Internal audit under Kazakhstan’s 2019 risk-management and internal control requirements: A continuous-treatment difference-in-differences analysis of commercial banks’ financial stability

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Type of the article: Research Article

Abstract
Weak risk governance and legacy non-performing loans have repeatedly destabilized banks in emerging markets, making the payoff from regulatory strengthening of internal control and internal audit a first-order policy question. This study aims to determine whether Kazakhstan’s 2019 risk-management and internal control requirements (National Bank Resolution No. 188), whose core assurance mechanism is a strengthened internal audit function, improved the financial stability of the country’s commercial (second-tier) banks, and to identify the channel of this effect. The analysis applies a continuous-treatment difference-in-differences design to an annual panel of 37 banks over 2015–2025 (287 bank-years), interacting each bank’s pre-intervention (2016–2019) weakness with the post-intervention period and measuring stability by the log Z-score. The results show that the stabilizing effect is concentrated in the asset-quality channel: banks that entered the post-2020 period with a one-standard-deviation greater non-performing-loan weakness recorded a 0.38-0.41 log-point (roughly 40-50%) larger post-intervention increase in the Z-score (p < 0.01), whereas composite pre-intervention weakness yields no robust effect under any weighting scheme. The effect emerges with a multi-year lag, becoming statistically detectable only toward the end of the sample period, and operates through capital rebuilding. Because pre-intervention weakness strongly predicts market exit (Cox hazard ratio ≈ 3.95), the estimates are a lower bound on the intervention’s full association with sector stability. The findings imply that supervisors should target credit-risk governance, loan classification, timely recognition of problem loans, and provisioning, where strengthened internal control and audit yield the largest stability gains.

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    • Figure 1. Difference-in-differences coefficients by pre-intervention weakness dimension (dependent variable: log Z-score)
    • Figure 2. Event-study estimates of the intervention effect, by pre-intervention weakness measure (base year 2020)
    • Figure 3. Stability trajectory of high- versus low-NPL-weakness banks (mean log Z-score by year)
    • Figure 4. Pre-intervention weakness (2016–2019) and bank outcome
    • Table 1. Variable definitions and sources
    • Table 2. Descriptive statistics
    • Table 3. 2019 requirements and bank stability: continuous-treatment difference-in-differences
    • Table A1. Sample of banks and treatment status
    • Table B1. Correlation matrix of control variables
    • Table C1. Pre-intervention balance by weakness group
    • Table D1. Summary of robustness checks
    • Table E1. Alternative weighting schemes for the composite pre-intervention weakness index
    • Table F1. Event-study coefficients (dependent variable: log Z-score)
    • Conceptualization
      Ulpan A. Shonayeva, Aliya Nurgaliyeva, Diana Alisheva, Gaukhar Uvakbayeva, Kalilla Abdullayev
    • Methodology
      Ulpan A. Shonayeva, Aliya Nurgaliyeva, Kalilla Abdullayev
    • Supervision
      Ulpan A. Shonayeva
    • Writing – original draft
      Ulpan A. Shonayeva, Aliya Nurgaliyeva, Diana Alisheva, Gaukhar Uvakbayeva, Kalilla Abdullayev
    • Writing – review & editing
      Ulpan A. Shonayeva, Aliya Nurgaliyeva, Diana Alisheva, Gaukhar Uvakbayeva, Kalilla Abdullayev
    • Investigation
      Aliya Nurgaliyeva
    • Data curation
      Diana Alisheva, Kalilla Abdullayev
    • Formal Analysis
      Diana Alisheva
    • Funding acquisition
      Gaukhar Uvakbayeva
    • Validation
      Gaukhar Uvakbayeva
    • Visualization
      Kalilla Abdullayev