Analysis of the possibility of building a credit risk model

FinAi has undertaken a project focused on the development of an innovative credit risk model utilizing alternative data sources, such as data from social media platforms (Facebook, LinkedIn) and mobile phone records. This project was co-financed through the European Regional Development Fund under a funding agreement between FinAi S.A. and the National Centre for Research and Development (NCBiR), headquartered in Warsaw. The initial phase of the project involved the collection of data and their utilization in constructing a network graph of customer relationships. Furthermore, leveraging external data as well as data managed by FinAi, specific indicators were formulated. These indicators were employed under the supervision of experts to train a predictive model that incorporated graph structures. The model thus constructed was to exhibit a higher predictive capability compared to conventional models commonly employed within the industry. The study explored the feasibility of creating a credit risk model based on the acquired data and assessed the quality of data originating from alternative sources. It was demonstrated that alternative data sources were populated for a small fraction of the population, and their quality has proven unsatisfactory. The scale of the dataset proved inadequate for establishing a robust credit risk model or attaining a competitive advantage over the models in use within banking institutions.

The growing interest in using graphs in education created the need for researchbased guidelines. This study examined the effects of graph type, conceptual domain and perceptual organization of information on graph comprehension. Forty-two undergraduate students were given eight different kinds of graphs, and their descriptions were analyzed. The results indicated that graphical reasoning was influenced by perceptual grouping of information in visual chunks rather than by type of graph. Learners faced difficulties when an unconventional graph format was used. Implications for research and practice were also discussed.