Shweta Anand – författare

This book explores the emergence of artificial intelligence blended with financial concepts as a promising new area in business and technology—financial technology, or fintech.

The book introduces the very relevant concepts of fintech, its financial derivatives, management information systems, and artificial intelligence and provides tools to find solutions to complex problems in the finance and investment domain. The case studies provide firsthand knowledge of real problems faced by the industry and highlights the thought processes in resolution of complex problems.

Topics address the global adoption of fintech, fintech disruptions in the financial sector, the use of machine learning and artificial intelligence to increase the effectiveness of financial trading algorithms, fintech in retail banking and risk management, inbound marketing as well as internal marketing for fintech, fintech in the international education sector, and more.

Both business professionals and those in the technical industry will find this book to be of great use. It will be quite helpful for both professionals and students in the fields of finance and artificial intelligence.

This book explores the emergence of artificial intelligence blended with financial concepts as a promising new area in business and technology—financial technology, or fintech.

The book introduces the very relevant concepts of fintech, its financial derivatives, management information systems, and artificial intelligence and provides tools to find solutions to complex problems in the finance and investment domain. The case studies provide firsthand knowledge of real problems faced by the industry and highlights the thought processes in resolution of complex problems.

Topics address the global adoption of fintech, fintech disruptions in the financial sector, the use of machine learning and artificial intelligence to increase the effectiveness of financial trading algorithms, fintech in retail banking and risk management, inbound marketing as well as internal marketing for fintech, fintech in the international education sector, and more.

Both business professionals and those in the technical industry will find this book to be of great use. It will be quite helpful for both professionals and students in the fields of finance and artificial intelligence.

This book extensively explores the implementation of AI in the risk mitigation process and provides information for auditing, banking, and financial sectors on how to reduce risk and enhance effective reliability.

The applications of the financial industry incorporate vast volumes of structured and unstructured data to gain insight into the financial and non-financial performance of companies. As a result of exponentially increasing data, auditors and management professionals need to enhance processing capabilities while maintaining the effectiveness and reliability of the risk mitigation process. The risk mitigation and audit procedures are processes involving the progression of activities to “transform inputs into output.” As AI systems continue to grow mainstream, it is difficult to imagine an aspect of risk mitigation in the financial industry that will not require AI-related assurance or AI-assisted advisory services. AI can be used as a strong tool in many ways, like the prevention of fraud, money laundering, and cybercrime, detection of risks and probability of NPAs at early stages, sound lending, etc.

Audience

This is an introductory book that provides insights into the advantages of risk mitigation by the adoption of AI in the financial industry. The subject is not only restricted to individuals like researchers, auditors, and management professionals, but also includes decision-making authorities like the government. This book is a valuable guide to the utilization of AI for risk mitigation and will serve as an important standalone reference for years to come.

This book extensively explores the implementation of AI in the risk mitigation process and provides information for auditing, banking, and financial sectors on how to reduce risk and enhance effective reliability.

The applications of the financial industry incorporate vast volumes of structured and unstructured data to gain insight into the financial and non-financial performance of companies. As a result of exponentially increasing data, auditors and management professionals need to enhance processing capabilities while maintaining the effectiveness and reliability of the risk mitigation process. The risk mitigation and audit procedures are processes involving the progression of activities to “transform inputs into output.” As AI systems continue to grow mainstream, it is difficult to imagine an aspect of risk mitigation in the financial industry that will not require AI-related assurance or AI-assisted advisory services. AI can be used as a strong tool in many ways, like the prevention of fraud, money laundering, and cybercrime, detection of risks and probability of NPAs at early stages, sound lending, etc.

Audience

This is an introductory book that provides insights into the advantages of risk mitigation by the adoption of AI in the financial industry. The subject is not only restricted to individuals like researchers, auditors, and management professionals, but also includes decision-making authorities like the government. This book is a valuable guide to the utilization of AI for risk mitigation and will serve as an important standalone reference for years to come.