One of the largest banks in the Southeast US has more than $100 billion in both loans and deposits. The bank has offices in 11 states and prides itself on a decentralized management structure that puts business decisions in the hands of local executives.
Like any financial services institution, having timely, accurate data was essential to the company’s performance, stability, and profitability. Because of the increasingly competitive nature of the business, and the continually shifting financial landscape, the bank knew that having the most accurate data meant having a real competitive advantage.
Although decision-making was decentralized throughout the company, the bank’s corporate headquarters still needed to create credit risk management reports that would allow those local decisions to be consistent with corporate goals and objectives for the entire company. This would ensure that executives at the bank’s 50 units would have the information they needed to approach each decision with an eye towards understanding how much lending risk they could assume.
A credit risk unit provided oversight of this process. Periodically, the unit would have to divert from other urgent business and spend days manually compiling data from multiple sources into spreadsheets for analysis and reporting. Using this labor-intensive process, it would routinely take three weeks to compile a single risk management report, meaning that the report could easily be out of date by the time it was completed.
Furthermore, because this manual process was error-prone and difficult to verify, the organization had little or no confidence in the validity of the reports that they were creating, even after spending a significant amount in bringing in an external consulting firm to assist with creating the reports.
The bank chose DataFlux technology to review and compare multiple data sources simultaneously through data quality and data integration workflows. The bank created a set of business logic rules and applying these rules to the data that the bank collects from all its lending units. DataFlux offers graphical workflow tools and a powerful, intuitive interface to give high-level data quality and data integration capabilities to business users. Analysts in the credit risk units could automate their accumulated business rules and create a better mechanism for inspecting and correcting data.
With DataFlux technology, the bank’s staff automated the process for calculating and recalculating risk ratios in various loan sub-categories on a nearly continual basis. At the same time, the system could alert users when credit risk exceeds appropriate levels.
Through its data monitoring capabilities, dfPower Studio can generate automated email alerts when a potential loan is outside the bank’s lending parameters. Feedback on credit risk, once an arduous and latent process, became an ongoing piece of the company’s IT infrastructure.
With DataFlux technology, it takes hours – not weeks – to calculate risk ratios. For the first time, the bank’s credit risk group feels confident in the reports it is producing due to higher levels of data quality – and the ability to monitor acceptable levels of data quality over time.
The technology is currently used by 10 analysts (with plans to increase that number to 25) who do not have programming skills. Further, the group is freeing itself from dependence on expensive consultants, helping the company realize an impressive ROI from the initial deployment.