Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK

A data-driven journey to customer-centric banking

Data-driven business management
Location: Capital Suite 4 Level: Beginner
Average rating: ***..
(3.60, 5 ratings)

TBC Bank is the largest bank in Georgia, with around 40% market share for loans and deposits. Over the last three years, TBC Bank has transitioned from a product-centric approach to a client-centric one, which has included the development of advanced customer analytics. The ultimate goal is to have up-to-date analytical information readily available for all systems and in all channels at all times.

Mikheil Nadareishvili discusses this transition and explains how the company implemented an integrated 360-degree view of customer and advanced analytics. To enable all this, TBC broke down data silos and moved to a single, strictly quality-controlled data lake, created various predictive models and segmentation algorithms and operationalized them, created a data science layer in the organization, which acts not only as a passive support for business but as an idea generator as well, and worked closely with business to promote a data-driven, evidence-based approach to decision making. This system also includes cross-sell, up-sell, churn, and default scores, next-best offer calculated by different goals (to retain customers, the largest profit, to meet sales targets, etc.), and segmentation by spending habits, product holding, etc. The analytical information is then used to create personalized service to clients. Mikheil concludes by discussing the measurable impact the transition has had on sales and customer experience and plans to build on current results.

Photo of Mikheil Nadareishvili

Mikheil Nadareishvili

TBC Bank

Mikheil Nadareishvili is deputy head of BI at TBC Bank, in charge of company-wide data science initiative. His main responsibilities include overseeing development of data science capability and embedding it in business to achieve maximum business value. Previously, Mikheil applied data science to various domains, most notably real estate (to determine housing market trends and predict real estate prices) and education (to determine factors that influence students’ educational attainment in Georgia).