Artificial Intelligence: Transforming Risk Management in Kazakhstan's Banking Sector

Abstract

Artificial intelligence (hereinafter – AI) is increasingly recognised as a transformative force within the banking sector, remodelling traditional risk management practices through improved analytical abilities and improved decision-making processes. The work aims to develop an Artificial Intelligence Risk Management Index (AI Risk Management Index, ARMI) to compare the level of AI implementation and effectiveness across leading banks in Kazakhstan. The research methodology is based on the construction of the composite ARMI index, which includes five standardized components: model accuracy (A), risk coverage (C), depth of integration (I), interpretability (X) and effectiveness (E). Weighting factors were set for each component (0.25, 0.20, 0.20, 0.15, and 0.20, respectively), allowing the consolidated ARMI indicator to be calculated. Empirical data (illustrative) cover the three largest banks in Kazakhstan: Kaspi Bank, ForteBank and Halyk Bank. Calculations show that Kaspi Bank has the highest ARMI (0.75), followed by ForteBank (0.71), while Halyk Bank (0.56) lags significantly behind. Kaspi Bank's greatest strengths are the high accuracy and depth of AI integration. The results of the study show that the active implementation of AI contributes to improving forecast accuracy, reducing operating costs, and developing a proactive risk management culture. At the same time, key problems have been identified – the limited use of AI in certain risk domains and the lack of transparency of algorithms. The proposed ARMI index can be used to monitor the digital maturity of Kazakhstan's banks, as well as to shape government policy on the development of AI in the financial sector.

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