SUN’IY INTELLEKT YORDAMIDA MOLIYAVIY FIRIBGARLIKNI ANIQLASH MODELI
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Abstract:
Moliyaviy firibgarlik (fraud) dunyo bo‘yicha eng katta iqtisodiy muammolardan biri bo‘lib, korxonalar har yili milliardlab dollar yo‘qotmoqda. Ushbu tezisda firibgarlikni aniqlashda qo‘llaniladigan zamonaviy yondashuvlar, xususan ma’lumotlarni tahlil qilish (data mining) va mashina o‘rganishi (machine learning) usullari yoritiladi. Naqshlarni (patterns) aniqlash, anomaliyalarni topish va tasniflash modellari moliyaviy xavfni kamaytirishda muhim o‘rin tutadi. Tadqiqot “Fraud and Fraud Detection: A Practical Guide”, “Data Mining for Business Analytics”, hamda “Machine Learning for Financial Risk Management with Python” manbalari asosida olib borilgan.
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References:
Bolton, R.J., & Hand, D.J. (2002). Statistical Fraud Detection: A Review.
Delena D. Spann. (2014). Fraud and Fraud Detection: A Practical Guide.
Galit Shmueli, Peter C. Bruce, Inbal Yahav, Nitin Patel, Kenneth Lichtendahl (2020). Data Mining for Business Analytics: Concepts, Techniques, and Applications in R and Python.
Svetlana Borovkova. (2021). Machine Learning for Financial Risk Management with Python.