<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">qainar</journal-id><journal-title-group><journal-title xml:lang="ru">Qainar Journal of Social Science</journal-title><trans-title-group xml:lang="en"><trans-title>Qainar Journal of Social Science</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2958-7212</issn><issn pub-type="epub">2958-7220</issn><publisher><publisher-name>Q University</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.58732/2958-7212-2025-3-6-23</article-id><article-id custom-type="elpub" pub-id-type="custom">qainar-369</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>Статьи</subject></subj-group></article-categories><title-group><article-title>Искусственный интеллект: трансформация системы управления рисками в банковском секторе Казахстана</article-title><trans-title-group xml:lang="en"><trans-title>Artificial Intelligence: Transforming Risk Management in Kazakhstan's Banking Sector</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0000-8585-3341</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Отеген</surname><given-names>А. Н.</given-names></name><name name-style="western" xml:lang="en"><surname>Otegen</surname><given-names>A. N.</given-names></name></name-alternatives><bio xml:lang="ru"><p>PhD докторант</p><p>Алматы</p></bio><bio xml:lang="en"><p>Aizhan N. Otegen – PhD candidate</p><p>Almaty</p></bio><email xlink:type="simple">aizhanotegen29@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">Казахский национальный университет им. аль-Фараби<country>Казахстан</country></aff><aff xml:lang="en">Al-Farabi Kazakh National University<country>Kazakhstan</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>04</day><month>11</month><year>2025</year></pub-date><volume>4</volume><issue>3</issue><fpage>6</fpage><lpage>23</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Отеген А.Н., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Отеген А.Н.</copyright-holder><copyright-holder xml:lang="en">Otegen A.N.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.journal-kainar.kz/jour/article/view/369">https://www.journal-kainar.kz/jour/article/view/369</self-uri><abstract><p>Настоящее исследование посвящено комплексному анализу гендерных различий в доступе к информационно-коммуникационным технологиям (далее – ИКТ) в Казахстане в 2015-2024 гг. и их влияния на образование и занятость. Методология исследования основана на описательном статистическом анализе, корреляционных методах и модели «разница в разнице» (DiD). Данный подход позволяет сравнить динамику гендерного неравенства с течением времени и определить, как цифровизация повлияла на социально-экономические различия между женщинами и мужчинами. Результаты показывают устойчивое сокращение гендерного цифрового разрыва. Разница в доступе к интернету между мужчинами и женщинами снизилась с 2,8 п.п. в 2015 г. до 0,6 п.п. в 2024 г., а в использовании мобильных технологий произошёл инверсный сдвиг в пользу женщин на 15,8 п.п. к 2024 г. (при преимущественно мужском доминировании в 2016 г. на 1,6 п.п.). Корреляционный анализ выявил сильную положительную взаимосвязь между интернет-доступом и цифровой грамотностью (r &gt; 0,9), а также между цифровыми навыками и обращениями к государственным платформам занятости (r = 0,88 для мужчин и r = 0,71 для женщин), что подтверждает роль цифровизации как механизма расширения участия на рынке труда. Женщины стали активнее использовать смартфоны и онлайн-платформы, получив более широкий доступ к электронным услугам и государственным ресурсам, что способствовало их участию на рынке труда и выходу в формальные системы занятости. Кроме того, исследование показало, что гендерное неравенство по-прежнему сохраняется в сфере высшего образования. В результате, в исследовании подчеркивается двойственная природа цифровизации: с одной стороны, она повышает социальную инклюзивность, но с другой стороны, усиливает сохранение структурного неравенства в обществе.</p></abstract><trans-abstract xml:lang="en"><p>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.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>искусственный интеллект</kwd><kwd>управление рисками</kwd><kwd>финансы</kwd><kwd>банк</kwd><kwd>банковский сектор</kwd><kwd>социально ориентированные финансы</kwd><kwd>цифровая трансформация</kwd></kwd-group><kwd-group xml:lang="en"><kwd>artificial intelligence</kwd><kwd>risk management</kwd><kwd>finance</kwd><kwd>bank</kwd><kwd>banking sector</kwd><kwd>socially oriented finance</kwd><kwd>digital transformation</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Aitkhanova, A. &amp; Khamzina, A. (2023). The vulnerabilities of AI in financial services: risks and challenges. Journal of Kazakhstan Economic Studies, 15 (3), 201–218.</mixed-citation><mixed-citation xml:lang="en">Aitkhanova, A. &amp; Khamzina, A. (2023). The vulnerabilities of AI in financial services: risks and challenges. Journal of Kazakhstan Economic Studies, 15 (3), 201–218.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Akhmet, A. T., &amp; Kairat, Y. K. (2024). Integration of Chatbots for Sales purposes in Kazakhstan: Benefits and Risks (Bachelor's thesis, International School of Economics Maqsut Narikbayev University, Astana).</mixed-citation><mixed-citation xml:lang="en">Akhmet, A. T., &amp; Kairat, Y. K. (2024). Integration of Chatbots for Sales purposes in Kazakhstan: Benefits and Risks (Bachelor's thesis, International School of Economics Maqsut Narikbayev University, Astana).</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Alzahrani, Z., Mehmood, A. &amp; Malik, A. (2021). The impact of artificial intelligence on bank risk management: a case study by Kazakhstan. International Journal of Financial Services Management, 10(2), 89-105.</mixed-citation><mixed-citation xml:lang="en">Alzahrani, Z., Mehmood, A. &amp; Malik, A. (2021). The impact of artificial intelligence on bank risk management: a case study by Kazakhstan. International Journal of Financial Services Management, 10(2), 89-105.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Azharbayeva, A., Abdinova, M. &amp; Khlevna, I. (2023). Credit risk management of JSC “Halyk bank”: problems and solutions. International journal of information and communication technologies, 4(3), 1-23. https://doi.org/10.54309/IJICT.2023.15.3.001</mixed-citation><mixed-citation xml:lang="en">Azharbayeva, A., Abdinova, M. &amp; Khlevna, I. (2023). Credit risk management of JSC “Halyk bank”: problems and solutions. International journal of information and communication technologies, 4(3), 1-23. https://doi.org/10.54309/IJICT.2023.15.3.001</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Azretbergenova, G. (2021). Positive aspects of big data in the financial sector and development in Kazakhstan. Geçmişten Geleceğe Avrasya, 188-219 (Paradigma Akademi Basın Yayın Dağıtım).</mixed-citation><mixed-citation xml:lang="en">Azretbergenova, G. (2021). Positive aspects of big data in the financial sector and development in Kazakhstan. Geçmişten Geleceğe Avrasya, 188-219 (Paradigma Akademi Basın Yayın Dağıtım).</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Barlybayev, A., Ongalov, N., Sharipbay, A., &amp; Matkarimov, B. (2024). Enhancing Real Estate Valuation in Kazakhstan: Integrating Machine Learning and Adaptive Neuro-Fuzzy Inference System for Improved Precision. Applied Sciences, 14(20), 9185. https://doi.org/10.3390/app14209185</mixed-citation><mixed-citation xml:lang="en">Barlybayev, A., Ongalov, N., Sharipbay, A., &amp; Matkarimov, B. (2024). Enhancing Real Estate Valuation in Kazakhstan: Integrating Machine Learning and Adaptive Neuro-Fuzzy Inference System for Improved Precision. Applied Sciences, 14(20), 9185. https://doi.org/10.3390/app14209185</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Giuca, O., Popescu, T.M., Popescu, A.M., Prostean, G., &amp; Popescu, D.E. (2021). A Survey of Cybersecurity Risk Management Frameworks. Soft Computing Applications. SOFA 2018. Advances in Intelligent Systems and Computing, 1221. Springer, Cham. https://doi.org/10.1007/978-3-030-51992-6_20</mixed-citation><mixed-citation xml:lang="en">Giuca, O., Popescu, T.M., Popescu, A.M., Prostean, G., &amp; Popescu, D.E. (2021). A Survey of Cybersecurity Risk Management Frameworks. Soft Computing Applications. SOFA 2018. Advances in Intelligent Systems and Computing, 1221. Springer, Cham. https://doi.org/10.1007/978-3-030-51992-6_20</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Kazbekova, K., Adambekova, A., Baimukhanova, S., Kenges, G., &amp; Bokhaev, D. (2020). Bank risk management in the conditions of financial system instability. Entrepreneurship and Sustainability Issues, 7(4), 3269. https://doi.org/10.9770/jesi.2020.7.4%2846%29</mixed-citation><mixed-citation xml:lang="en">Kazbekova, K., Adambekova, A., Baimukhanova, S., Kenges, G., &amp; Bokhaev, D. (2020). Bank risk management in the conditions of financial system instability. Entrepreneurship and Sustainability Issues, 7(4), 3269. https://doi.org/10.9770/jesi.2020.7.4%2846%29</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Marzhan, Y., Talshyn, K., Kairat, K., Belginova, S., Karlygash, A., &amp; Yerbol, O. (2022). Smart technologies of the risk-management and decision-making systems in a fuzzy data environment. Indonesian Journal of Electrical Engineering and Computer Science, 28(3), 1463-1474. https://doi.org/10.11591/ijeecs.v28.i3.pp1463-1474</mixed-citation><mixed-citation xml:lang="en">Marzhan, Y., Talshyn, K., Kairat, K., Belginova, S., Karlygash, A., &amp; Yerbol, O. (2022). Smart technologies of the risk-management and decision-making systems in a fuzzy data environment. Indonesian Journal of Electrical Engineering and Computer Science, 28(3), 1463-1474. https://doi.org/10.11591/ijeecs.v28.i3.pp1463-1474</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Moldabekova, S. (2022). Technology investment decision-making: case studies of the implementation of contactless and QR payments in commercial banks of Kazakhstan. [Doctoral thesis, University of Edinburgh]. University of Edinburgh ERA. http://dx.doi.org/10.7488/era/2777</mixed-citation><mixed-citation xml:lang="en">Moldabekova, S. (2022). Technology investment decision-making: case studies of the implementation of contactless and QR payments in commercial banks of Kazakhstan. [Doctoral thesis, University of Edinburgh]. University of Edinburgh ERA. http://dx.doi.org/10.7488/era/2777</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Nagrani, P.H. (2025). Quantifying Intelligence: Shaping a Flourishing Financial Ecosystem Through AI. International Journal of Social Science and Economic Research, 10(8), 3179 – 3191. https://doi.org/10.46609/ijsser.2025.v10i08.011</mixed-citation><mixed-citation xml:lang="en">Nagrani, P.H. (2025). Quantifying Intelligence: Shaping a Flourishing Financial Ecosystem Through AI. International Journal of Social Science and Economic Research, 10(8), 3179 – 3191. https://doi.org/10.46609/ijsser.2025.v10i08.011</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Nichkasova, Y., Sadvokassova, K., &amp; Kayupov, N. (2021). Conceptual model for managing sustainable development of the financial market based on fuzzy cognitive maps: case study of Kazakhstan. International Journal of Economic Policy in Emerging Economies, 14(1), 1- 38. https://doi.org/10.1504/ijepee.2020.10030960</mixed-citation><mixed-citation xml:lang="en">Nichkasova, Y., Sadvokassova, K., &amp; Kayupov, N. (2021). Conceptual model for managing sustainable development of the financial market based on fuzzy cognitive maps: case study of Kazakhstan. International Journal of Economic Policy in Emerging Economies, 14(1), 1- 38. https://doi.org/10.1504/ijepee.2020.10030960</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Nichkasova, Y., Shmarlouskaya, H., &amp; Sadvokassova, K. (2022). Financial market sustainable development of Kazakhstan: scenario approach based on fuzzy cognitive maps. Journal of Sustainable Finance &amp; Investment, 12(3), 912-933. https://doi.org/10.1080/20430795.2020.1812293</mixed-citation><mixed-citation xml:lang="en">Nichkasova, Y., Shmarlouskaya, H., &amp; Sadvokassova, K. (2022). Financial market sustainable development of Kazakhstan: scenario approach based on fuzzy cognitive maps. Journal of Sustainable Finance &amp; Investment, 12(3), 912-933. https://doi.org/10.1080/20430795.2020.1812293</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Nurgaliyeva, K., Koshkina, O., Zaitenova, N., Kireyeva, A., &amp; Kredina, A. (2024). Relationship between banking infrastructure, innovation and economic growth in Kazakhstan. Banks and Bank Systems, 19(2), 40-52. https://doi.org/10.21511/bbs.19%282%29.2024.04</mixed-citation><mixed-citation xml:lang="en">Nurgaliyeva, K., Koshkina, O., Zaitenova, N., Kireyeva, A., &amp; Kredina, A. (2024). Relationship between banking infrastructure, innovation and economic growth in Kazakhstan. Banks and Bank Systems, 19(2), 40-52. https://doi.org/10.21511/bbs.19%282%29.2024.04</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Omarkhanova, A., Tynyshbayeva, A., Kadyrova, M., Igibayeva, A., &amp; Saktayeva, А. (2024). Risk management in the public sector of Kazakhstan: current state and development opportunities. Public Policy and Administration, 23(2), 222-236. https://doi.org/10.13165/vpa-24-23-2-08</mixed-citation><mixed-citation xml:lang="en">Omarkhanova, A., Tynyshbayeva, A., Kadyrova, M., Igibayeva, A., &amp; Saktayeva, А. (2024). Risk management in the public sector of Kazakhstan: current state and development opportunities. Public Policy and Administration, 23(2), 222-236. https://doi.org/10.13165/vpa-24-23-2-08</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Satymbekova, K., Yessenova, A., Kuanaliyeva, G., &amp; Kerimbek, G. (2024). The main challenges of digital transformation in financial services and solutions to overcome them. THE BULLETIN, 3 (409), 431-445. https://doi.org/10.32014/2024.2518-1467.778</mixed-citation><mixed-citation xml:lang="en">Satymbekova, K., Yessenova, A., Kuanaliyeva, G., &amp; Kerimbek, G. (2024). The main challenges of digital transformation in financial services and solutions to overcome them. THE BULLETIN, 3 (409), 431-445. https://doi.org/10.32014/2024.2518-1467.778</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Utebayev, A., &amp; Kemelbayeva, S. (2024). Report on key findings and recommendations across various sectors in Kazakhstan based on ISE master’s theses and diploma projects. Maqsut Narikbayev University, International School of Economics. http://repository.mnu.kz/bitstream/handle/123456789/2085/ISE_Diploma_Projects_Conclusions%26Recommendations.pdf?sequence=1&amp;isAllowed=y</mixed-citation><mixed-citation xml:lang="en">Utebayev, A., &amp; Kemelbayeva, S. (2024). Report on key findings and recommendations across various sectors in Kazakhstan based on ISE master’s theses and diploma projects. Maqsut Narikbayev University, International School of Economics. http://repository.mnu.kz/bitstream/handle/123456789/2085/ISE_Diploma_Projects_Conclusions%26Recommendations.pdf?sequence=1&amp;isAllowed=y</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">World Finance. (2024). How ForteBank is shaping Kazakhstan’s banking future. World Finance. Retrieved from https://www.worldfinance.com/banking/how-fortebank-is-shaping-kazakhstans-banking-future</mixed-citation><mixed-citation xml:lang="en">World Finance. (2024). How ForteBank is shaping Kazakhstan’s banking future. World Finance. Retrieved from https://www.worldfinance.com/banking/how-fortebank-is-shaping-kazakhstans-banking-future</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Yelesh, A. (2020). Machine learning techniques in Kazakhstan banks’ sustainability assessment based on ISE master’s theses and diploma projects. Maqsut Narikbayev University, International School of Economics. http://repository.kazguu.kz/bitstream/handle/123456789/838/Arman%20Yelesh%20MSC%20thesis.pdf?sequence=1</mixed-citation><mixed-citation xml:lang="en">Yelesh, A. (2020). Machine learning techniques in Kazakhstan banks’ sustainability assessment based on ISE master’s theses and diploma projects. Maqsut Narikbayev University, International School of Economics. http://repository.kazguu.kz/bitstream/handle/123456789/838/Arman%20Yelesh%20MSC%20thesis.pdf?sequence=1</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
