مدل فرایندی سیاستگذاری توسعه هوش‌مصنوعی در صنعت فینتک ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دکتری مدیریت فناوری اطلاعات، دانشکدگان مدیریت، دانشگاه تهران، ایران

2 استاد، دانشکده مدیریت صنعتی و فناوری، دانشکدگان مدیریت، دانشگاه تهران، ایران

3 دانشیار، دانشکده مدیریت و حسابداری، دانشکدگان فارابی، دانشگاه تهران، ایران.

4 دانشیار، دانشکده مدیریت دولتی و علوم سازمانی، دانشکدگان مدیریت، دانشگاه تهران، ایران

10.22034/jstp.2025.12014.1912

چکیده

فینتک (فناوری مالی) به‌عنوان یکی از صنایع پیشرو در تحول دیجیتال، با بهره‌گیری از هوش‌مصنوعی توانسته است مزایای رقابتی قابل‌توجهی از جمله هوشمندی بیشتر، داده‌های بزرگ‌تر و در نتیجه عملکرد بهتری ایجاد کند. با این حال، گسترش کاربرد هوش‌مصنوعی در این صنعت، چالش‌های مالی، قانونی، اخلاقی و اجتماعی متعددی را برای کسب‌وکارها، مصرف‌کنندگان و نهادهای حاکمیتی و نظارتی به همراه داشته که ضرورت سیاستگذاری نظام‌مند در این حوزه را آشکار می‌سازد. هدف این تحقیق، ارائه یک مدل سیاستگذاری فرایندی برای توسعه هوش‌مصنوعی در صنعت فینتک است. در این تحقیق با با مبنا قرار دادن فرامدل توسعه هوش‌مصنوعی در صنعت فینتک ایران با استفاده از روش مطالعه موردی، اقدام شده ‌است. به این منظور 24 مورد شامل 6 مورد مستند مرتبط با موضوع تحقیق و 18 مورد مصاحبه شناسایی و تحت مطالعه موردی قرارگرفت. با هدف ایجاد فرایند سازمان‌یافته و امکان ارزیابی صحیح و عادلانه‌تر مصاحبه‌ها، پروتکل مصاحبه بر اساس پروتکل مصاحبه اسپیکارد تنظیم گردید و سپس انجام مصاحبه‌ها با نخبگان سیاستگذاری توسعه هوش‌مصنوعی و فعالان صنعت فینتک، بصورت عمیق و نیمه ساختاریافته و تا حصول کفایت نظری ادامه یافت. روش نمونه‌گیری در این تحقیق روش گلوله برفی و تجزیه ‌و تحلیل داده‌ها با استفاده از تحلیل مضمون صورت پذیرفته است. تحلیل تفسیری متن در این  تحقیق بر اساس روش هشت مرحله‌ای رابین و گیلهام  و تحلیل مضامین با روش جایگاه مضمون در شبکه مضامین اتراید_استرلینگ انجام شده است.در نهایت مدل سیاستگذاری توسعه هوش‌مصنوعی در صنعت فینتک با پنج‌گام اصلی شامل بررسی و شناسایی، ارائه و تحلیل‌، اتخاذ سیاست، اجرای سیاست، ارزیابی و بازنگری و 22 مرحله ارائه گردید. همچنین ملاحظات راهبردی و عملیاتی  مربوط به هر گام که از تحلیل مضامین احصاء شده به‌دست آمده بود، جهت بهبود در کیفیت اجرای مدل توضیح داده شد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

A Process-Oriented Policy Model for AI Development in Iran's FinTech Industry

نویسندگان [English]

  • Ali Eskandari 1
  • Amir Manian 2
  • Morteza Soltani 3
  • Hamidreza Yazdani 4
1 Ph.D. in Information Technology Management, Faculty of Industrial and Technology Management, University of Tehran, Iran.
2 Professor, Faculty of Industrial and Technology Management, School of Management, University of Tehran, Iran
3 Associate Professor, Faculty of Management and Accounting, Farabi School, University of Tehran, Iran
4 Associate Professor, Faculty of Public Administration and Organizational Sciences, School of Management, University of Tehran, Iran.
چکیده [English]

Financial technology (FinTech) has emerged as a pioneering industry in digital transformation by leveraging artificial intelligence to create substantial competitive advantages, including enhanced intelligence capabilities, big data utilization, and improved operational performance. However, the expanding application of AI in this sector has simultaneously introduced numerous financial, legal, ethical, and social challenges for businesses, consumers, and regulatory institutions, highlighting the critical need for systematic policymaking in this domain. This research aims to develop a process-oriented policy model for AI implementation within the FinTech industry. The study adopts a meta-model framework for AI development in FinTech and employs a case study methodology focusing on Iran's FinTech sector. The research methodology involved examining 24 distinct cases, comprising 6 relevant documentary sources and 18 in-depth interviews. To ensure methodological rigor, the interview process followed the SPICKARD protocol and consisted of semi-structured, intensive discussions with both AI policy experts and FinTech industry practitioners, continuing until theoretical saturation was achieved. Snowball sampling was utilized for participant selection, while data analysis was conducted through thematic analysis methods. Textual interpretation followed Rabiee and Gillham's eight-stage approach, with thematic analysis performed using Attride-Stirling's thematic network framework. The study ultimately proposes a comprehensive AI development policy model for the FinTech industry, structured around five core phases: investigation and identification, proposal and analysis, policy adoption, policy implementation, and evaluation and revision, encompassing a total of 22 specific stages. Furthermore, the research elucidates strategic and operational considerations derived from thematic analysis for each phase, providing valuable insights to enhance the model's implementation quality and effectiveness. The findings offer significant contributions to both academic discourse and practical policymaking in the evolving FinTech landscape.
 

کلیدواژه‌ها [English]

  • FinTech (financial technology)
  • artificial intelligence
  • Policymaking
  • artificial intelligence in fintech

مراجع

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