Разработка модели социального скоринга на примере социально-экономических характеристик населения

Т. Ю. Кудрявцева; Е. В. Королёва; Е. А. Ефимов

Authors

T. Yu. Kudryavtseva Peter the Great St. Petersburg Polytechnic University
E. V. Koroleva Peter the Great St. Petersburg Polytechnic University
E. A. Efimov Peter the Great St. Petersburg Polytechnic University

Keywords:

social scoring, logistic regression, social networks, ROC analysis, social profile

Abstract

The activities of the banking sector in the financial system of the state are an important factor in increasing socio-economic development. Consumer lending is a driver of demand for goods and services. The direction of assessing the creditworthiness of individual borrowers is functioning quite well at present; there are many methods and approaches, however, along with this, there are also problems and shortcomings that need to be eliminated. To ensure the continuous circulation of capital in the economy, one of the main tasks of banks is to reduce the volume of problem debt. The purpose of the study is to develop a social scoring model using modern approaches to processing and analyzing Big data. The scientific novelty of the study is the development of the author’s model for assessing the socio-economic characteristics of the population based on data from social networks through the construction of logistic regression. The practical significance of the study lies in the fact that the developed model can be used by credit institutions as an additional tool to the standard methodology for scoring analysis of the creditworthiness of individuals.

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Author Biographies

T. Yu. Kudryavtseva, Peter the Great St. Petersburg Polytechnic University

Doctor of Economic Sciences, Professor, Professor of the Higher School of Engineering and Economics
E. V. Koroleva, Peter the Great St. Petersburg Polytechnic University

Candidate of Economic Sciences, Associate Professor, Associate Professor of the Higher School of Engineering and Economics
E. A. Efimov, Peter the Great St. Petersburg Polytechnic University

postgraduate student of the Higher School of Engineering and Economics

References

Rose P.S. (1995). Bank Management. Producing and Selling Financial Services. Moscow: Delo. [In Russian]

Vodopyanova V. A., Boroday E. A. (2020). Analysis of methods for assessing the creditworthiness of legal entities used by Russian banks. Azimuth of scientific research: economics and management, 4 (33), 83-86. [In Russian]

Pestova A., Mamonov M. (2013). Macroeconomic and bank-specific determinants of credit risk: Evidence from Russia. Economic Education and Research Consortium. Working Paper No. 13/10E, 53 p.

Chernikova L., Faizova G., Egorova E., Kozhevnikova N. (2015). Functioning and development of retail banking in Russia. Mediterranean Journal of Social Sciences, 6 , 274-274. http://doi.org/10.5901/mjss.2015.v6n6s4p274.

Kjosevski J., Petkovski M. (2017). Non-performing loans in the Baltic States: determinants and macroeconomic effects. Baltic Journal of Economics, 1, 25-44.

Leo M., Sharma S., Maddulety K. (2019). Machine learning in banking risk management: A literature review. Risks, 1, 29.

Niu B., Ren J., Li X. (2019). Credit scoring machine learning by combining social network information: Evidence from peer-to-peer lending. Information, 12, 397. http://doi.org/10.3390/info10120397.

Orlando G., Pelosi R. (2020). Non-performing loans for Italian companies: When time matters. an empirical research on estimating probability to default and loss given default. International Journal of Financial Studies, 4, 68. http://doi.org/10.3390/ijfs8040068

Berger A.N., Sedunov J. (2017). Bank liquidity creation and real economic output. Journal of Banking & Finance, 81, 1-19. http://doi.org/10.1016/j.jbankfin.2017.04.005.

Poleshchuk Y.A. (2014). Tricks of social networks. Banking review, 2, 46-52. [In Russian]

Buchneva A.V. (2018). Analysis of user profiles of social networks. Chronoeconomics, 3 (11), 66-70. [In Russian]

Naumenko T.V., Sekretareva K.N. (2022). Chinese social credit system: dystopia or a factor of public well-being?. Journal of Social Policy Research, 3, 419-432. [In Russian]

Voronin S.M., Soverteka Z.K., Berezin A.D., Larin A.I. (2022). Credit scoring implemented using machine learning. Stolypinsky Bulletin, 10, 5640-5648. [In Russian]

Ismailov I.M., Istomina Yu.V. (2023). Modern trends in the development of credit bureaus in Russia. Spring Days of Science: collection of reports of the International Conference of Students and Young Scientists. Ekaterinburg: Publishing House "Azhur".[In Russian]

Pronyaeva L.I., Shchegolev A.V., Davydkin I.G. (2022). Financial support for the activities of small businesses. Bulletin of the Academy of Knowledge, 6 (53), 369-375. [In Russian]

Ruvinsky R.Z. (2022). Legal aspects of introducing the social credit system into modern public administration. Nizhny Novgorod: National Research University RANEPA. [In Russian]

Mironov S.V., Sharafutdinov A.G. (2022). Calculation of net assets in valuation activities. Modern scientific research: theory, methodology, practice: Collection of scientific articles based on the materials of the IX International Scientific and Practical Conference. Part 2. Ufa: Limited Liability Company "Scientific Publishing Center "Bulletin of Science". [In Russian]

Gnatik E. N. (2022). The world in the era of obsession with security: risks, limitations, opportunities. Humanity in the new reality: global biotechnological challenges: Collection of articles. Moscow: Kanon+.[In Russian]

Gerasimenko A.V. (2022). Modern approaches to client assessment in Russian banks. Innovative science, 2-1, 41-43. [In Russian]

Kosmarsky A.A., Kartavtsev V. V. (2022). Digital technologies of reputation in urban everyday life: between platform capitalism and state social rating. Urban Research and Practice, 1, 65-74. [In Russian]

Ovchinnikova A.V., Zimin S.D. (2023). Aspects of the effective functioning of state microfinance organizations in the context of sustainable development of the regional economy. Development of territorial social and economic systems: questions of theory and practice, 57-61. [In Russian]

Yusupova O.A., Fedotov M.Yu. (2022). Borrower’s profile in social networks and its assessment by the bank when issuing a loan. Challenges of modernity and strategies for the development of society in the new reality, 267-273. [In Russian]

Komarova O.M. (2022). Economic justification for the effectiveness of using the social rating system as a form of state control over society. Management accounting, 4, 48-54. [In Russian]

Yaroshchuk A.B. (2023). Modern banking technologies and their influence on the development of the financial and credit system of the Russian Federation. Scientific activity in the conditions of digitalization: Theoretical and practical aspects: collection of articles of the National (All-Russian) scientific and practical conference with international participation. Part 1. Ufa: Limited Liability Company "Omega Science".[In Russian]

Lazarov A.A. (2022). The right to access information when applying the social credit system (social scoring). Bulletin of the O. E. Kutafin University, 4 (92), 136-142. [In Russian]

Oseev V.A., Klemenov D.A. (2023). Introduction of digital technologies by banks to overcome financial imbalances in modern conditions. Issues of innovative economics, 2, 837-848. [In Russian] http://doi.org/10.18334/vinec.13.2.117881