FİNANS SEKTÖRÜNDE YAPAY ZEKA, MAKİNE ÖĞRENMESİ ve BÜYÜK VERİ KULLANIMI: Fırsatlar, Zorluklar ve Politika Yapıcılar için Çıkarımlar

Abstract

Yapay Zekâ ve Makine Öğrenmesi teknolojilerinin finans sektöründeki kullanımları hızla yaygınlaşmaktadır. Sektörün mali aracılık fonksiyonunu yerine getirirken ürettiği büyük miktardaki veri söz konusu teknolojiler için elverişli bir çalışma ortamı da sağlamaktadır. Bu teknolojilerle desteklenen modeller bir yandan finansal kurumların ve piyasaların faaliyetlerinin etkinliğini ve verimliliğini artırıp, finansal tüketicilere daha kaliteli ürün ve hizmetler sunulmasına imkan verirken, diğer yandan ayrımcı, önyargılı, adaletsiz, manipülatif davranma, kararların arkasındaki nedenselliği açıklayamama, sürü davranışı yoluyla finansal piyasalarda tek yönlü harekete, döngüselliğe ve sistemik risklere yol açma gibi sebeplerle eleştirilmektedir. Çalışmamızda, dünyadaki uygulamalar da göz önünde bulundurularak sağlam ve güvenilir Yapay Zekâ ve Makine Öğrenmesi destekli modellerin finans sektöründe kullanımını sağlayacak politika ve düzenlemeler ele alınmış, düzenleme arbitrajını önleyecek şekilde uluslararası iş birliğinin geliştirilmesi ve düzenlemelerle teknolojik yenilikler arasında kurulması gereken dengenin önemine vurgu yapılmıştır.

Keywords

• finansal kurumlar
• finansal hizmetler
• yapay zeka

USE of ARTIFICIAL INTELLIGENCE, MACHINE LEARNING and BIG DATA in the FINANCIAL SECTOR: Opportunities, Challenges and Implications for Policymakers

Abstract

The use of Artificial Intelligence and Machine Learning technologies in the financial sector is rapidly expanding. While on the one hand, models supported by these technologies increase the effectiveness and efficiency of the activities of financial institutions and markets and provide better quality products and services to financial consumers, on the other hand, they are criticised for discriminatory, biased, unfair, manipulative behaviour, inability to explain the causality behind decisions, one-way movement in financial markets through herd behaviour, procyclicality and systemic risks. In our study, policies and regulations that will ensure the use of robust and reliable Artificial Intelligence and Machine Learning-supported models in the financial sector are discussed, taking into account global practices, and the importance of developing international cooperation to prevent regulatory arbitrage and the balance between regulations and technological innovations is emphasised.

Keywords

• financial institutions
• financial services
• artificial intelligence

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