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Global AI in Fintech Market 2021 Production, Revenue, Price and Gross Margin Analysis with Forecasts

AI in Fintech

AI in Fintech Market” report provides strategic supports mentioned by the business specialists with market sources, amount of manufacturing cost structure, raw materials, forecasts, turnover, manufacturing outlays, latest market trends, labor cost, demands and much more. AI in Fintech market report covers a comprehensive market structure through the globe with an in-depth study of major dynamics (Drivers, Challenges, Opportunities).  

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Key Market Trends:

Fraud Detection Segment is Expected to Have A Significant Growth

Fraud prevention and detection represent the most significant area of concern, for the financial institutions. This segment is likely to become one of the prominent drivers of IT expenditure. Thus, AI capable of avoiding these frauds is expected to experience increased adoption in Fintechs. Fraudulent activities in the industry have evolved, over the decades. Earlier, frauds were limited to cheque frauds and wire frauds. However, with the growth of the cybersphere and the accompanying expansion of the cybercriminal realm, fraud has taken on more virtualized forms.
Owing to rising technological penetration and digital channels (such as internet banking and mobile banking) becoming the prominent choices of customers for banking services, there is a greater need for banks to leverage fraud prevention solutions.
– NetGuardians, a Switzerland based Fintech company established in 2007, developed an augmented intelligence solution. It has been made especially for the banks to proactively prevent fraud and empower their clients with ML technology together with contextual information and excellent user experience.The company claimed that banks using this solution were able to achieve 83% reduction in false positives and save 93% of the time lost in fraud investigation.
– Fraud detection and management are imperative for financial institutions, now more than ever, as firms are faced with new and more sophisticated threats to client data, in addition to security breaches. Financial organizations could face fines of more than USD 1 billion, if they fail to meet government standards against money laundering, GDPR regulations, and other financial crimes.
– For instance, HSBC paid a fine for not being compliant with AML laws. The company was fined USD 1.9 billion for its failure to control money laundering. Hence, the company implemented Ayasdi’s solutions that provide anti-fraud solutions to banks. Using Ayasdi’s AML solution, HSBC found a reduction of 20% in false positives, without reducing the number of cases reported for suspicious activities.
– The alignment to anti-fraud standards has led to a drastic increase in anti-fraud efforts by financial companies, many of which have proven to be time consuming and expensive. In addition, with the rise of AI-based fintech solutions, banks now have the opportunity to fight against fraud more effectively, effortlessly, and at a fraction of the cost.

North America Region is Expected to Have Largest Market Share

North America is regarded as the most competitive and rapidly developing AI technology market, in the finance industry. North America, among all the regions, has registered the maximum adoption of AI in Fintech solutions, due to its early implementation in a majority of application areas.
The presence of financial service firms in the region is quite high. From 2011, until the third quarter of 2017, more than 3,330 new technology-based firms serving the financial services industry have been founded, around 40% of which are focused on banking and capital markets, as reported by the Treasury Department. These firms are grappling with unprecedented opportunities and challenges in digital finance, due to changing customer expectations, emerging new technologies, and fluctuating regulations.
– 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.
– Furthermore, slackening of federal regulations, enacting national data breach protections and drafting model laws at the state level to reduce overlapping red tape, could help promote fintech companies in the United States, according to the report released by the US Treasury Department, in 2017.
– Additionally, there is an increased attention from lawmakers, to promote innovation among non-bank providers of new payments and payment-related technologies, and garner more consumer concern about online data security. These factors are expected to contribute toward the growth of the market studied in the region.

Market Overview:

  • AI in fintech market was valued at USD 6.84 billion in 2019 and is expected to reach USD 26.92 billion by 2024 registering a CAGR of 31.5% during the forecast period (2019 – 2024). Financial firms have been the early adopters of the mainframe computer, relational databases, and have eagerly awaited for the next level of computational power. Artificial Intelligence (AI) improves results by applying methods derived from aspects of Human Intelligence at a beyond human scale. The computational arms race for past years has revolutionized the Fintech companies. AI and machine learning have benefited the banks and fintechs as they can process huge 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, essentially, in developing customer relations. Owing to these benefits offered by the AI technology, fintech companies are increasingly demanding the AI-based solutions. Moreover, the fintech industry is witnessing a considerable increase in the number of startups. These players are also highly attracted toward the adoption of AI to automate and expand their businesses.
  • – Process automation is one of the key drivers of AI in financial organizations, however, it is also evolving into cognitive process automation, where AI systems are able to perform even more complex automation processes. Recently, JPMorgan Chase invested in new technology, ‘COiN’ that reviews documents and extracts data in a lesser time than that taken by a human. This tool reviews about 12,000 documents in just seconds. The company has been testing other ways of using this technology as well.
  • – Robotic process automation and machine learning are beginning to play an increasingly significant role in the fintech industry by reducing costs and increasing productivity. With the increase in fraud losses, process automation and machine learning are expected to witness increased adoption.
  • – The third-party applications, such as WhatsApp, have integrated in-app transaction system in specific regions, including the Asia-Pacific. This will raise the bar for cyber-attacks and possibilities for fraud, owing to which the incorporation of artificial intelligence is expected to gain traction and propel the market growth.
  • – Fintech space is one of the fastest growing industry across the world, owing to the rising penetration of internet users. The users are rapidly switching to mobile devices to perform a transaction or related actions, owing to rising ease and growing internet user base. Thus, mobile technologies are supporting the fintech revolution, providing innovative, secure, and accessible solutions to financial services and products, and are using AI for managing structured and unstructured data.

    Key Manufacturers Like 

  • IBM Corporation
  • Intel Corporation
  • ComplyAdvantage.com
  • Amazon Web Services, Inc.
  • Samsung Group
  • IPsoft Inc.
  • Next IT Corporation
  • Microsoft Corporation
  • Onfido
  • Ripple Labs Inc.
  • Trifacta Software Inc.
  • Zeitgold GmbH
  • TIBCO Software
  • Data Minr Inc.
  • Sift Science Inc.
  • Pefin Holdings LLC
  • Betterment Holdings Inc.
  • WealthFront Software Inc.
  • Active.Ai.

    Scope of the Report:

  • Artificial intelligence is a part of computer science, aiming to enable the development of computers, which can perform jobs usually done by people. Its main focus remains thinking or intelligence.
  • The development of AI systems tends to fall inside three main areas; building systems that think like people, creating computation models that get tasks done, and forming systems to inform and inspire, but not imitate. Fintech prioritizes financial inclusivity, and to achieve this, real-time play an important role in fintech’s ease of adoption as individuals with a smartphone gain access to quick, personalized, and customized financial services.

    AI in Fintech market report focuses on the latest trends in the global and regional spaces on all the significant components, including the capacity, cost, price, technology, supplies, production, profit, and competition. Moreover, the old data and present development of the AI in Fintech market have been given in the scope of the report. The latest trends, product portfolio, demographics, geographical segmentation, and regulatory framework of the AI in Fintech market have also been involved in the study.

    Market Dynamics: –

    • Drivers: (Developing regions and growing markets)
    • Limitations: (Regional, Key Player facing Issues, Future Barriers for growth)
    • Opportunities: (Regional, Growth Rate, Competitive, Consumption)

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    Key Questions Answered in Market Report: –

    • What will the market growth rate, Overview and Analysis by Type of AI in Fintech market in 2023?
    • What are the key factors driving, Analysis by Applications and Countries AI in Fintech market?
    • What are Dynamics, This Overview Includes Analysis of Scope, and price analysis of top Vendors Profiles of AI in Fintech ?
    • Who are Opportunities, Risk and Driving Force of AI in Fintech market? Knows Upstream Raw Materials Sourcing and Downstream Buyers
    • Who are the opportunities and threats faced by the vendors in AI in Fintech space? Business Overview by Type, Applications, Gross Margin and Market Share
    • What are the AI in Fintech market opportunities, market risk and market overview of the Market?

    Lastly, the Global AI in Fintech Market Research covers a complete market structure across the world with a comprehensive analysis of major key factors. This report provides planned orientations referred by the industry experts.

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    Study objectives of AI in Fintech Market Report:

    • To provide a detailed analysis of the market structure along with the AI in Fintech market forecast of various segments and sub-segments of the AI in Fintech market
    • To provide insights into factors influencing and affecting market growth
    • To provide historical, current, and forecast revenue of market segments based on material, type, design, and end user
    • To provide historical, current, and forecast revenue of market segments and sub-segments with respect to regional markets and key countries
    • To provide strategic profiling of key players in the market, comprehensively analyzing their market shares, core competencies, and drawing a competitive landscape for the market
    • To provide economic factors, technology and AI in Fintech market trends that influence the global AI in Fintech market

    Detailed TOC of AI in Fintech Market Report 2019-2024:

    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 Introduction to Market Dynamics
    4.3 Market Drivers
    4.3.1 Increasing Demand For Process Automation Among Financial Organizations
    4.3.2 Increasing Availability Of Data Sources
    4.4 Market Restraints
    4.4.1 Need For Skilled Workforce
    4.5 Industry Attractiveness – Porter’s Five Force Analysis
    4.5.1 Bargaining Power of Suppliers
    4.5.2 Bargaining Power of Buyers/Consumers
    4.5.3 Threat of New Entrants
    4.5.4 Threat of Substitute Products
    4.5.5 Intensity of Competitive Rivalry
    4.6 Emerging Use-cases for AI in Financial Technology
    4.7 Technology Snapshot

    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 & Asset Management
    5.3.4 Fraud Detection
    5.3.5 Others (Market Research / Sentiment Analysis, Insurance, Predictive Analytics)
    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 Amazon Web Services, Inc.
    6.1.5 Samsung Group
    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 Trifacta Software Inc.
    6.1.12 Zeitgold GmbH
    6.1.13 TIBCO Software
    6.1.14 Data Minr Inc.
    6.1.15 Sift Science Inc.
    6.1.16 Pefin Holdings LLC
    6.1.17 Betterment Holdings Inc.
    6.1.18 WealthFront Software Inc.
    6.1.19 Active.Ai

    7 INVESTMENT ANALYSIS

    8 MARKET OPPORTUNITIES AND FUTURE TRENDS

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