Machine Learning In Finance Risk Management Trading And Fraud Detection
Download Machine Learning In Finance Risk Management Trading And Fraud Detection PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Machine Learning In Finance Risk Management Trading And Fraud Detection book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
MACHINE LEARNING IN FINANCE: RISK MANAGEMENT, TRADING, AND FRAUD DETECTION
Author: Dr. Aman Gupta
language: en
Publisher: Xoffencerpublication
Release Date: 2023-07-04
Artificial intelligence (AI) systems are machine-based systems with varying degrees of autonomy that generate predictions, suggestions, or judgements for a set of humanspecified goals utilizing enormous numbers of alternative data sources and data analytics referred to as "big data"3 (OECD, 2019). Artificial intelligence (AI) systems are sometimes referred to as intelligent machines. Systems that are powered by artificial intelligence (AI) are increasingly finding applications in a wide range of fields, including the medical field, the financial sector, and the armed forces. Common synonyms for artificial intelligence (AI) include "machine learning" and "machine learning systems." An explanation of artificial intelligence may be found in the following: "Artificial intelligence systems" are defined by the Oxford English Dictionary as "machine-based systems that can exhibit varying degrees of autonomy." You may learn more about this concept by reading the page titled "Artificial Intelligence Systems." Once they have access to the data, the models have the potential to "self-improve" by inferentially learning from further data sets without the need for human instruction. This may occur if they learn to draw conclusions from other data sets via inference. The acceleration and strengthening of a tendency toward digitalization that was already apparent before the pandemic is a direct outcome of the spread of the COVID-19 virus. This trend was already clear before the epidemic. Utilization of artificial intelligence is included in this trend. The abundance of data that is already available, in addition to the advancements in computer capacity that have made computers both more affordable and more powerful, have made it possible for artificial intelligence to play an increasingly important role in the financial sector. This role can be seen in asset management, algorithmic trading, credit underwriting, and blockchain-based financial services, among other applications. AI4 is integrated into goods and services across a wide range of sectors, including healthcare, autos, consumer items, and the phrase "internet of things" is abbreviated as "IoT."
Machine Learning in Finance
This book discusses the evolution of technical features in decentralized finance and focuses on machine-learning finance in emerging economies. As technological advancement evolves at an unpredictable pace, the financial industry, like every other sector, must adapt accordingly. Furthermore, the rapid expansion of diverse financial products and services is creating new applications and markets. Alongside technological progress, the exploration of complex patterns in vast amounts of data, known as big data, is facilitated by its commonly acknowledged characteristics: volume, variety, veracity, value, and velocity. Overall, machine learning has become crucial in the financial industry, allowing businesses to automate operations, gain insights from data, and make more informed decisions in real time. This edited book covers algorithmic trading, risk management, fraud detection, customer service and personalization, portfolio management, credit scoring, sentiment analysis, and algorithmic pricing. The book connects theoretical concepts with practical real-world applications, benefiting professionals looking to enhance their proficiency in using these methods efficiently. It offers insightful guidance for theorists, market participants, and policymakers by exploring financial theories and practices in light of contemporary machine-learning approaches, with a special emphasis on emerging economies.
Artificial Intelligence for Financial Risk Management and Analysis
Author: Derbali, Abdelkader Mohamed Sghaier
language: en
Publisher: IGI Global
Release Date: 2025-04-08
The revolution of artificial intelligence (AI) impacts various business sectors, including accounting and finance. Machine intelligence is on the rise in human interaction, as novel technologies automate tasks and enhance human capabilities at an increasingly rapid rate. While AI has the potential to assist in the identification and management of risks, such as in financial risk measurement, analysis, and management, the disruptive nature of these emerging technologies introduces new and complex scenarios. Utilizing these technologies to facilitate decision-making processes could result in biased, inequitable, and unreliable decisions, giving rise to concerns regarding data, privacy, and security. Further research is necessary to understand the implications of AI in financial practices. Artificial Intelligence for Financial Risk Management and Analysis delves into the most recent advancements in AI technologies that facilitate risk analysis and decision-making. It examines the potential risks these technologies pose to individuals, businesses, and establishments. Covering topics such as firm management, automation, and long short-term memory (LSTM) networks, this book is an excellent resource for financial advisors, banking professionals, computer scientists, professionals, researchers, academicians, and more.