The Credit Union Movement has been one of the slowest industries to adopt Big Data and Analytics and data warehouse solutions. The reason for this is many credit unions have failed to recognize the benefits Big Data and Analytics has on solving some of the industry’s biggest pain points. Identifying these pain points and their possible Big Data and Analytics solutions will help identify the true value of Big Data and Analytics. Here are three pain points and their Credit Union Big Data/Analytics solutions:
NCUA Reporting Requirements – Credit Unions are required to file several reports to comply with regulators such as a quarterly 5300 Call Report. The 5300 Call Report shows data regarding a credit union’s financial health and its results from operations. This data is then used by the Congress of the United States, banking authorities, researchers, and rating agencies. Consequently, these reports need to be filed on time with completely accurate information. This is so important that the NCUA has set penalties of up to $1 million per day for failing.
Preparing these reports for filing is no easy task as there is a plethora of information required such as income statements, charge-offs, balance sheets, securities, assets, liabilities, and a daunting list of other information. Much of the data required for reporting is scattered throughout disparate data sources that are individually and manually accessed at the credit union.
Solution – With the adoption of a Big Data and Analytics solution based on an integrated data warehouse, Call Report filing becomes a much less complex, automated process which results in lower costs and less time commitment. A data warehouse provides credit unions with the power to capture all the data required for NCUA reporting in one place, reducing the amount of labor hours needed. Data warehouses also decrease the chance of human error during the reporting process. Using multiple sources of data and manually compiling them into one source leaves a lot of room for error. With an automated process the risk for error is greatly minimized. In the case of reporting, data warehouses save credit unions numerous labor hours on a quarterly basis. It also protects them from incurring penalties by delivering the most accurate, timely information required by the NCUA.
Legacy IT Systems – Credit union growth often suffers as a result of processes maintained in legacy systems. Old, outdated technology is hard to get rid of and hinders productivity as employees are often confused by its content. Information systems relying on legacy systems have data spread throughout the organization in disparate silos. This paralyzes decision making because the immense amount of time and effort it takes to gather information. It also tempts credit union executives to make decisions without consulting the data, a process that leads to ill-advised choices.
Solution – Properly constructed data warehouses can rid credit unions of their legacy IT systems by integrating all disparate types of data into one source of truth. Historical member data that has been collected and locked in the tangled web of legacy systems will be unlocked for use in strategic decision making. Data warehouses enable effortless enterprise reporting and allow credit unions to eliminate many of the inefficient spreadsheets that consume employee time.
Maximizing Net Profit – Finding a healthy balance between maximizing profits and cutting costs is a pain point for every business. Credit unions are no exception. Should the credit union invest more or cut down its exposure to mobile banking, physical branches, employees, technology, etc? These decisions are difficult and part of the reason is the way credit unions leaders have been approaching them. Credit union leaders have been ignoring historical data locked up legacy systems and instead use their gut feelings. Ignoring data often results in errors and even minor errors can have major repercussions.
Solution – By gaining access to and taking control of their data, credit unions will be able to make profit maximizing decisions more swiftly and accurately. When faced with tough investment decisions, data can be leveraged to analyze past investment initiatives and trends to ensure the best decisions are made. This will result in greater profit as well as more satisfied members and employees.