Who are we
WE ARE A BIG DATA AND CREDIT SCORING
Retail lending is one of the most popular and prioritized businesses in financial industry as well as demanding the most attention. Lending to potentially bad borrowers may substantially harm bank or credit union therefore this process must be addressed systematically by setting up automated and effective borrowers scoring process.
We effectively score borrowers using big data.
We retrieve additional statistical data to conduct further communications with existing borrowers.
Optimize credit portfolio to minimize payment overdues and defaults.
PROBLEMS AND SOLUTIONS
Consumer crediting is one of the highest priorities in financial sector nowadays that demands maximum attention. This process should be approached systematically and there should be efficient and automatic process of borrowers examination.
Organization of continuous work under repayments of granted credits.
Preparation of credit portfolio for sale or collectors
Efficient scoring of potential borrower based on “big data” analysis.
Receipt of additional statistics based on analysis of financial and nonfinancial data set for further communication with client.
Work with credit portfolio of a client for minimization of delays and elimination of missed credit payments.
Preparation of credit portfolio for sale or collectors.
TECHNOLOGIES AND ALGORITHMS
During the development of software we use the stack of technologies from Microsoft:
- Azure cloud
- technologies CUDA
Our algorithms and models of analysis are based on:
Group of self-learning neural networks; Systems of normalization of input parameters and semantic analyzer for parsing of text information; Formation of psychological profile of potential client; Method of clustering data; Classical scoring systems.
BENEFITS FOR CLIENTS
Efficient scoring (real time scoring based on behavioral analysis) of potential borrower based on analysis of “big data” in the moment of loan processing, loans support and after-sales servicing.
Receipt of additional statistics based on analysis of financial and nonfinancial data set for further communication with client with the purpose of increasing conversion of offered financial and nonfinancial products.
Automatization of workspace of credit analyst, formation of the range of roles for automatization of loans granting process, loans portfolio support and offering clients relevant services in real time.
More than 10 years in IT business. Successful sale of several businesses. Management of several IT-companies (Eureka! Solutions, Ticket Solutions). Working as technical analyst in FISON fund.
Education: Management on goods and services market, Kyiv National Trade and Economic University, Department of Economics.
More than 15 years of development of software and web-services, perfect acknowledge of web technologies (.Net, C#, C++, MS Azure, Java, PHP, Ruby).
Education: Applied mathematics, Taras Shevchenko National University of Kyiv, Department of Cybernetics.
More than 10 years of marketing and promotion. Co-founder of venture capital fund FISON. One year of work as a board member of ukrainian syndicate UAngels.
Education: Prydniprovs’ka State Academy of Civil Engineering and Architecture: Computer-Integrated Technologies. Academy of Business and Law: management innovative activity.