A company that purchases, securitizes and invests in the secondary mortgage market indirectly finances one out of every six homes in the United States. Since its inception, the company has financed more than 50 million homes. In recent years, as regulatory pressures increased, the company found that it was relying on outmoded technology and processes to attempt to meet real and immediate compliance requirements.
Like every publicly-traded company, this business has faced increasing Federal oversight in the wake of many high-profile corporate scandals. New regulatory requirements, such as the Sarbanes-Oxley (SOX) legislation, only added to the compliance burden in an already heavily-regulated industry. The company was particularly concerned with new quarterly and annual financial reporting requirements. To meet these regulations, the company decided to institute a proactive data governance initiative to ensure that it was operating from the best possible data.
In the past, separate lines of business within the company were individually responsible for their own data quality. Each unit would work directly with the corporate IT division, creating data quality rules, which would then be implemented on application or data source by IT. This process had a slow turnaround time, with changes to the rules taking weeks or months to be implemented. Plus, the business analysts who depended on the data had very little control over it.
The company saw a need for a faster, more efficient and more reliable means of managing data quality. With the stakes raised due to SOX and other legislation, the company needed a more robust, reliable enterprise data governance system. Seeking a system with faster implementation times that could produce more reliable data — and that would place control of data quality in the hands of business analysts — the company turned to DataFlux.
The company chose DataFlux technology to help it meets its compliance goals. Using DataFlux data profiling and data monitoring capabilities, the company’s business analysts were able to work separately from the IT department to develop their own business rules for data quality.
By profiling their data, the company was able to seek out and correct erroneous or duplicate data to ensure that their data governance initiatives focused on the most troublesome data sources. Through statistical and numeric range analysis, business analysts verified that key metrics, such as loan-to-value ratios or total unpaid balances, fell within acceptable ranges. Once the initial data profiling had been performed, analysts established these rules as ongoing data monitoring routines, which were then deployed as real-time services using the DataFlux Integration Server.
By ensuring that its Federally-mandated reporting was built on high-quality data, the company is now much more confident about its quarterly and annual financial reports. Instead of multiple divisions having separate data quality rules, the company now has one source for data governance rules across all applications and data sources.
Putting data quality in the hands of the business users allowed the company to reduce the time needed to implement data quality initiatives from weeks and months to a few hours. Business users – acting independently of IT – could analyze the data and establish real-time controls. With business users controlling data, the company also gained greater flexibility to respond to changes and meet challenges as they arose.
Furthermore, the company is now certain that it has the technology in place to be compliant with SOX. By making data governance an ongoing part of its operations, this mortgage company is prepared to meet changing regulatory obligations in the future.