Lakshmana Narayanan, V. <br/><br/>
Machine learning algorithm for fintech innovation in blockchain applications 

 - Vol.14(1), Oct 
 - Chennai  ICT Academy  2024 
 - 3165-3172p. 
<br/><br/> The rapid growth of Fintech innovation and the widespread adoption<br/>of blockchain technologies have indeed had a transformative impact on<br/>the financial industry. In this paper, the focus is on the application of<br/>machine learning algorithms, specifically the Random Forest<br/>Regression algorithm, within the context of Fintech and blockchain.<br/>This research contributes to the advancement of machine learning<br/>techniques in the field of Fintech and blockchain. The Random Forest<br/>Regression algorithm utilizes ensemble learning, combining multiple<br/>decision trees to analyze complex financial data and make predictions<br/>on various outcomes. This algorithm has proven to be effective in<br/>addressing key challenges within the industry, such as predicting loan<br/>defaults, detecting fraud, and assessing risks. Through experimental<br/>evaluations and case studies, the paper demonstrates the effectiveness<br/>of the Random Forest Regression algorithm in enhancing Fintech<br/>innovation in blockchain applications. The algorithm improved<br/>accuracy, scalability, and interpretability enable financial institutions<br/>to make data-driven decisions and optimize their operations. 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Computer Engineering