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“AI in Fintech Market” report provides profound research of industry players, dynamics, and strategies are segmented and sub-segmented to simplify the actual conditions of the industry. The report also covers scope of product market, research methodology, Porter’s Five Force analysis, and Competitive landscape of industry. This report scrutinizes all the key factors influencing growth of global AI in Fintech market, including production and value chain analysis, pricing structure, demand-supply scenario, profit margins.
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Top Players Are:
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.
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- Market Dynamics – Drivers, Restraints, and Opportunities
- Market Segmentation – Types, Applications, Regions, and Technology
- Market Trends
- Competitive Landscape
- SWOT Analysis and Porter’s Five Forces Analysis
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.
Most of the companies present in the market are efficient at the technological front, but require significant support for enhancing their services and expanding their businesses. Thus, mergers and acquisitions offer significant opportunities to gain the attention of a large number of providers across developed regions.
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Detailed TOC of AI in Fintech Market Report 2024:
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
5.2 By Deployment
5.3 By Application
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)
5.4.1 North America
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
6.1.4 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
6.1.10 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.
7 INVESTMENT ANALYSIS
8 MARKET OPPORTUNITIES AND FUTURE TRENDS
Name: Ajay More
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