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| Report Code: A03986 | Pages: 321 | ||
| Tables: 168 | Charts: 75 |
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The global AI and advance machine learning in BFSI market size was valued at $7.66 billion in 2020, and is projected to reach $61.24 billion by 2030, growing at a CAGR of 23.1% from 2021 to 2030. Artificial intelligence in finance is transforming the BFSI industry as AI is helping the financial industry to streamline and optimize processes ranging from credit decisions to quantitative trading and financial risk management. In addition, advanced machine learning technology is used to help organizations to improve customer experience, services, and to optimize budgets. Furthermore, it provides solutions to process automation to replace routine manual work in most cases. In addition, AI and advanced machine learning help in reducing the credit default frauds by monitoring transactions to detect suspicious transactions with compliance concerns.
COVID-19 pandemic is expected to positively impact the growth rate of the artificial intelligence and machine learning in BFSI market, owing to increased shift towards work from home culture across banks & fintech agencies and rapid adoption of artificial intelligence and machine learning tools in banks and fintech organizations for performing critical jobs across the globe.
Improvement in data collection technology among the banks and financial institutions positively impacts the AI and advance machine learning in BFSI market growth. In addition, rise in investment by BFSI companies in AI and machine learning and customer preferences for personalized financial services are some of the important factors that boost growth of the AI and advance machine learning in BFSI market across the globe. However, factors such as higher deployment cost of AI & advance machine learning and lack of skilled labor are limiting the growth of the AI and advance machine learning in BFSI market. Conversely, surge in adoption of modern applications in BFSI sector is expected to offer remunerative opportunities for the expansion of the market during the forecast period.
The global AI and advance machine learning in BFSI market is segmented into component, deployment model, enterprise size, application and region. Depending on component, the AI and advanced machine learning in BFSI market is segregated into solution and services. On the basis of deployment model, it is categorized into on-premise and cloud. Depending on enterprise size, it is fragmented into large enterprises and SMEs. Based on application, the market is divided into fraud & risk management, customer segmentation, sales & marketing, digital assistance and others. Region wise, the AI and advance machine learning in BFSI market is studied across North America, Europe, Asia-Pacific, and LAMEA.
The fraud & risk management segment is expected to garner a significant AI and advance machine learning in BFSI market share in 2020, owing to surge in need for machine learning technologies by banks and financial institution in their fraud detection system and implementing of an AI-driven verification model across the fintech and banks. However, the digital assistance segment is expected to grow at the highest rate during the forecast period, owing to growing need of digital assistance in banks and fintech to solve critical customer queries.
Region wise, North America region is contributed largest market share in 2020, owing to early adoption of machine learning solutions among the banking sector and various government initiatives for supporting SMEs to adopt artificial intelligence solution. However the Asia-Pacific region is expected provides lucrative opportunity to boost the growth of the AI and advanced machine learning in BFSI market owing to rapid adoption of analytics solutions by banks across China, Japan and India to analyze their customer behavior and prevent online frauds.
The report focuses on the growth prospects, restraints, and trends of global AI and advance machine learning in BFSI market analysis. The study provides Porter’s five forces analysis to understand the impact of various factors such as bargaining power of suppliers, competitive intensity of competitors, threat of new entrants, threat of substitutes, and bargaining power of buyers on global AI and advanced machine learning in BFSI market.
The key players operating in the global AI and advanced machine learning in BFSI industry include Amazon Web Services Inc., BigML, Inc, Cisco Systems, Inc., Fair Isaac Corporation, Hewlett Packard Enterprise Development LP, International Business Machines Corporation, Microsoft Corporation, RapidMiner, Inc., SAP SE and SAS Institute Inc. These players have adopted various strategies to increase their market penetration and strengthen their foothold in the competitive AI & advance machine learning in BFSI industry.
With alarming increase in COVID-19 patients, various governments have implemented lockdown, which, in turn, increased the number of digital banking and access of premiums. Furthermore, with rise in digitization among both financial institutes & end users and surge in demand for advanced machine learning technology among fintech, transaction delays & need to increase the speed of payment processing drive the growth of the AI and advance machine learning in BFSI analysis in the pandemic situation.
For instance, according to a survey of Prudential Regulation Authority (PRA) by Bank of England in August 2020, around 40% of respondents reported an increase in the importance of machine learning and data science for future operations, and a further 10% of banks reported a large increase. In addition, none of the banks reported a decrease in the importance of machine learning and data science. Furthermore, around 35% of banks reported that machine learning and data science had a positive impact on technologies that support remote working among employees and on their overall security provided for ML projects. In addition, the pandemic has accelerated the use of ML-powered tools to manage a sudden increase in customer enquiries. Thus, number of such development across the globe are anticipated to provide lucrative opportunity for the expansion of the AI and advance machine learning in BFSI market.
BFSI companies are increasing investment in machine learning and AI solutions to transform the management process of fintech and to provide better services to end users. In addition, with incase in complexity and competition in the BFSI sector, the demand for industry-specific solutions increased to meet its goals. Thus, to meet the requirement of customers, various banking institutes and fintech are investing in AI solution, which, in turn, drives the growth of the market. Furthermore, AI and machine learning can assist financial institutes at various stages of risk management process ranging from identifying risk exposure, measuring, estimating, and assessing its effects. In addition, BFSI companies are adopting and developing machine learning techniques to analyze large volume of data and to deliver valuable insights to customers. Moreover, increase in investments in AI and advanced machine learning by fintech & banks to enhance the automation process and to offer more streamlined and personalized customer experience propels the growth of the market. In addition, major financial institutes such as Bank of America, JPMorgan, and Morgan Stanley are investing heavily in machine learning technology to develop automated investment advisors and train systems to detect flags such as money laundering techniques, which can be prevented by financial monitoring, thus augmenting the growth of the market.
End users are increasingly preferring personalized financial services, owing to surge in adoption of chatbots among banks and increase in competition among the BFSI companies for garnering maximum market share. Various BFSI companies are providing budget management apps powered by machine learning, which help customers to achieve their financial targets and improve their money management process, thus driving the growth of the market.
Furthermore, robo-advisors are one of the other rapidly emerging trends in personalized financial services, as they specifically target investors with limited resources such as individuals and small- to medium-sized businesses for managing their funds. In addition, machine learning-based robo-advisors can apply traditional data processing techniques to create financial portfolios and solutions such as trading, investments, and retirement plans for their users. Moreover, with rise of usage-based insurance machine learning and AI technologies are helping to calculate the premium suitable for each individual, which, in turn, propels the growth of the AI and advanced machine learning in BFSI market.
Key Benefits For Stakeholders
Key Market Segments
By Component
By Deployment Model
By Enterprise Size
By Application
By Region
Key Market Players
AI and Advance Machine Learning in BFSI Market Report Highlights
| Aspects | Details |
|---|---|
| By COMPONENT |
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| By DEPLOYMENT MODEL |
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| By ENTERPRISE SIZE |
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| By APPLICATION |
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| By Region |
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| Key Market Players | RapidMiner, Inc., FAIR ISAAC CORPORATION, SAP SE, Amazon Web Services, Inc., Cisco System Inc., BigML, Inc., HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP, .INTERNATIONAL BUSINESS MACHINES CORPORATION, MICROSOFT CORPORATION, SAS INSTITUTE INC. |
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The adoption of AI and advance machine learning in BFSI solutions has increased over the years to help organizations monitor production processes and to provide enhanced customer services. In addition, AI and advance machine learning in BFSI technology is being used across a number of applications to help drive productivity, improve efficiency, and save people time and organizational funds. Furthermore, AI and advance machine learning in BFSI tools is used to clean data sets, give predictions, improve decision-making, and to respond to customer service needs, which are expected to fuel the market growth. In addition, surge in adoption of cloud as well as mobile applications is expected to drive the growth of the market.
Key providers of AI and advance machine learning in BFSI market such as SAP SE, International Business Machines Corporation, and Microsoft Corporation account for a significant share in the market. For instance, Saxo Bank, a leading Danish investment bank, managed to drastically reduce the time it takes to onboard new customers and get them trading on its platform, owing to investments in data science and advanced machine learning technologies by automating repeating and time-consuming tasks and provide better time management of workers.
Furthermore, financial institutes are collaborating with AI and machine learning companies to enhance their existing AI system for better and secure systems. For instance, in August 2021, RBL Bank partnered with Amazon Web Services (AWS) to strengthen its AI-powered banking solutions and drive digital transformation at the bank, adding significant value to the bank’s innovative offerings, saving costs, and tightening risk controls. In addition, it is leveraging Amazon Textract, a machine learning service that automatically extracts text, handwriting, and data from scanned documents, across the bank’s risk and operations divisions to analyze documents such as financial statements, stock statements, and stock audit reports to predict default risk.
Moreover, many open banking platforms are leveraging solutions from financial technology providers to improve their management technology. For instance, in September 2020, Open banking platform, Tink leveraged open banking technology from Enel to develop digital financial solutions for its clients in Italy and Europe. With the agreement, Tink will be able to support its clients in the daily management of their finances, with an innovative and engaging solution that uses machine learning to provide tailored and personalized advice. Thus, such developments across the globe drive the growth of the market.
A. The AI and advance machine learning in BFSI Market is estimated to grow at a CAGR of 23.1% from 2021 to 2030.
A. The AI and advance machine learning in BFSI Market is projected to reach $61.24 billion by 2030.
A. To get the latest version of sample report
A. Factors such as increase in investments in AI and advanced machine learning by fintech & banks to enhance the automation process and to offer more streamlined and personalized customer experience drives the growth of the AI and advance machine learning in BFSI market
A. The key players profiled in the report include Amazon Web Services Inc., BigML, Inc, Cisco Systems, Inc., Fair Isaac Corporation, Hewlett Packard Enterprise Development LP, International Business Machines Corporation, Microsoft Corporation, RapidMiner, Inc., SAP SE and SAS Institute Inc and many more.
A. On the basis of top growing big corporations, we select top 10 players.
A. The AI and advance machine learning in BFSI Market is segmented on the basis of component, deployment model, enterprise size, application and region.
A. The key growth strategies of AI and advance machine learning in BFSI market players include product portfolio expansion, mergers & acquisitions, agreements, geographical expansion, and collaborations.
A. Solution Segment holds a dominant position throughout the forecast period.
A. Cloud segment will grow at a highest CAGR of 23.9% during 2021 - 2030.
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