Registering a CAGR of 24.77% over the forecast period of 2022-2027, the global Cloud AI in Fintech size is anticipated to reach the market value of USD 26.67 Billion in the year 2027 from USD 7.91 Billion in the year 2022.
Cloud AI in Fintech Overview
Artificial Intelligence (AI) has taken the tech world by storm, allowing companies to automate their high-value and complicated processes. The reason to make a shift towards machine learning is also motivated by the reduction in cost, growing efficiency, reducing error, and improved customer experience. The AI in fintech is majorly driven by credit card fraud detection. With the help of a Generative Adversarial Network, AI can spot the difference between real data and hacked data in each transaction and send alerts to banks. The biggest challenge with AI is the sensitive issue of data privacy and security, which most fintech companies are facing. The fintech sector is governed by strict compliance to regulations and governance since any data breach or security failure could be disastrous.
Who are the Major Players in Cloud AI in Fintech Market?
The global Cloud AI in Fintech includes the identification and analysis of the various market participants competing in the global market. Prominent competitors include ABigML, Inc. (US), Cisco Systems, Inc. (US), FICO (US), Hewlett Packard Enterprise Development LP (US), RapidMiner, Inc. (US), SAP SE (Germany), SAS Institute Inc. (US), Microsoft (US), Google, LLC (US), Salesforce.com Inc. (US), IBM (US), Intel Corporation (US), Amazon Web Services, Inc. (US), Inbenta Technologies (US), IPsoft (US), Nuance Communications (US), ComplyAdvantage (UK)
Industry News and Development:
15 September 2021: IBM announced a new agreement with Caixa Bank, one of the largest banks in Europe, and launched a new IBM Cloud Multizone Region (MZR) in Spain to support clients across the region as they adopt hybrid cloud strategies. This enables Caixa Bank to reinforce its innovative vision by evolving its core applications and improving efficiencies with increased availability and resiliency.
July 28, 2021 IBM and SAP SE today announced that SAP intends to onboard two of its finance and data management solutions to IBM Cloud for Financial Services to help accelerate IBM cloud adoption within the financial services industry. The collaboration will be designed to help the companies address the industry's stringent compliance, security and resiliency requirements, while supporting business transformation and innovation for financial services institutions.
What are the major Applications, Types and Regions for Cloud AI in Fintech Market?
Cloud AI in Fintech is segmented based on the Type, Applications and Regions.
By Type, it is segmented into
By Applications, it is segmented into
- Chatbots
- Credit Scoring
- Quantitative and Asset Management
- Fraud Detection
- Others
Cloud AI in Fintech Market Regional Analysis
North America is one of the largest and most advanced markets for AI in the world. The region has also registered the maximum adoption of AI in Fintech solutions, due to the strong economy, robust presence of prominent AI software and system suppliers, and combined investment by government and private organizations for the development and growth of R&D activities Moreover, the region accounts for a significant share of the millennial population, particularly the United States. Millennials have a clear preference for accomplishing tasks through digital applications and services that fintech companies are better at providing than banks in terms of speed and personalization. According to the US Census Bureau population estimates, as of 2019, there are around 72.1 million millennials. However, according to Digital Banking Report 2019, the adoption rates of fintech services in Canada (50%) and the United States (46%) are some of the lowest.
- North America
- Europe
- Germany
- France
- UK
- Italy
- Spain
- Rest of Europe
- Asia-Pacific
- China
- Japan
- India
- Australia
- South Korea
- Rest of Asia-Pacific
- Rest of the World
- Middle East & Africa
- Latin America
What is our Cloud AI in Fintech Market report scope?
Report Attributes
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Report Details
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Forecast Period 2022 to 2027 CAGR
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CAGR of 24.77% during the review period (2022 to 2027).
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By Type
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By Application
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- Chatbots
- Credit Scoring
- Quantitative and Asset Management
- Fraud Detection
- Others
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By Companies
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BigML, Inc. (US), Cisco Systems, Inc. (US), FICO (US), Hewlett Packard Enterprise Development LP (US), RapidMiner, Inc. (US), SAP SE (Germany), SAS Institute Inc. (US), Microsoft (US), Google, LLC (US), Salesforce.com Inc. (US), IBM (US), Intel Corporation (US), Amazon Web Services, Inc. (US), Inbenta Technologies (US), IPsoft (US), Nuance Communications (US), ComplyAdvantage (UK)
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Regions Covered
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- North America
- Europe
- Asia-Pacific
- Rest of the World
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Countries Covered
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- US
- Canada
- Germany
- France
- UK
- Italy
- Spain
- Rest of Europe
- China
- Japan
- India
- Australia
- South Korea
- Rest of Asia-Pacific
- Middle East & Africa
- Latin America
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Base Year
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2022
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Historical Year
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2017 to 2021
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Forecast Year
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2022 to 2027
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Number of Pages
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115
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Customization Available
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Yes, the report can be customized as per your needs
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Key Takeaways from this Cloud AI in Fintech Report
- Evaluate Cloud AI in Fintech market potential through analyzing growth rates (CAGR %), Volume (Units), and Value ($M) data given at country level - for product types, end-use applications, and by different industry verticals.
- Understand the different dynamics influencing the market - growth driving factors, specific challenges, and hidden opportunities.
- Get in-depth insights on your competitor's performance – revenue, shares, business strategies, financial benchmarking, product benchmarking, SWOT analysis and more.
- Analyze the sales and distribution channels across geographies to enhance top-line revenues.
- Understand the demanding supply chain with a deep dive on the value augmentation at each, in order to optimize value and bring efficiencies in your processes.
- Get a quick outlook on the Cloud AI in Fintech market entropy - M&As, deals, partnerships, product launches of all key players for the past 5 years.
- Evaluate the import-export statistics, supply-demand, and competitive landscape for more than the top 20 countries globally for the market.
Frequently Asked Questions
What is the study period of this market?
The Cloud AI in Fintech Market is studied from 2017 - 2027.
What is the growth rate of Cloud AI in Fintech Market?
The Cloud AI in Fintech Market is growing at a CAGR of 24.77% over the next 5 years.
Who are the leading key players in Cloud AI in Fintech Market?
BigML, Inc. (US), Cisco Systems, Inc. (US), FICO (US), Hewlett Packard Enterprise Development LP (US), RapidMiner, Inc. (US), SAP SE (Germany), SAS Institute Inc. (US), Microsoft (US), Google, LLC (US), Salesforce.com Inc. (US), IBM (US), Intel Corporation (US), Amazon Web Services, Inc. (US), Inbenta Technologies (US), IPsoft (US), Nuance Communications (US), ComplyAdvantage (UK)
What regions regions does this Cloud AI in Fintech Market report covers?
North America (the United States, Canada, and Mexico)
Europe (Germany, France, UK, Russia, and Italy)
Asia-Pacific (China, Japan, Korea, India, and Southeast Asia)
South America (Brazil, Argentina, Colombia, etc.)
The Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria, and South Africa)
What are the significant types of Cloud AI in Fintech Market?
Solutions, Services
What are the significant Applications of Cloud AI in Fintech Market?
Chatbots, Credit Scoring, Quantitative and Asset Management, Fraud Detection, Others
All our reports are custom made to your company's needs to a certain extent, we do provide 5 free consulting hours along with the purchase of each report, and this will allow you to request any additional data to customize the report as your needs.
SECONDARY RESEARCH
Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia etc. Paid data sources include third party authentic industry databases.
PRIMARY RESEARCH
Once data collection is done through secondary research, primary interviews are conducted with different stakeholders across the value chain like manufacturers, distributors, ingredient/input suppliers, end customers and other key opinion leaders of the industry. Primary research is used both to validate the data points obtained from secondary research and to fill in the data gaps after secondary research.
MARKET ENGINEERING
The market engineering phase involves analyzing the data collected, market breakdown and forecasting. Macroeconomic indicators and bottom-up and top-down approaches are used to arrive at a complete set of data points that give way to valuable qualitative and quantitative insights. Each data point is verified by the process of data triangulation to validate the numbers and arrive at close estimates.
EXPERT VALIDATION
The market engineered data is verified and validated by a number of experts, both in-house and external.
REPORT WRITING/ PRESENTATION
After the data is curated by the mentioned highly sophisticated process, the analysts begin to write the report. Garnering insights from data and forecasts, insights are drawn to visualize the entire ecosystem in a single report.
