USD 20.15 Billion
Report ID:
SQMIG40A2015 |
Region:
Global |
Published Date: June, 2024
Pages:
197
|Tables:
122
|Figures:
77
Global Artificial Intelligence (AI) in BFSI Market size was valued at USD 20.15 Billion in 2022 and is poised to grow from USD 26.24 Billion in 2023 to USD 246.04 Billion by 2031, growing at a CAGR of 32.5% in the forecast period (2024-2031).
BFSI companies around the world are focusing on enhancing their business operations through deployment of AI solutions and services. High investments in the development of novel AI solutions for BFSI applications coupled with increasing emphasis on improving profitability are also slated to drive artificial intelligence (AI) in BFSI market growth going forward. Increasing demand for better risk and compliance management to avoid frauds is also expected to promote the use of AI solutions in the BFSI industry over the coming years. AI will also allow BFSI companies to make data-driven decisions and provide personalized customer experiences that will help them maximize their business scope on a global level. However, high costs of implementation and data privacy and security concerns are estimated to hinder AI adoption in the BFSI space through 2031 and beyond.
Global Market Size
USD 20.15 Billion
Largest Segment
Risk Management
Fastest Growth
Chatbot
Growth Rate
32.5% CAGR
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Global artificial intelligence (AI) in banking, financial services, and insurance (BFSI) market is segmented into component, application, technology, end-use, and region. By component, the market is segmented into hardware, software, and services. By technology, it is segmented into machine learning, natural language processing, generative AI, computer vision, and others. By application, the market is segmented into chatbot, cyber security, risk management, predictive analytics, data collection & analysis, and others. By end use, the market is segmented into banking, financial services, and insurance. By region, the market is segmented into North America, Asia Pacific, Europe, Latin America, and MEA.
Analysis by Application
Risk management takes precedence when it comes to use of AI in BFSI industry allowing this segment to hold a dominant share. Growing sophistication of frauds and attacks on finance organizations has led to a high adoption of AI-powered risk and compliance management solutions that can proactively manage risks and threats. Implementation of stringent data security and privacy regulations for the BFSI industry are also projected to promote the use of AI for risk management applications in the future.
Meanwhile, the use of chatbots to enhance customer experience is projected to increase at a rapid pace over the coming years. Growing deployment of AI-enabled chatbots to provide customer service with faster response times is projected to help this segment expand in the future. AI chatbots can also be trained on individual data to create more personal responses and provide a more fulfilling customer interaction. Low costs and high quality of support are key benefits of AI chatbots that are helping this segment bolster market growth at a notable pace.
Analysis by Technology
Machine learning is estimated to be the most widely used AI sub technology in the BFSI industry. High use of this technology to train AI models and use of the same to derive meaningful insights from raw unstructured data will also contribute to the high market share of this segment. Machine learning can also manage document labelling and tagging to improve document management capabilities of BFSI companies. Investing in this segment can never go wrong for any artificial intelligence (AI) in banking, financial services, and insurance (BFSI) market player.
Use of natural language processing in the BFSI industry is projected to increase at a rapid pace across the study period and beyond. Natural language processing (NLP) can be used to perform sentiment analysis and reduce errors in the BFSI space. The technology is also being used to improve communication of companies with their customers as more and more customer service becomes dependent on chatbots. The technology can also be used to detect fraud in insurance claim processes.
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The presence of leading commercial banks and financial institutions in the North American region allow it to emerge as a leader in the global AI in BFSI market. High adoption of AI technologies by multiple BFSI organizations in this region and growing investments in AI integration are helping the region maintain its dominance. Moreover, the presence of strict regulatory framework is also necessitating the use of risk and compliance management solutions powered by advanced technologies in countries such as Canada and the United States.
Rise of digital banking in the Asia Pacific region has helped this region bag the title of the fastest-expanding market for AI in BFSI. Evolving consumer preferences, high use of digital banking solutions, and growing accessibility of people for different BFSI services are all boosting AI in BFSI adoption in this region. Japan, India, China, and South Korea are noteworthy markets for artificial intelligence (AI) in banking, financial services, and insurance (BFSI) companies looking to make a mark in this region. Growing use of mobile banking and demand for more personalized financial services will also create new opportunities for AI in BFSI providers going forward.
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Drivers
Growing Demand for Better Customer Experience
Maintaining Regulatory Compliance
Restraints
Integration with Legacy Infrastructure
Data Privacy and Security Concerns
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The global artificial intelligence in BFSI market is highly opportune as the use of AI in this industry is in its initial stages. New companies have a good chance of penetrating and succeeding in this market provided they come up with unique AI solutions for different BFSI applications. Integration of AI with other advanced technologies such as blockchain will also create new opportunities for AI in BFSI market players. Creating personalized finance recommendations and user experience will be a key trend that all AI in BFSI providers will be targeting in the long run.
Top Player’s Company Profiles
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SkyQuest’s ABIRAW (Advanced Business Intelligence, Research & Analysis Wing) is our Business Information Services team that Collects, Collates, Correlates, and Analyses the Data collected by means of Primary Exploratory Research backed by robust Secondary Desk research.
As per SkyQuest analysis, artificial intelligence (AI) in banking, financial services, and insurance (BFSI) is projected to be driven by rising demand for better customer experience, a growing need for better risk management, and advancements in AI technology. However, the complexity of AI solutions and data privacy and security concerns are slated to slow down artificial intelligence (AI) in banking, financial services, and insurance (BFSI) market growth in the future. Evolving consumer preferences and the adoption of digital banking services are slated to help Asia Pacific remain the fastest-growing market in the world. AI in BFSI providers should target the personalization trend if they want to stay relevant in the long run.
Report Metric | Details |
---|---|
Market size value in BFSI | USD 20.15 Billion |
Market size value in 2031 | USD 246.04 Billion |
Growth Rate | 32.5% |
Base year | 2023 |
Forecast period | 2024-2031 |
Forecast Unit (Value) | USD Billion |
Segments covered |
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Regions covered | North America (US, Canada), Europe (Germany, France, United Kingdom, Italy, Spain, Rest of Europe), Asia Pacific (China, India, Japan, Rest of Asia-Pacific), Latin America (Brazil, Rest of Latin America), Middle East & Africa (South Africa, GCC Countries, Rest of MEA) |
Companies covered |
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Customization scope | Free report customization with purchase. Customization includes:-
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Executive Summary
Market overview
Parent Market Analysis
Market overview
Market size
KEY MARKET INSIGHTS
COVID IMPACT
MARKET DYNAMICS & OUTLOOK
Market Size by Region
KEY COMPANY PROFILES
For the Artificial Intelligence (AI) in Banking, Financial Services, and Insurance (BFSI) Market, our research methodology involved a mixture of primary and secondary data sources. Key steps involved in the research process are listed below:
1. Information Procurement: This stage involved the procurement of Market data or related information via primary and secondary sources. The various secondary sources used included various company websites, annual reports, trade databases, and paid databases such as Hoover's, Bloomberg Business, Factiva, and Avention. Our team did 45 primary interactions Globally which included several stakeholders such as manufacturers, customers, key opinion leaders, etc. Overall, information procurement was one of the most extensive stages in our research process.
2. Information Analysis: This step involved triangulation of data through bottom-up and top-down approaches to estimate and validate the total size and future estimate of the Artificial Intelligence (AI) in Banking, Financial Services, and Insurance (BFSI) Market.
3. Report Formulation: The final step entailed the placement of data points in appropriate Market spaces in an attempt to deduce viable conclusions.
4. Validation & Publishing: Validation is the most important step in the process. Validation & re-validation via an intricately designed process helped us finalize data points to be used for final calculations. The final Market estimates and forecasts were then aligned and sent to our panel of industry experts for validation of data. Once the validation was done the report was sent to our Quality Assurance team to ensure adherence to style guides, consistency & design.
Customization Options
With the given market data, our dedicated team of analysts can offer you the following customization options are available for the Artificial Intelligence (AI) in Banking, Financial Services, and Insurance (BFSI) Market:
Product Analysis: Product matrix, which offers a detailed comparison of the product portfolio of companies.
Regional Analysis: Further analysis of the Artificial Intelligence (AI) in Banking, Financial Services, and Insurance (BFSI) Market for additional countries.
Competitive Analysis: Detailed analysis and profiling of additional Market players & comparative analysis of competitive products.
Go to Market Strategy: Find the high-growth channels to invest your marketing efforts and increase your customer base.
Innovation Mapping: Identify racial solutions and innovation, connected to deep ecosystems of innovators, start-ups, academics, and strategic partners.
Category Intelligence: Customized intelligence that is relevant to their supply Markets will enable them to make smarter sourcing decisions and improve their category management.
Public Company Transcript Analysis: To improve the investment performance by generating new alpha and making better-informed decisions.
Social Media Listening: To analyze the conversations and trends happening not just around your brand, but around your industry as a whole, and use those insights to make better Marketing decisions.
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Report ID: SQMIG40A2015
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