THE USE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN FINANCIAL SECTOR. A DECISION-MAKING FRAMEWORK
DOI:
https://doi.org/10.35631/JISTM.1143002Keywords:
Artificial Intelligence, Financial Management, Machine Learning, Selection Framework, Task AutomationAbstract
This study provides an overall review on current state of Artificial Intelligence (AI) and Machine Learning (ML) adoption in financial sector as well as explores a framework for identification of potential tasks for automation using AI and ML. The study utilizes a qualitative research methodology grounded in Dynamic Capabilities Theory. The research examines existing processes automated in financial institutions. The overall approach comprised review of existing literature, obtaining primary data through semi-structured interviews and performing thematic analysis. Analysis of data identified that AI & ML models are used for predictive analytics, fraud detection, credit risk assessment, investment portfolio, auditing, compliance monitoring, and customer services across the financial sector. Common criteria for selecting tasks were identified during primary data collection are also explored in this study. The study also discusses concerns shared by participants while they are selecting processes for automation. The research work also assisted in development of a framework to support the process for tasks automation for AI/ML.
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