B&N Bank

“OLAP-cubes, visuals, clustering and forecasting algorithms, association rules methods, it's all connected and available for users at one place, one web page. That makes process of finding insights comfortable. In Polymatica smart data discovery, exploration of big data volumes do not require building models or writing algorithms.”
Pavel Kravchenko, CIO B&N Bank Digital

B&n bank

B&N Bank is one of Russia’s top five banks, with the country’s fastest-growing digital banking business and millions of customers.

The challenge

The digital banking department wanted to maintain required levels of credit, while increasing sales efficiency for digital products, credit usage, new client acquisition and retention. The best way to achieve this was to create an online communication process whenever a customer used their credit card.

Why Polymatica?

To carry on using their existing solution, particularly with the need for customisation, was going to be extremely costly. The bank wanted a modern solution to support online operations with high volumes of data, smart data discovery and advanced analytics capabilities. A direct connection to the data source was also essential. They chose Polymatica as the best fit.

The solution

Full implementation took less than three weeks, including preparing the virtual server, system set up, and connecting to data sources, plus creating cubes and some functional validation. Building Polymatica into B&N Bank’s existing IT infrastructure required no changes – in fact, the architecture was simplified.

Business benefits

Rise conversion rates up to 34%

Improved customer targeting and quality of communication led to a rise in conversion rates to 34%, so all marketing communications are now profitable

Increased speed to market for new products

The length of the analytical cycle changed from several weeks to just a few hours, while speed to market increased 30 times for new services and products

Growth of citizen data scientists

Polymatica has become a tool for everyone, so there’s less need for high profile specialists to perform the same analytical routines.