Bank Cashes in on Better Services with Advanced Analytics
Faster development, continuous innovation, support for an advanced strategy
Financial institutions today need a variety of analytical models—risk models that predict the credit worthiness of loan applicants and assessment models that determine the value of assets. Models enable fast and accurate responses to loan applications—responses that include specific credit limits.
For this European bank, creating and updating its analytical models used to be a slow, labor-intensive process. "First, we designed what a model should look like, then we handed it to IT who started over, hand coding the model in our legacy systems," recalls the bank's first vice president. "It was a very long, manual process that did not meet the needs of the business or our customers."
The bank began looking for a solution to streamline its analytical model development and provide the advanced analytics it needed now and into the future. Its functional requirements and selection criteria included speed of implementation, ease of use, ability to integrate with existing systems, low total cost of ownership, and high quality of support. Based on those criteria, the bank chose TIBCO Statistica™ Data Science.
"Statistica Data Science met our functional requirements and much more," explains the VP. "It fit well into our platform and existing architecture. Users are very comfortable using it. For my part, I think the best part of Statistica is really good support. TIBCO delivered everything we needed."
Faster Analysis, Model Development in Half the Time
With Statistica, the bank now quickly develops and deploys statistical models to serve customers quickly and accurately. "My team uses Statistica to develop the models and put them into production on the front line," explains the head of model framework. "When a customer applies for a loan, our answer is based on those models, which consider data we get from the customer as well as from credit bureaus. The Statistica solution finds patterns in the data related to the customer's financial behavior, determines their credit worthiness, and predicts if they will default within a year."
"We reduced the time it takes to develop models by up to 50 percent," reports the VP. "Development is much leaner and smoother compared to what we had before."
Easy and Continuous Innovation
To keep up with market demands, such as increased demand for mobile banking, models need to change often. "We continually innovate to meet customer requirements," says the head of model framework. "Statistica predictive analytics is the foundation for meeting those demands. We easily customize the Statistica standard toolbox to meet our needs, and we constantly challenge and update our model portfolio."
Easy Response to Regulatory Requirements
"Since the financial crisis, there are many new requirements," says the VP. "Our models have been under increasing scrutiny, and we had to recalibrate all of them. In doing this, we definitely saw the benefits of the Statistica platform. It's so easy to use."
Advanced Analytics for an Advanced Strategy
"We can do more advanced modeling than we could before, which is a key part of our larger strategy that involves both structured and big data. We want to help customers better manage their finances through insight into their household economy," says the head of model framework. "Statistica predictive analytics supports the model framework to achieve this goal."
"We've built a lot of models, and make almost 20,000 calculations each day—and we need to build more. Models for putting processes on mobile devices, for gaining more insight into customer behavior, for automating more decisions. I'm confident the Statistica platform will scale to meet our needs."