The Federal Financial Institutions Examination Council (FFIEC) started the Call Report Modernization project in 2005. This project requires banks to collect, validate, manage, and distribute structured data into a central data repository (CDR) that federal regulators and the public can access. The FFIEC agencies were quick to adopt XBRL before many of the SEC industry mandates were enacted, and its members understood the value of incorporating the new standard data format at the introduction of the reporting process rather than waiting until the end and attempting to “fit” the data into XBRL. This decision not only streamlined the XBRL tagging process, it substantially increased the quality of the reported data and facilitated a real-time analysis of the data as it was processed. These organizations were also the first U.S. groups to build a CDR and introduce a large-scale solution based on the premise of structured XBRL data, better quality, and more timely reporting. It was, in part, the success of the banking regulators that helped to push the SEC (and other regulators) toward the industry XBRL mandates we see today.

This wouldn’t have been possible if the FFIEC hadn’t had the foresight to educate banks, software vendors, and the related regulators on ways they could improve efficiency, transparency, quality, and cost saving through the use XBRL data. Because standardized data is universally comparable, banks can more quickly express complex formulas and have that data immediately usable for analysis. 

The FFIEC’s use of XBRL to assist with the management and governance of the vast amounts of data being transferred between the operating entities, was directed toward their goals to avoid much of the manual entry and effort, to programmatically detect variations in data, and to identify substantial inefficiencies when confronted with big data. Their success can be demonstrated simply by reflecting on the state of data after the XBRL “Call Report” project, where it’s reported that 95% of bank data is considered clean before it is submitted by the banks. This success was substantially attributed to the FDIC’s roles in the implementation of XBRL formulas, for use with the Call Reports, which allowed for the ‘hands free’ ability for the identification of data anomalies.

Noteworthy is that during the early implementation meetings, banks expressed concern as to how they’d learn XBRL. By including software vendors, who wrote the reporting software, at the start of the project, these organizations created an environment where the banks were oblivious to XBRL efforts; they would just realize the benefits.

Today, banks and their regulatory bodies are drowning in data, leading to issues with long processing times, error reconciliation, re-work, speed to market, and data analysis, among others, but XBRL continues to prove its potential. By using a standardized reporting language and process, business leaders can base more decisions on meaningful data, which leads to improved risk management. It also saves time on data collation, allowing for quick action to be taken. Banks see faster recertifications, have fewer flawed data records, and have reduced their processing times when creating and managing the information required for regulators. Regulators also take advantage of the more consistent, accurate, and comparable data by realizing a reduction of their operating expenses and time spent on pre-XBRL corrective action.

The banking industry has been a sterling example of how XBRL can reduce the time and money spent on internal operations, improve the decision-making and reporting processes and help manage overall risk. When it comes to the big data headache, XBRL is the remedy you need.

Richard Jones is the senior vice president of operations at RR Donnelley’s Financial Services Division. Prior to this role, he served in a similar capacity for EDGAR Online and as vice president of Operations at Financial Insight Systems.

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