Global analysis and growth forecast to 2027

Global analysis and growth forecast to 2027

NEW YORK, 16 November 2022 /PRNewswire/ —

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

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– AI-based products that are in the pilot phase or are live for demonstration purposes are not included in the calculation of the total market size.
– The market size includes the market for AI in terms of fintech components, distribution, 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 assessed in the report.

The report includes:
– 47 data tables and 24 additional tables
– A comprehensive overview and up-to-date analysis of current and future global markets for artificial intelligence (AI) in the financial industry
– Analyzes of the global market trends, with market revenue data for 2021, estimates for 2022, 2023 and 2025, and projections for 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, distribution, application and region
– Assessment of the most important growth-driving factors and constraints that will shape the market for artificial intelligence in financial services, as a basis for estimating demand over the next five years (2022-2027)
– Identifying the companies best positioned to meet this demand due to or in connection with their proprietary technologies, product launches, M&A deals and other market strategic advantages
– Coverage of the technological, financial and business assessments of AI in the Fintech market, with analysis and growth forecasts through 2027
– Analysis of the supplier landscape and the global company share analysis of the companies based on their segment revenues
– Descriptive company profiles of the leading global players, including Affirm Inc., IBM Corp., Microsoft Corp. and Salesforce.com Inc.

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Summary:
The use of AI systems and techniques in finance is growing rapidly, enabled by the abundance of available data and the increased affordable computing capacity. AI is increasingly being deployed by financial service providers in the financial services industry in sectors such as retail and corporate banking, fraud monitoring and detection, naturally 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 companies.

Deploying AI techniques in finance can create efficiencies by minimizing commissions and fees associated with transaction execution and by improving productivity levels, leading to higher profitability. Furthermore, the use of automation and technology-enabled cost reduction allows cost efficiency, capacity redistribution and increased 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 companies unlock the potential data insights needed to identify investment strategies and improve financial inclusion by allowing organizations to analyze the creditworthiness of customers with minimal credit histories.

The global artificial intelligence in fintech market was valued at REDACTED in 2021 and will reach REDACTED by 2027. The market is expected to enjoy a REDACTED compound annual growth rate (CAGR) over the forecast period 2022-2027.

Increasing digitization in the banking, finance and insurance (BFSI) industry is one of the essential aspects driving market growth worldwide. AI in fintech is largely used for the operation of virtual assistance, sentiment and predictive analysis, debt collection, reporting and customer behavior analysis.

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It helps increase efficiency, reduces the chances of human error and processes large amounts of data in a short time. In addition, AI also helps with automated and real-time examination of cash, investment and credit accounts to evaluate individual financial health and develop 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 contribute to market growth. These technologies offer improved monitoring of financial transactions, speech recognition, risk management and secured network access to financial institutions and banks.

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