Fico, the leading provider of analytics and decision management technology, announced that the Ferratum Group, the largest mobile microlending institution in Europe, will use Fico Model Builder 7.1 to develop more than 100 predictive models to support its growth in 15 countries over the next two years.
Headquartered in Helsinki, Ferratum provides short-term, unsecured microloans to borrowers across 15 countries, serving up to 1 million customers worldwide. Ferratum’s modelling team will use FICO Model Builder to build different models for different products and countries, and will explore creating models for different sales channels. The demand to build a high volume of models with a small team drove the selection process, in which FICO Model Builder beat products from SAS and other competitors.
“Our aim was to find a system that we can use to produce more than 100 models by the end of 2014,” said Marcus Siljander, risk manager at Ferratum Group. “We needed a system that is very fast and easy to use in order to minimise the need for a huge staff. FICO Model Builder gives us a common development approach with a well-structured process, which increases our speed of development while allowing us to keep our staff costs low. It also meets our requirement of using multiple modelling technologies. FICO Model Builder provides everything we need in a modelling tool now and for the future.”
“We are seeing tremendous momentum with FICO Model Builder, as analytic teams at companies like Ferratum look to build more models more frequently, without hiring more staff,” said Mike Gordon, FICO vice president and managing director for Europe, the Middle East and Africa. “More companies than ever are investing in predictive analytics, and for developing predictive models nothing beats FICO Model Builder.”
FICO Model Builder 7.1 combines industry breakthroughs in scorecard development functionality with a highly visual interface and 64-bit certification to solve very large modelling problems. Model Builder can reduce model deployment costs by as much as 75%, while shortening time-to-value and improving model ROI.