reports financial technology
Published on : Nov 23, 2022
The "Artificial Intelligence in Fintech Market: Global Analysis and Growth Forecast to 2027" report has been added to ResearchAndMarkets.com's offering.
The adoption of AI systems and techniques in finance is growing rapidly, enabled by the abundance of available data and the increased affordability of computing capacity. AI is increasingly deployed by financial services providers across the financial industry in sectors such as retail and corporate banking, fraud monitoring and detection, natural language processing (NLP), customer service, asset management, trading and insurance. AI is also being deployed in supervisory technology (Suptech) and regulatory technology (Regtech) applications by financial authorities and public sector firms.
The deployment of AI techniques in finance can create efficiencies by minimizing commissions and fees related to transaction execution and by improving productivity levels, leading to higher profitability. Furthermore, the use of automation and technology-enabled cost reduction allows for spending effectiveness, capacity reallocation and improved transparency in decision-making. Applications of AI in financial services accelerate the quality of services and products offered to financial customers, increase the personalization of products, and diversify product offerings. AI helps businesses unlock the potential data insights needed to identify investment strategies and enhance financial inclusions by allowing organizations to analyze the creditworthiness of clientswith minimal credit history.
Increasing digitization in the banking, financial services and insurance (BFSI) industry is one of the essential aspects propelling market growth across the globe. AI in fintech is extensively utilized for operating virtual assistance, sentiment and predictive analysis, debt collection, reporting, and customer behavior analysis. It helps drive efficiency, curtails the chances of human error and processes large volumes of data in a short time span. In addition, AI also helps in the automated and real-time examination of cash, investment and credit accounts for evaluating individual financial health and developing customized insights for future development.
In addition, technological advances such as combining financial technology solutions with ML, big data, evolutionary algorithms and neural networks will also aid market growth. These technologies offer enhanced supervising of financial transactions, speech recognition, risk management and secured network access to financial institutions and banks.
Key Topics Covered:
Chapter 1 Introduction
Chapter 2 Executive Summary and Highlights
Chapter 3 Industry Outlook
Chapter 4 Market Dynamics
Chapter 5 Market Breakdown by Component
Chapter 6 Market Breakdown by Deployment
Chapter 7 Market Breakdown by Application
Chapter 8 Market Breakdown by Region
Chapter 9 Competitive Landscape
Chapter 10 Company Profiles
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