Global $22.6Bn AI in Fintech Market Outlook, 2020-2025 Featuring Profiles of IBM, Intel, ComplyAdvantage.com, Narrative Science, Amazon Web Services, IPsoft, and More
DUBLIN, June 25, 2020 /PRNewswire/ -- The "AI in Fintech Market - Growth, Trends, Forecasts (2020-2025)" report has been added to ResearchAndMarkets.com's offering.
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The global AI in Fintech market was estimated at USD 6.67 billion in 2019 and is expected to reach USD 22.6 billion by 2025. The market is also expected to witness a CAGR of 23.37% over the forecast period (2020-2025).
Artificial Intelligence improves results by applying methods derived from the aspects of human intelligence but beyond human scale. The computational arms race since the past few years has revolutionized the fintech companies. Further, data and the near-endless amounts of information are transforming AI to unprecedented levels where smart contracts will merely continue the market trend.
Key Highlights
-- Increasing demand for process automation among financial organizations
is driving the market. Process automation is one of the major 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 will 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.
-- Further, several market players are introducing ML-based fraud detection
solutions owing to the surging market demand. For instance, in May 2020,
GBG announced its expansion of AI and machine learning capabilities for
its transaction and payment monitoring solution, Predator, making deep
learning and predictive analytics available to their entire digital risk
management customer journey.
-- The increasing availability of data sources is driving the market. As
the fintech industry continues to innovate and evolve at a rapid pace,
fintech firms and startups have broadened their horizons to cater to a
diverse range of segments. The financial sector expanded its footprint
across areas, such as personal financial management, personal banking,
consumer and business loans, investments, financial advisory, and
various other data sources.
-- Fintech companies are investing in deploying AI solutions for efficient
processing of data and effective decision making. Further, according to
a Fintrail survey in 2019, almost 33% of surveyed FinTechs currently
employ AI solutions developed in-house. Many FinTech firms chose built,
over buy, option because their needs may not be easily catered for by
current vendors, although it is also changing with the rise of the
RegTech sector.
-- Further, as brick and mortar retailers continue to face challenges due
to the onset of COVID-19 pandemic, many merchants are implementing
point-of-sale financing alternatives as a potential new avenue for
growth. Apart from utilizing conventional data like bank account
statements for underwriting, these players are further utilizing AI
models to assess consumer behaviors based on their transaction history,
product purchase, and other data points to create a sharper customer
risk profile.
-- Also, 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.
Major 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 the
businesses in evaluating investment opportunities, optimizing their
investment portfolios, and mitigating the associated risks have been
clinical in the technology adoption.
-- The investment advisory services, for instance, are undergoing radical
changes with the growth and evolution of automated wealth advisers.
These advisers have the capabilities to assist the 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.
-- Further, in the area of financial record keeping, blockchain, and
distributed ledger technology are augmenting the 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 can 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 would be used by MDOTM to provide to 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 would use the funding
to continue improving Boosted Insights, 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 factors such as the strong economy, robust
presence of prominent AI software and system suppliers, combined
investment by government and private organizations for the development
and growth of research & development activities.
-- According to Baker McKenzie, the ongoing economic expansion in the US
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 CB Insights, the fintech startups in the
country have witnessed about 70+ mega-rounds of funding accounting to
more than USD 100 million,
-- In 2019. SoFi, a personal finance platform based out of the San
Francisco, has 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 such as, in June 2020,
Betterview, a US-based insuretech and AI start-up, has secured an
additional of USD 7.5 million, adding up to USD 17 million from Maiden
Re, a reinsurer based out Bermuda. The AI startup utilizes computer
vision and AI, to capture and analyze imagery of data for buildings and
properties throughout the US 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 U.S. Census Bureau
population estimates, there are around 72.1 million millennials, as of
2019. However, according to Digital Banking Report 2019, the adoption
rates of fintech services in Canada (50%) and the US (46%) are some of
the lowest in the world.
-- Also, according to the World Payments Report published by World Bank,
this 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 Fintech market is moving towards fragmented owing to the presence of many global players in the market. Further various acquisitions and collaboration of large companies are expected to take place shortly, which focuses on innovation. Some of the major players in the market are IBM Corporation, Intel Corporation, Microsoft Corporation, among others.
Some 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 will allow the companies to collaborate on solutions that
can help clients address the multitude of financial risks they face.
-- April 2020 - Verient System INC, the parent company of Next IT
corporation, completed an agreement to provide its new standard solution
for enterprise fraud and security investigations to the world's largest
banking organizations. The AI platform Of Verient systems will help
banks in fraud detection, cybersecurity, and deployment management
requirements.
Key Topics Covered
1 INTRODUCTION
1.1 Study Deliverables
1.2 Scope of the Study
1.3 Study Assumptions
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
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 Use-cases for AI in Financial Technology
4.4 Technology Snapshot
4.5 Introduction to Market Dynamics
4.6 Market Drivers
4.6.1 Increasing Demand for Process Automation Among Financial Organizations
4.6.2 Increasing Availability of Data Sources
4.7 Market Restraints
4.7.1 Need for Skilled Workforce
4.8 Assessment of Impact of COVID-19 on the Industry
5 MARKET SEGMENTATION
5.1 Offering
5.1.1 Solutions
5.1.2 Services
5.2 Deployment
5.2.1 Cloud
5.2.2 On-premise
5.3 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 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
7 INVESTMENT ANALYSIS
8 MARKET OPPORTUNITIES AND FUTURE TRENDS
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