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市场调查报告书
商品编码
649722

金融科技(金融技术)的AI的全球市场:类型(解决方案,服务),应用(聊天机器人,信用评分,定量的·资产管理,诈欺检测),各地区的成长率,趋势及预测(2018-2023)

AI in Fintech Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

出版日期: | 出版商: Mordor Intelligence Pvt Ltd | 英文 130 Pages | 商品交期: 2-3个工作天内

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  • 全貌
  • 简介
  • 目录
简介

金融科技市场中的人工智能在2017年达到12.7亿美元,预计2023年将达到72.8亿美元,在2018年到2023年期间的复合年增长率为33.8%。本报告提供解决方案及服务之各类型,信用评分,定量·资产管理,诈欺检测等各应用领域类别。对象地区有北美,欧洲,亚太地区,中南美,中东·非洲等。该研究还强调了人工智能在金融科技方面的益处,以符合不同的应用和未来前景。

本报告提供金融科技(金融技术)的AI全球市场调查,总括性汇整整体市场趋势,产品·各地区的详细趋势,市场成长的影响要素分析,竞争情形,主要企业简介等资讯。

目录

第1章 简介

  • 研究主要的成果物
  • 调查的前提条件
  • 市场定义
  • 调查结果

第2章 研究方法和方法论

第3章 摘要整理

第4章 市场动态

  • 市场概况
  • 产业价值链
  • 促进市场成长的要素
    • 网际网路普及率的上升
    • 金融业界巨量资料的增加
  • 市场阻碍因素
    • 缺乏熟练劳动力
  • 产业的魅力 - 波特的五力分析
    • 供应商谈判力
    • 消费者谈判力
    • 新加入厂商的威胁
    • 替代产品或服务的威胁
    • 跟现有其他竞争公司的竞争
  • 科技概述

第5章 市场区隔

  • 各类型
    • 解决方案
    • 服务
  • 各应用领域
    • 聊天机器人
    • 信用评分
    • 定量的·资产管理
    • 诈欺检测
    • 其他(市场调查/感情分析,保险,预测分析)
  • 各地区
    • 北美
    • 欧洲
    • 亚太地区
    • 中南美
    • 中东·非洲地区

第6章 其他竞争公司的资讯- 企业简介

  • IBM Corporation
  • Intel Corporation
  • ComplyAdvantage Ltd
  • Amazon Web Services, Inc.
  • Samsung Group
  • Ipsoft Inc.
  • Next IT Corp
  • Microsoft Corporation
  • Onfido
  • Ripple
  • ZestFinance

上述清单仅是部分

第7章 投资分析

第8章 金融科技上AI的全球市场机会

目录
Product Code: 61424

The global AI in the Fintech market was estimated at USD 7.91 billion in 2020, and it is expected to reach USD 26.67 billion by 2026. The market is also expected to witness a CAGR of 23.17% over the forecast period (2021 - 2026). Artificial intelligence improves results by applying methods derived from the aspects of human intelligence but beyond the human scale. The computational arms race for the past few years has revolutionized fintech companies. Furthermore, data and the near-endless amounts of information are transforming AI to unprecedented levels where smart contracts may merely continue the market trend.

Key Highlights

  • In the finance industry, AI is used to examine cash accounts, credit accounts, and investment accounts to look at a person's overall financial health, keep up with real-time changes, and create customized advice based on new incoming data. AI and machine learning have benefited banks and fintech, as they can process vast amounts of information about customers. This data and information are then compared to obtain results about suitable services/products that customers want, which has aided primarily in developing customer relations.
  • Additionally, the increasing demand for process automation among financial organizations​ is driving the market. Process automation is one of the significant drivers of artificial intelligence in financial organizations. However, it is further evolving into cognitive process automation, where AI systems can perform even more complex automation processes.​ For instance, in May 2020, Traydstream, a FinTech that scans trade documents with artificial Intelligence (AI), partnered with Infosys Finacle to implement blockchain technology and further automate trade finance. The partnership may allow Finacle's blockchain tech, called Finacle TradeConnect, to be integrated with Traydstream's platform, which uses AI to scan documents and cut down the time it takes to check on rules or regulations in trade, where mistakes can be costly and time-consuming to correct.​
  • Moreover, credit card companies implement predictive analytics into their existing fraud detection workflows to reduce false positives. For instance, in May 2020, SparkCognition, an industrial AI company, announced that the Japanese AI and fintech company, MILIZE Co. Ltd, may offer financial institutions fraud detection and anti-money laundering (AML) solutions. These solutions are built using the automated machine learning software of SparkCognition. As a result, the software detects fraudulent transactions with about 90% accuracy, which is anticipated to lead to a significant improvement in credit card companies' profitability.
  • AI is further on its way to becoming mainstream in Financial Services within the short term. For instance, according to a survey conducted by Cambridge Centre for Alternative Finance (CCAF) in 2020, 85% of all respondents in the study used some forms of AI, with the fintech companies being slightly ahead of incumbents in the adoption of AI. Owing to these benefits offered by AI technology, fintech companies are increasingly demanding-based solutions. Moreover, the fintech industry is witnessing a significant increase in the number of start-ups. These players are also highly attracted to the adoption of Artificial Intelligence to automate and expand their businesses.
  • Additionally, as brick-and-mortar retailers continue to face challenges due to the onset of the COVID-19 pandemic, many merchants are implementing point-of-sale financing alternatives as a potential new avenue for growth. Apart from utilizing current data like bank account statements for underwriting, these players further use AI models to assess consumer behaviors based on their transaction history, product purchase, and other data points to create a sharper customer risk profile.​
  • Additionally, banks and financial institutions are adopting AI solutions to harness information and insights locked away in unstructured documents and automate the manual process done traditionally by banks in double-quick time. ​For instance, in April 2020, Temenos, the banking software company, announced the launch of eight propositions - using innovative Explainable AI (XAI) and cloud technologies to help banks and financial institutions in their immediate response to the COVID-19 crisis.

Key Market Trends

Quantitative and Asset Management​ to Witness Significant Growth

  • Fintech has been undergoing a continued evolution in the landscape of investment management. Advanced technology and solution adoption, including the use of big data, AI, and machine learning (ML), to help businesses evaluate investment opportunities, optimize their investment portfolios, and mitigate the associated risks, have been clinical in the technology adoption.
  • For instance, investment advisory services are undergoing radical changes with the growth and evolution of automated wealth advisers. These advisers can assist investors without the intervention of a human adviser and can also be used in combination with a human adviser. It extends the ability to provide tailored, actionable advice to its investors with ease of access at a partially lower cost.​
  • In the area of financial record keeping, blockchain and distributed ledger technology are augmenting AI adoption by creating new ways to record, track, and store transactions for financial assets. For instance, Sentifi, a Swiss Fintech company established in 2012, uses AI and ML to enable investors and other financial market stakeholders to tap into the online available financial intelligence of millions of persons and organizations.
  • Furthermore, asset management companies can gain substantial benefits through the adoption of AI and ML. These technologies help provide real-time actionable insights and facilitate portfolio management decisions. Sub-sets of AI can empower asset managers to streamline processes to optimize investment decisions and processes.
  • In October 2019, MDOTM and Raiffeisen Capital Management, one of Austria's largest fund managers, announced a new strategic partnership. With this new initiative, the range of Raiffeisen Capital Management's sustainable funds may be used by MDOTM to provide the market SRI investment solutions that benefit from the efficiency brought by AI technology in portfolio construction.​
  • Moreover, in May 2020, Boosted.ai, the prominent distributed ML platform for global investment professionals, announced the closing of a USD 8 million USD Series A financing round. Boosted.ai may use the funding to continue improving Boosted Insights and its proprietary ML platform that empowers portfolio managers, analysts, and chief investment officers (CIO's) to augment their existing investment processes, source new ideas, and manage risks.

North America Accounts for the Significant Market Share

  • 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.
  • According to Baker McKenzie, the ongoing economic expansion in the United States has attracted considerable investment in the fintech sector. Payments and Insuretech continue to dominate the landscape of the fintech sector in the country. According to C B Insights, the country's fintech startups have witnessed about 70+ mega-rounds of funding, accounting for more than USD 100 million,
  • In 2019, SoFi, a personal finance platform based out of San Francisco, raided the maximum amount (USD 500 million) in a Series G Round. SiFi is followed by Klarna (USD 460 million), Robinhood (USD 323 million), home & rental insurer, Lemonade (USD 300 million), etc.
  • Some of the investments in the field of AI are mentioned here. For instance, in June 2020, Betterview, a US-based insuretech and AI startup, secured an additional USD 7.5 million, adding up to USD 17 million from Maiden Re, a reinsurer based in Bermuda. The AI startup utilizes computer vision and AI to capture and analyze imagery of data for buildings and properties throughout the United States to be used by the property insurance industry in underwriting.
  • 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.​
  • According to the World Payments Report published by the World Bank, the region has one of the highest penetration in terms of citizens' bank accounts and has the highest concentration of ATMs per 100,000 people. The above factors significantly drive the market in the region.

Competitive Landscape

AI in the Fintech market is fragmented, owing to the presence of many global players in the market. Furthermore, various acquisitions and collaborations of large companies are expected to occur shortly, focusing on innovation. Some of the major players in the market are IBM Corporation, Intel Corporation, and Microsoft Corporation, among others. Recent developments in the market are -

  • April 2020 - Fenergo, the provider of digital transformation, customer journey, and client lifecycle management (CLM) solutions for financial institutions, and IBM signed an original equipment manufacturing (OEM) agreement that may allow companies to collaborate on solutions that can help clients address the multitude of financial risks they face.​
  • May 2020 - Sentifi AG announced the expanded alternative data-based analytics to surface investment opportunities and manage risks. Sentifi's new analytics solution includes detection of the sector, industry outliers, ESG events with potential asset valuation impact, and investment themes trending real-time while offering investors the ability to detect outliers within their portfolios. Investors can assess portfolio sentiment performance to the custom benchmark and quickly identify significant market events and impacted sectors, industries, and assets.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Force Analysis
    • 4.2.1 Bargaining Power of Suppliers
    • 4.2.2 Bargaining Power of Buyers/Consumers
    • 4.2.3 Threat of New Entrants
    • 4.2.4 Threat of Substitute Products
    • 4.2.5 Intensity of Competitive Rivalry
  • 4.3 Emerging Uses of AI in Financial Technology
  • 4.4 Technology Snapshot
  • 4.5 Market Drivers
    • 4.5.1 Increasing Demand for Process Automation Among Financial Organizations
    • 4.5.2 Increasing Availability of Data Sources
  • 4.6 Market Restraints
    • 4.6.1 Need for Skilled Workforce
  • 4.7 Assessment of Impact of COVID-19 on the Industry

5 MARKET SEGMENTATION

  • 5.1 By Type
    • 5.1.1 Solutions
    • 5.1.2 Services
  • 5.2 By Deployment
    • 5.2.1 Cloud
    • 5.2.2 On-premise
  • 5.3 By Application
    • 5.3.1 Chatbots
    • 5.3.2 Credit Scoring
    • 5.3.3 Quantitative and Asset Management
    • 5.3.4 Fraud Detection
    • 5.3.5 Other Applications
  • 5.4 By Geography
    • 5.4.1 North America
    • 5.4.2 Europe
    • 5.4.3 Asia Pacific
    • 5.4.4 Rest of the World

6 COMPETITIVE LANDSCAPE

  • 6.1 Company Profiles
    • 6.1.1 IBM Corporation
    • 6.1.2 Intel Corporation
    • 6.1.3 ComplyAdvantage.com
    • 6.1.4 Narrative Science
    • 6.1.5 Amazon Web Services Inc.
    • 6.1.6 IPsoft Inc.
    • 6.1.7 Next IT Corporation
    • 6.1.8 Microsoft Corporation
    • 6.1.9 Onfido
    • 6.1.10 Ripple Labs Inc.
    • 6.1.11 Active.Ai
    • 6.1.12 TIBCO Software (Alpine Data Labs)
    • 6.1.13 Trifacta Software Inc.
    • 6.1.14 Data Minr Inc.
    • 6.1.15 Zeitgold GmbH
    • 6.1.16 Sift Science Inc.
    • 6.1.17 Pefin Holdings LLC
    • 6.1.18 Betterment Holdings
    • 6.1.19 WealthFront Inc.
    • 6.1.20 Sentifi AG

7 INVESTMENT ANALYSIS

8 FUTURE OF THE MARKET