IMPACT UNCERTAINTY ON BANK CREDIT POLICY: A THEORETICAL ANALYSIS

Abstract

The intricate interplay between geopolitical tensions, regulatory changes, economic fluctuations, and unexpected shocks underscores the need for a comprehensive framework to assess and manage uncertainty in credit policy formulation. Considering the above, the article aims to develop a theoretical model of the impact of uncertainty on the bank’s credit policy. For this purpose, it explores the essence of «uncertainty» as a scientific category and forms its typology based on sources of origin. The article also describes geopolitical, political, regulatory, and economic uncertainties and uncertainty shocks resulting from extreme events (natural disasters, pandemics, technological catastrophes, geopolitical conflicts, etc.). The study delineates that the indirect influence of uncertainty on credit policy occurs through changes in borrowers’ economic behaviour, which can entail uncertainty about income stability, cash flow forecasts, and collateral values, complicating lenders’ assessment of their ability to service loans. Moreover, uncertainty can affect borrowers’ willingness to undertake new debt obligations (delaying loan decisions or reducing credit exposure) in response to uncertainty about future operating conditions. For banks as lenders, uncertainty may alter risk propensity and tolerance levels, affecting their willingness to lend, set loan terms, and allocate capital. A higher level of uncertainty may prompt banks to adopt a more conservative credit policy, strengthen lending standards, or increase the cost of loans to offset risks. Furthermore, uncertainty complicates credit portfolio management decisions as banks seek to balance risks, optimize asset allocation, and mitigate credit-related losses. Uncertainty regarding future economic conditions, market instability, and regulatory changes can influence lenders’ strategies for diversification, asset selection, and risk reduction, including scaling back credit activities. By incorporating insights from this model into decision-making processes, banks can develop more robust risk management strategies, and mitigate the adverse effects of uncertainty on financial stability.