December 2024
Intermediate to advanced
336 pages
8h 46m
English
book
Computational Intelligence for Autonomous Finance
by Deepak Gupta, Mukul Gupta, Rajesh Kumar Dhanaraj, Balamurugan Balusamy, Parth M. Gupta
Content preview from Computational Intelligence for Autonomous Finance
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10Application of Machine Learning Models in the Field of Autonomous Finance
Umesh Gupta1*, Shriyash Saxena1, Sachin Kumar Yadav2 and Aditya Bhardwaj1
1SCSET, Bennett University, Greater Noida, Uttar Pradesh, India
2Dept. of CEA, GLA Mathura, Uttar Pradesh, India
Abstract
Using Artificial Intelligence (AI) in Autonomous Finance (AF) helps reduce error and biases caused by humans. By automating duties and functions previously performed manually, such as data entry, analysis, and decision-making, AI enhances the efficiency of financial institutions. This automation reduces costs, improves efficiency, and ensures more accurate and consistent decisions. AI algorithms help identify fraudulent activities, making financial institutions more secure and better at managing risks. By scrutinizing vast data sets and detecting iterations, repetitions and anomalies, AI can identify and prevent fraudulent transactions in real-time. Additionally, AI algorithms provide personalized services and products according tailored to individuals’ distinctive financial preferences and priorities. By analyzing data and making future predictions, AI recommends personalized investment options, insurance products, and other financial services.
Keywords: Markov decision process, neural network, reinforcement learning, sentiment analysis, autonomous finance, deep learning
10.1 Overview
Machine learning (ML) and AI are among the latest technologies people aspire to work in. Terms like data mining and statistical ...
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