Big Data Days 2019

 October 8-10   Moscow

Vladimir Bogdanovskiy

Home Credit Bank, Russia


Vladimir is the architect of the BigData platform at Home Credit Bank. He is responsible for the selection of technical solutions in terms of building and developing the platform based on the business objectives. He has experience in foreign projects related to the processing of Big Data for various purposes: analysis of users on the Internet and telecom, analysis of current events in real time, prediction of the performance of various systems. More than 10 years ago, he took an active part in the construction of one of the first highly loaded systems for online car monitoring, which is now successfully functioning.


Home Credit: Our Road to Data Driven

Every modern bank faces big challenges: the rapid growth in the number of transactions, together with the desire to meet the growing needs of customers in high-quality and fast service, makes us take a different look at the processes of working with data. There is a number of tasks in which Big Data is actively used to achieve the maximum business result is growing. This leads to an avalanche-like increase in the volume of stored and processed information. The database of knowledge and patterns collected by the bank allows you to make both operational and strategic decisions as efficiently as possible. Therefore, the data comes to the fore for determining priority tasks aimed at solving business goals through the generation of ideas and hypotheses with confirmation of their correctness based on the figures obtained. We set ourselves the goal of collecting all possible data about our customers in one place – the BigData platform, which currently collects and processes information about current and future customers in real time, provides a single data access interface, and also contains a “sandbox” for data analysis. In terms of platform development, we consider the tasks of constructing an analytical repository, calculating various metrics in real time, ensuring transactional operations and data consistency. We want to predict the needs and possible problems of our and future customers, offer them the highest quality and operational service, introducing more and more business scenarios that are solved using Big Data.

Session Keywords

Big Data
Data Lake