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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 22.60 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.
– 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.
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– 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.
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 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
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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.
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. 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.
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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
5.3.2 Credit Scoring
5.3.3 Quantitative and Asset Management
5.3.4 Fraud Detection
5.3.5 Other Applications
5.4.1 North America
5.4.4 Rest of the World
6 COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 IBM Corporation
6.1.2 Intel Corporation
6.1.4 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
6.1.10 Ripple Labs Inc.
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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