The National Centre for Research and Development in Poland (NCBR) granted FinAi PLN 7.3 million (ca. EUR 1.75 million) under the Smart Growth Operational Programme.
The company aims to build a retail credit risk estimation model using alternative data sources and the latest research and tools in the field of graph theory. FinAi has signed project partnerships with the Faculty of Mathematics and Information Science of Warsaw University of Technology and one of the leading retail banks in Poland.
The FinAi’s project meets the expectations of banks that are seeking for new, effective methods of analyzing and reducing credit risk in a dynamically changing business environment.Similar solutions are already successfully operating globally and are offered by companies such as Lenddo or ZestFinance. However, they are less advanced as far as the data analysis methods used and the mathematical methodology behind the project are concerned. The European market still lacks a player who would offer banks and customers a new quality in the area of credit risk assessment – said Łukasz Dziekan, CTO FinAi. And he adds: We are facing a unique opportunity for the Polish fintech to play a significant role in the export of Polish scientific and technological thought on a European scale, for the key process for the banking sector.
The implementation of a new credit risk assessment model will enable banks and other financial institutions to reach new segments of the population with loan products, while at the same time improving the efficiency of existing tools and processes. Thanks to its use, the number of people who will be assessed by the Polish banking system as credible from the credit risk point of view will also increase, which in the long run may have an impact on improving the financial exclusion rate among Poles. This will particularly apply to young people, at the beginning of their careers, for whose banks are currently lacking solutions to assess their creditworthiness, especially in remote channels.
Research related to the analysis of advanced graph theory will be carried out by FinAi
in cooperation with the Faculty of Mathematics and Information Science of Warsaw University of Technology. The team of scientists at Warsaw University of Technology will be led by prof. Jarosław Grytczuk. On behalf of FinAi the project will be implemented by experts with many years of experience in building risk models for the banking sector. The teams will closely cooperate so that the latest scientific achievements and work on new customer data representations can be implemented as a real business solution.
To build an effective credit risk estimation model, FinAi has also established a partnership with one of the largest retail banks on the Polish market.
The involvement of significant partners shows the scale of the project carried out by the Polish fintech. The total cost of its implementation will amount to PLN 9.5 million (c.a. EUR 2.3 million), of which PLN 7.3 million will be financed from the European funds.
The National Centre for Research and Development is the implementing agency of the Minister of Science and Higher Education. It was appointed in the summer 2007 as an entity in charge of the performance of the tasks within the area of national science, science and technology and innovation policies. When it was founded, it was the first entity of this type, created as the platform of an effective dialogue between the scientific and business communities.
FinAi is a Poland-based fintech founded in 2016. The company is creating a top-notch fully digital lending platform which aims to simplify the consumer’s credit path, as well as services supporting remote sales: models for operational risk management and credit risk based on completely new data for the sector. There are over 50 people on board at the moment, all have various experience in banking, IT, Data Science and digital marketing. The FinAi credit platform will be available to customers of Polish banks in the first quarter of 2018. In 2020, the company plans to intermediate over PLN 1 billion of loans through the platform.