Artificial Intelligence in Fintech Market: Global Analysis and Growth Forecast to 2027

NEW YORK, Nov. 16, 2022 /PRNewswire/ -- 

Report Scope:
The scope of the report includes the global market of commercially deployed AI solutions and services in the financial industry.



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- AI-based products that are in the pilot phase or are live for demonstration purposes have not been considered in the calculation of the overall market size.
- The market size includes the market for AI in terms of fintech components, deployment, application and organization size.
- The final market estimates and forecasts from industry experts are also aligned with the size of the global market in the report.
- AI-based software, solutions and services are not considered in the report.

Report Includes:
- 47 data tables and 24 additional tables
- A comprehensive overview and up-to-date analysis of the current and future global markets for artificial intelligence (AI) in the financial services industry
- Analyses of the global market trends, with market revenue data for 2021, estimates for 2022, 2023 and 2025, and projections of compound annual growth rates (CAGRs) through 2027
- Global market outlook and estimation of the actual market size for AI in Fintech, revenue forecast, and corresponding market share analysis based on component, deployment, application, and region
- Assessment of the key growth driving factors and constraints that will shape the market for AI in financial services, as the basis for projecting demand over the next five years (2022-2027)
- Identification of the companies best positioned to meet this demand owing to or in conjunction with their proprietary technologies, product launches, M&A deals, and other market strategic advantages
- Coverage of the technological, economic, and business considerations of the AI in Fintech market, with analyses and growth forecasts through 2027
- Analysis of the vendor landscape and the global company share analysis of the companies based on their segmental revenues
- Descriptive company profiles of the leading global players, including Affirm Inc., IBM Corp., Microsoft Corp. and Salesforce.com Inc.

Summary:
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, fraudmonitoring 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.

The global market for AI in fintechwas valued at REDACTED in 2021 andwill reach REDACTED by 2027.The market is expected to enjoy aREDACTED compound annual growth rate (CAGR) over the forecast period of 2022-2027.

Increasing digitization in the banking, financial services and insurance (BFSI) industry is one of the essentialaspects propelling market growth across the globe.AI in fintech is extensively utilized foroperating virtual assistance, sentiment and predictive analysis, debt collection, reporting, and customerbehavior 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 forevaluating individual financial health and developing customized insights for future development.

In addition, technological advances such as combining financial technology solutionswithML, big data, evolutionary algorithms and neural networkswill also aid market growth. These technologies offer enhanced supervising of financial transactions, speech recognition, riskmanagement and secured network access to financial institutions and banks.

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