Global AI in Fintech Market Size, Industry Analysis By Segmentations, Top Key Players, Trends, Future Development & Forecast 2024-2035
- PUBLISHED ON
- 2/24/2023
- NO OF PAGES
- 216
- CATEGORY
- Banking & Finance
Market Overview:
The global AI in Fintech Market was valued at USD 10.23 billion in 2022, and is projected to reach USD 65.30 billion by 2032 at a CAGR of 22.0% from 2022 to 2032.
The AI in Fintech market refers to the use of Artificial Intelligence (AI) technologies and applications in the financial services industry, including banking, insurance, and investment management. AI in Fintech can help improve the speed, accuracy, and efficiency of financial services, as well as enhance customer experience and reduce costs. With respect to the Silicon Valley Bank (SVB) bank fallout, AI in Fintech can be leveraged to improve risk management practices in the banking sector. For instance, AI can be used to identify potential risks and fraudulent activities in real-time, thereby preventing similar incidents from occurring in the future. Additionally, AI can help automate compliance and regulatory reporting, which is a critical issue for banks like SVB.
For tech startups, AI in Fintech can help improve the efficiency of their financial operations, including accounting, invoicing, and payment processing. AI can also be leveraged to analyze customer data and behavior, which can help startups personalize their offerings and improve customer engagement. Overall, the AI in Fintech market is expected to grow significantly in the coming years, driven by advances in AI technology and increasing demand for digital financial services. Fintech companies, including SVB, are likely to continue investing in AI to improve their operations, enhance customer experience, and stay competitive in the market.
The main driver of AI in Fintech is the need for increased efficiency, speed, and accuracy in financial services
The use of AI in Fintech is driven by several factors, including the need to improve the speed and accuracy of financial services. With the increasing demand for digital financial services, financial institutions are leveraging AI technologies to automate manual processes, reduce errors, and increase efficiency. For example, AI-powered chatbots can handle customer inquiries and complaints quickly and accurately, without the need for human intervention. Another driver of AI in Fintech is the desire to improve customer experience. With the rise of digital financial services, customers expect personalized and seamless experiences across multiple channels. AI can be used to analyze customer data and behavior, providing insights that can be used to personalize offerings and improve engagement. Finally, the need to reduce costs is also driving the adoption of AI in Fintech. By automating processes and reducing the need for human labor, financial institutions can cut costs and improve their bottom line. This is especially important for fintech startups, which operate on tight budgets and need to be efficient to stay competitive in the market.
Overall, the main driver of AI in Fintech is the desire to improve financial services, reduce costs, and enhance customer experience through the use of advanced technologies.
Segmentation:
By Component
· Solution
· Services
By Deployment Mode
· On-premise
· Cloud
By Application
· Virtual Assistants (Chatbots)
· Business Analytics and Reporting
· Customer Behavioral Analytics
Geography:
North America currently dominates the AI in Fintech market, accounting for a significant share of the global market. This is due in part to the presence of leading Fintech companies and tech startups, including Silicon Valley Bank (SVB) and other major players in the United States. SVB, as a leading financial institution in the Fintech industry, has been at the forefront of leveraging AI to enhance its services and customer experience. Its adoption of AI technologies has helped the bank to improve risk management practices, automate compliance reporting, and personalize its offerings to customers.
In addition to SVB, North America has a large and growing Fintech ecosystem, with a diverse range of companies operating in the space. This includes established players like PayPal and Square, as well as newer startups focused on areas such as digital banking, robo-advisory, and blockchain-based financial services.
Impact of COVID-19 on the global AI in Fintech Market:
The COVID-19 pandemic has had a significant impact on the AI in Fintech market. The pandemic has accelerated the shift towards digital financial services, as more people are using online and mobile banking services to manage their finances. This has led to increased demand for AI-powered financial services, such as chatbots and robo-advisors, which can provide 24/7 support to customers. The pandemic has also changed customer behavior and preferences, with many people now looking for contactless payment options and digital financial services that can be accessed remotely. This has led to a surge in demand for AI-powered fraud detection and risk management solutions to ensure that transactions are secure and reliable. Financial institutions are increasingly adopting AI technologies to improve efficiency, automate processes, and reduce costs in response to the economic challenges posed by the pandemic. This includes using AI for credit risk assessment, fraud detection, and regulatory compliance reporting. However, the pandemic has also created the challenges for the implementation and adoption of AI in Fintech, including disruptions in supply chains, budget cuts, and a lack of skilled talent. As a result, some AI projects have been delayed or scaled back.
Impact of the Russia-Ukraine War on the global AI in Fintech Market:
The Russia-Ukraine war has the potential to impact the AI in Fintech market in several ways, although the exact extent of the impact is difficult to predict. Here are some of the potential ways that the conflict could affect the market: Increased risk and uncertainty: The conflict could create increased risk and uncertainty for financial institutions, as well as for customers and investors. This could lead to a flight to safety, with investors seeking out more stable and secure financial services, and could also lead to increased demand for AI-powered risk management and fraud detection solutions; Geopolitical tensions: The conflict could also create geopolitical tensions that could impact the global economy and financial markets. This could lead to increased volatility and instability, which could create challenges for financial institutions and could also impact the adoption of AI technologies.
Company Profiles:
· Ant Financial
· PayPal
· ZhongAn
· Credit Karma
· ZestFinance
· Lemonade
· Wealthfront
· Kabbage
· LendingClub
· Robinhood
· SoFi
· Square
· Betterment
· Freenome
· Ayasdi
Global AI in Fintech Market: Regional Analysis
The countries covered in the regional analysis of the Global AI in Fintech market report are U.S., Canada, and Mexico in North America, Germany, France, U.K., Russia, Italy, Spain, Turkey, Netherlands, Switzerland, Belgium, and Rest of Europe in Europe, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, China, Japan, India, South Korea, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, South Africa, Egypt, Israel, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), and Argentina, Brazil, and Rest of South America as part of South America.
Key Benefits:
• The analysis provides an overview of the factors driving and limiting the growth of the market including trends, structure and others.
• Market estimation for type and geographic segments is derived from the current market scenario and expected market trends.
• Porter’s Five Force Model and SWOT analysis are used to study the global AI in Fintech market and would help stakeholders make strategic decisions.
• The analysis assists in understanding the strategies adopted by the companies for the growth of this market.
• In-depth analysis of the types of AI in Fintech would help in identifying future applications in this market.
Reasons to Purchase this Report:
• Qualitative and quantitative analysis of the market based on segmentation involving both economic as well as non-economic factors
• Provision of market value (USD Billion) data for each segment and sub-segment
• Indicates the region and segment that is expected to witness the fastest growth as well as to dominate the market
• Analysis by geography highlighting the consumption of the product/service in the region as well as indicating the factors that are affecting the market within each region
• Competitive landscape which incorporates the market ranking of the major players, along with new service/product launches, partnerships, business expansions, and acquisitions in the past five years of companies profiled
• Extensive company profiles comprising of company overview, company insights, product benchmarking, and SWOT analysis for the major market players
• The current as well as the future market outlook of the industry with respect to recent developments which involve growth opportunities and drivers as well as challenges and restraints of both emerging as well as developed regions
• Includes in-depth analysis of the market of various perspectives through Porter’s five forces analysis
• Provides insight into the market through Value Chain
• Market dynamics scenario, along with growth opportunities of the market in the years to come
• 6-month post-sales analyst support
Objectives of the Study:
• To provide with an exhaustive analysis on the AI in Fintech Market by Product, By Application, By End User and by Region.
• To cater comprehensive information on factors impacting market growth (drivers, restraints, opportunities, and industry-specific restraints)
• To evaluate and forecast micro-markets and the overall market
• To predict the market size, in key regions— North America, Europe, Asia Pacific, Latin America and Middle East and Africa.
• To record and evaluate competitive landscape mapping- product launches, technological advancements, mergers and expansions
Historic Year: 2016-2022
Forecast: 2024-2035
1 AI in Fintech Introduction and Market Overview
1.1 Objectives of the Study
1.2 Overview of AI in Fintech
1.3 AI in Fintech Market Scope and Market Size Estimation
1.3.1 Market Concentration Ratio and Market Maturity Analysis
1.3.2 Global AI in Fintech Revenue and Growth Rate from 2016-2026
1.4 Market Segmentation
1.4.1 Types of AI in Fintech
1.4.2 Applications of AI in Fintech
1.4.3 Research Regions
1.5 Market Dynamics
1.5.1 AI in Fintech Industry Trends
1.5.2 AI in Fintech Drivers
1.5.3 AI in Fintech Market Challenges
1.5.4 AI in Fintech Market Restraints
1.6 Industry News and Policies by Regions
1.6.1 Industry News
1.6.2 Industry Policies
1.7 Mergers & Acquisitions, Expansion Plans
1.8 AI in Fintech Industry Development Trends under COVID-19 Outbreak
1.8.1 Global COVID-19 Status Overview
1.8.2 Influence of COVID-19 Outbreak on AI in Fintech Industry Development
2 Industry Chain Analysis
2.1 Upstream Raw Material Supply and Demand Analysis
2.1.1 Global AI in Fintech Major Upstream Raw Material and Suppliers
2.1.2 Raw Material Source Analysis
2.2 Major Players of AI in Fintech
2.2.1 Major Players Manufacturing Base of AI in Fintech in 2020
2.2.2 Major Players Market Distribution in 2020
2.3 AI in Fintech Manufacturing Cost Structure Analysis
2.3.1 Production Process Analysis
2.3.2 Manufacturing Cost Structure of AI in Fintech
2.3.3 Labor Cost of AI in Fintech
2.4 Market Channel Analysis of AI in Fintech
2.5 Major Down Stream Customers by Application
3 Global AI in Fintech Market, by Type
3.1 Global AI in Fintech Revenue and Market Share by Type (2016-2021)
3.2 Global AI in Fintech Production and Market Share by Type (2016-2021)
3.3 Global AI in Fintech Revenue and Growth Rate by Type (2016-2021)
3.3.1 Global AI in Fintech Revenue and Growth Rate of Solutions
3.3.2 Global AI in Fintech Revenue and Growth Rate of Services
3.4 Global AI in Fintech Price Analysis by Type (2016-2021)
3.4.1 Explanation of Different Type Product Price Trends
4 AI in Fintech Market, by Application
4.1 Downstream Market Overview
4.2 Global AI in Fintech Consumption and Market Share by Application (2016-2021)
4.3 Global AI in Fintech Consumption and Growth Rate by Application (2016-2021)
4.3.1 Global AI in Fintech Consumption and Growth Rate of Chatbots (2016-2021)
4.3.2 Global AI in Fintech Consumption and Growth Rate of Credit Scoring (2016-2021)
4.3.3 Global AI in Fintech Consumption and Growth Rate of Quantitative & Asset Management (2016-2021)
4.3.4 Global AI in Fintech Consumption and Growth Rate of Fraud Detection (2016-2021)
4.3.5 Global AI in Fintech Consumption and Growth Rate of Others (2016-2021)
5 Global AI in Fintech Consumption, Revenue ($) by Region (2016-2021)
5.1 Global AI in Fintech Revenue and Market Share by Region (2016-2021)
5.2 Global AI in Fintech Consumption and Market Share by Region (2016-2021)
5.3 Global AI in Fintech Consumption, Revenue, Price and Gross Margin (2016-2021)
5.4 North America AI in Fintech Consumption, Revenue, Price and Gross Margin (2016-2021)
5.4.1 North America AI in Fintech Market Under COVID-19
5.4.2 North America AI in Fintech SWOT Analysis
5.5 Europe AI in Fintech Consumption, Revenue, Price and Gross Margin (2016-2021)
5.5.1 Europe AI in Fintech Market Under COVID-19
5.5.2 Europe AI in Fintech SWOT Analysis
5.6 China AI in Fintech Consumption, Revenue, Price and Gross Margin (2016-2021)
5.6.1 China AI in Fintech Market Under COVID-19
5.6.2 China AI in Fintech SWOT Analysis
5.7 Japan AI in Fintech Consumption, Revenue, Price and Gross Margin (2016-2021)
5.7.1 Japan AI in Fintech Market Under COVID-19
5.7.2 Japan AI in Fintech SWOT Analysis
5.8 Middle East and Africa AI in Fintech Consumption, Revenue, Price and Gross Margin (2016-2021)
5.8.1 Middle East and Africa AI in Fintech Market Under COVID-19
5.8.2 Middle East and Africa AI in Fintech SWOT Analysis
5.9 India AI in Fintech Consumption, Revenue, Price and Gross Margin (2016-2021)
5.9.1 India AI in Fintech Market Under COVID-19
5.9.2 India AI in Fintech SWOT Analysis
5.10 South America AI in Fintech Consumption, Revenue, Price and Gross Margin (2016-2021)
5.10.1 South America AI in Fintech Market Under COVID-19
5.10.2 South America AI in Fintech SWOT Analysis
5.11 South Korea AI in Fintech Consumption, Revenue, Price and Gross Margin (2016-2021)
5.11.1 South Korea AI in Fintech Market Under COVID-19
5.11.2 South Korea AI in Fintech SWOT Analysis
5.12 Southeast Asia AI in Fintech Consumption, Revenue, Price and Gross Margin (2016-2021)
5.12.1 Southeast Asia AI in Fintech Market Under COVID-19
5.12.2 Southeast Asia AI in Fintech SWOT Analysis
6 Global AI in Fintech Production by Top Regions (2016-2021)
6.1 Global AI in Fintech Production by Top Regions (2016-2021)
6.2 North America AI in Fintech Production and Growth Rate
6.3 Europe AI in Fintech Production and Growth Rate
6.4 China AI in Fintech Production and Growth Rate
6.5 Japan AI in Fintech Production and Growth Rate
6.6 India AI in Fintech Production and Growth Rate
7 Global AI in Fintech Consumption by Regions (2016-2021)
7.1 Global AI in Fintech Consumption by Regions (2016-2021)
7.2 North America AI in Fintech Consumption and Growth Rate
7.3 Europe AI in Fintech Consumption and Growth Rate
7.4 China AI in Fintech Consumption and Growth Rate
7.5 Japan AI in Fintech Consumption and Growth Rate
7.6 Middle East & Africa AI in Fintech Consumption and Growth Rate
7.7 India AI in Fintech Consumption and Growth Rate
7.8 South America AI in Fintech Consumption and Growth Rate
7.9 South Korea AI in Fintech Consumption and Growth Rate
7.10 Southeast Asia AI in Fintech Consumption and Growth Rate
8 Competitive Landscape
8.1 Competitive Profile
8.2 Inbenta Technologies Market Performance Analysis
8.2.1 Company Profiles
8.2.2 AI in Fintech Product Profiles, Application and Specification
8.2.3 Inbenta Technologies Sales, Revenue, Price, Gross Margin 2016-2021
8.2.4 Company Recent Development
8.2.5 Strategies for Company to Deal with the Impact of COVID-19
8.3 Salesforce.Com Market Performance Analysis
8.3.1 Company Profiles
8.3.2 AI in Fintech Product Profiles, Application and Specification
8.3.3 Salesforce.Com Sales, Revenue, Price, Gross Margin 2016-2021
8.3.4 Company Recent Development
8.3.5 Strategies for Company to Deal with the Impact of COVID-19
8.4 Intel Market Performance Analysis
8.4.1 Company Profiles
8.4.2 AI in Fintech Product Profiles, Application and Specification
8.4.3 Intel Sales, Revenue, Price, Gross Margin 2016-2021
8.4.4 Company Recent Development
8.4.5 Strategies for Company to Deal with the Impact of COVID-19
8.5 Trifacta Software Inc. Market Performance Analysis
8.5.1 Company Profiles
8.5.2 AI in Fintech Product Profiles, Application and Specification
8.5.3 Trifacta Software Inc. Sales, Revenue, Price, Gross Margin 2016-2021
8.5.4 Company Recent Development
8.5.5 Strategies for Company to Deal with the Impact of COVID-19
8.6 TIBCO Software Market Performance Analysis
8.6.1 Company Profiles
8.6.2 AI in Fintech Product Profiles, Application and Specification
8.6.3 TIBCO Software Sales, Revenue, Price, Gross Margin 2016-2021
8.6.4 Company Recent Development
8.6.5 Strategies for Company to Deal with the Impact of COVID-19
8.7 IBM Market Performance Analysis
8.7.1 Company Profiles
8.7.2 AI in Fintech Product Profiles, Application and Specification
8.7.3 IBM Sales, Revenue, Price, Gross Margin 2016-2021
8.7.4 Company Recent Development
8.7.5 Strategies for Company to Deal with the Impact of COVID-19
8.8 Complyadvantage.Com Market Performance Analysis
8.8.1 Company Profiles
8.8.2 AI in Fintech Product Profiles, Application and Specification
8.8.3 Complyadvantage.Com Sales, Revenue, Price, Gross Margin 2016-2021
8.8.4 Company Recent Development
8.8.5 Strategies for Company to Deal with the Impact of COVID-19
8.9 Samsung Market Performance Analysis
8.9.1 Company Profiles
8.9.2 AI in Fintech Product Profiles, Application and Specification
8.9.3 Samsung Sales, Revenue, Price, Gross Margin 2016-2021
8.9.4 Company Recent Development
8.9.5 Strategies for Company to Deal with the Impact of COVID-19
8.10 Amazon Web Services Market Performance Analysis
8.10.1 Company Profiles
8.10.2 AI in Fintech Product Profiles, Application and Specification
8.10.3 Amazon Web Services Sales, Revenue, Price, Gross Margin 2016-2021
8.10.4 Company Recent Development
8.10.5 Strategies for Company to Deal with the Impact of COVID-19
8.11 Microsoft Market Performance Analysis
8.11.1 Company Profiles
8.11.2 AI in Fintech Product Profiles, Application and Specification
8.11.3 Microsoft Sales, Revenue, Price, Gross Margin 2016-2021
8.11.4 Company Recent Development
8.11.5 Strategies for Company to Deal with the Impact of COVID-19
8.12 Onfido Market Performance Analysis
8.12.1 Company Profiles
8.12.2 AI in Fintech Product Profiles, Application and Specification
8.12.3 Onfido Sales, Revenue, Price, Gross Margin 2016-2021
8.12.4 Company Recent Development
8.12.5 Strategies for Company to Deal with the Impact of COVID-19
8.13 Samsung Group Market Performance Analysis
8.13.1 Company Profiles
8.13.2 AI in Fintech Product Profiles, Application and Specification
8.13.3 Samsung Group Sales, Revenue, Price, Gross Margin 2016-2021
8.13.4 Company Recent Development
8.13.5 Strategies for Company to Deal with the Impact of COVID-19
8.14 NetGuardians Market Performance Analysis
8.14.1 Company Profiles
8.14.2 AI in Fintech Product Profiles, Application and Specification
8.14.3 NetGuardians Sales, Revenue, Price, Gross Margin 2016-2021
8.14.4 Company Recent Development
8.14.5 Strategies for Company to Deal with the Impact of COVID-19
8.15 Data Minr Inc. Market Performance Analysis
8.15.1 Company Profiles
8.15.2 AI in Fintech Product Profiles, Application and Specification
8.15.3 Data Minr Inc. Sales, Revenue, Price, Gross Margin 2016-2021
8.15.4 Company Recent Development
8.15.5 Strategies for Company to Deal with the Impact of COVID-19
8.16 Nuance Communications Market Performance Analysis
8.16.1 Company Profiles
8.16.2 AI in Fintech Product Profiles, Application and Specification
8.16.3 Nuance Communications Sales, Revenue, Price, Gross Margin 2016-2021
8.16.4 Company Recent Development
8.16.5 Strategies for Company to Deal with the Impact of COVID-19
8.17 Ripple Labs Inc. Market Performance Analysis
8.17.1 Company Profiles
8.17.2 AI in Fintech Product Profiles, Application and Specification
8.17.3 Ripple Labs Inc. Sales, Revenue, Price, Gross Margin 2016-2021
8.17.4 Company Recent Development
8.17.5 Strategies for Company to Deal with the Impact of COVID-19
8.18 Google Market Performance Analysis
8.18.1 Company Profiles
8.18.2 AI in Fintech Product Profiles, Application and Specification
8.18.3 Google Sales, Revenue, Price, Gross Margin 2016-2021
8.18.4 Company Recent Development
8.18.5 Strategies for Company to Deal with the Impact of COVID-19
8.19 IPsoft Market Performance Analysis
8.19.1 Company Profiles
8.19.2 AI in Fintech Product Profiles, Application and Specification
8.19.3 IPsoft Sales, Revenue, Price, Gross Margin 2016-2021
8.19.4 Company Recent Development
8.19.5 Strategies for Company to Deal with the Impact of COVID-19
8.20 Zeitgold GmbH Market Performance Analysis
8.20.1 Company Profiles
8.20.2 AI in Fintech Product Profiles, Application and Specification
8.20.3 Zeitgold GmbH Sales, Revenue, Price, Gross Margin 2016-2021
8.20.4 Company Recent Development
8.20.5 Strategies for Company to Deal with the Impact of COVID-19
8.21 Next It Corp Market Performance Analysis
8.21.1 Company Profiles
8.21.2 AI in Fintech Product Profiles, Application and Specification
8.21.3 Next It Corp Sales, Revenue, Price, Gross Margin 2016-2021
8.21.4 Company Recent Development
8.21.5 Strategies for Company to Deal with the Impact of COVID-19
9 Global AI in Fintech Market Analysis and Forecast by Type and Application
9.1 Global AI in Fintech Market Revenue & Volume Forecast, by Type (2021-2026)
9.1.1 Solutions Market Revenue and Volume Forecast (2021-2026)
9.1.2 Services Market Revenue and Volume Forecast (2021-2026)
9.2 Global AI in Fintech Market Revenue & Volume Forecast, by Application (2021-2026)
9.2.1 Chatbots Market Revenue and Volume Forecast (2021-2026)
9.2.2 Credit Scoring Market Revenue and Volume Forecast (2021-2026)
9.2.3 Quantitative & Asset Management Market Revenue and Volume Forecast (2021-2026)
9.2.4 Fraud Detection Market Revenue and Volume Forecast (2021-2026)
9.2.5 Others Market Revenue and Volume Forecast (2021-2026)
10 AI in Fintech Market Supply and Demand Forecast by Region
10.1 North America Market Supply and Demand Forecast (2021-2026)
10.2 Europe Market Supply and Demand Forecast (2021-2026)
10.3 China Market Supply and Demand Forecast (2021-2026)
10.4 Japan Market Supply and Demand Forecast (2021-2026)
10.5 Middle East and Africa Market Supply and Demand Forecast (2021-2026)
10.6 India Market Supply and Demand Forecast (2021-2026)
10.7 South America Market Supply and Demand Forecast (2021-2026)
10.8 South Korea Market Supply and Demand Forecast (2021-2026)
10.9 Southeast Asia Market Supply and Demand Forecast (2021-2026)
10.10 Explanation of Market Size Trends by Region
10.11 AI in Fintech Market Trends Analysis
11 New Project Feasibility Analysis
11.1 Industry Barriers and New Entrants SWOT Analysis
11.2 Analysis and Suggestions on New Project Investment
12 Expert Interview Record
13 Research Finding and Conclusion
14 Appendix
14.1 Methodology
14.2 Research Data Source
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Case Study- Automotive Sector
One of the key manufacturers of automotive had plans to invest in electric utility vehicles. The electric cars and associated markets being a of evolving nature, the automotive client approached Straits Research for a detailed insight on the market forecasts. The client specifically asked for competitive analysis, regulatory framework, regional prospects studied under the influence of drivers, challenges, opportunities, and pricing in terms of revenue and sales (million units).
Solution
The overall study was executed in three stages, intending to help the client meet its objective of precisely understanding the entire market before deciding on an investment. At first, secondary research was conducted considering political, economic, social, and technological parameters to get a gist of the various aspects of the market. This stage of the study concluded with the derivation of drivers, opportunities, and challenges. It also laid substantial emphasis on understanding and collecting data not only on a global scale but also on the regional and country levels. Data Extraction through Primary Research
The second stage involved primary research in which several market players and automotive parts suppliers were contacted to study their viewpoint concerning the development of their market and production capacity, clientele, and product line. This stage concluded in a brief understanding of the competitive ecosystem and also glanced through the strategies and pricing of the companies profiled.
Market Estimates and Forecast
In the final stage of the study, market forecasts for the electric utility were derived using multiple market engineering approaches. This data helped the client to get an overview of the market and accelerate the process of investment.
Case Study- ICT Sector
Business process outsourcing, being one of the lucrative markets from both supply- and demand- side, has appealed to various companies. One of the prominent corporations based out of Japan approached us with their requirements regarding the scope of the procurement outsourcing market for around 50 countries. Additionally, the client also sought key players operating in the market and their revenue breakdown in terms of region and application.
Business Solution
An exhaustive market study was conducted based on primary and secondary research that involved factors such as labor costs in various countries, skilled and technical labors, manufacturing scenario, and their respective contributions in the global GDP. A comparative study of the market was conducted from both supply- and demand side, with the supply-side comprising of notable companies, such as GEP, Accenture, and others, that provide these services. On the other hand, large manufacturing companies from them demand-side were considered that opt for these services.
Conclusion
The report aided the client in understanding the market trends, including country-level business scenarios, consumer behavior, and trends in 50 countries. The report also provided financial insights of crucial players and detailed market estimations and forecasts till 2028.
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