How Does Loan and Funding Mix Differ Across Bank Ownership Types?

Ch. 12. P. 413–459.

Belousova V., Chichkanov N., Kraiouchkina J., Manzhulin I., Vasily Solodkov, Sukhov M.

This chapter explores how banks set priorities in their loan portfolio and funding mix depending on their form of ownership. We apply a two-stage approach: machine-learning method LASSO with K-fold cross-validation technique to select the meaningful determinants of bank’s loan and funding mix, which is followed up by panel data analysis. The classification of banks across ownership type is based on the official information disclosed on the website of the central bank. The dataset covers 3,220 observations over the period from January 1, 2013 to January 1, 2020. We show that banks differ substantially across ownership types. The foreign-owned banks rely mostly on their multinational brand and networks with the parent bank. The privately owned banks manage non-financial sector funds liabilities being highly linked with non-financial sector loans in assets through opening bank accounts for businesses when granting a loan. State-owned banks tend to decrease the share of non-financial sector funds in liabilities due to the higher volatility of these funds. Our study goes beyond the traditional empirical model, which is built often upon the preselected explanatory factors. Our model is data-driven, which accounts for institutional context and dynamics in market conditions. This chapter demonstrates that in spite of high efficiency reported in earlier scholarly research state-owned banks lack in bank’s capitalization. This provides an additional support for actions taken toward the privatization of banks (including banks undergoing financial rehabilitation measures of the central bank happened in leading emerging markets) rather than the state control over banks that leads to the capitalization of state-owned banks by the mode of public (budget) funding.

Keywords: private ownership, foreign ownership, loan portfolio, Banks, State ownership, LASSO, Funding mix

Publication based on the results of: National innovation system 2.0: involving key actors in transformation processes (2025)

In book

Handbook of Financial Econometrics, Statistics, Technology, and Risk Management (In 4 Volumes) Volume 1

Vol. 1. , World Scientific Publishing Co. Pte. Ltd, 2025.