LONDON, UK, May 20, 2021 (GLOBE NEWSWIRE) — AI in Banking Industry Global Size, Trends, Competitive, Historical & Forecast Analysis, 2021-2027- Increasing adoption of digitization across the global banking sector, rising use of AI-enabled chatbots, increasing collaboration between banks and increasing funding by government and rising digital transformation in finance sectors around the world are some of the factors driving the growth of Global AI in Banking Industry.
Infusion of artificial intelligence (AI) is one of the latest trends in the banking sector. By using AI to improve the customer experience in contact list. Banks contain large amounts of data and AI will connect the dots between the information points and alter the approach businesses act with their customers. Also, AI is being implemented by banks within middle-office functions to detect, assess risks and prevent payments fraud cases, improve processes for anti-money laundering (AML) and perform know-your-customer (KYC) regulatory checks. There are three main applications where banks can use artificial intelligence to save on costs are front office (conversational banking), middle office (anti-fraud) and back office (underwriting). AI used by many banks to transform the customer experience by enabling frictionless, 24/7 customer interactions.
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Increasing Adoption of Digitization in Banking, Growing Use of AI-enabled chatbots, Increasing Collaboration between Banks and Rising funding by the government are Driving the Market Growth
Increasing adoption of digitization across the global banking sector, growing adoption of AI-enabled chatbots and growing digital transformation in finance sectors around the world are some of the major factors deriving the growth of global AI in Banking Industrys. For example; the company Temenos designed AI based platform named as Temenos Infinity Digital Banking Platform for the business transformation that used in financial institutions to speed up their digital transformation initiatives. And, ATB Financial and the Bank of America (BoA) adapted AI chatbots like the famous BoA chatbot “Erica”, which was launched in 2018, served more than 10 million users. For instance, Kasisto Manulife Bank announced the partnership for launching MAI, a conversational AI solution targeted towards Manulife’s Canadian millennial clients in 2019. In addition, increasing collaboration between banks and increasing funding by government is also fostering the market growth. Recently, a leading bank in the Americas, Scotiabank, announced the collaboration with MaRS, a support network for Canadian startups, a non-profit community for Canadians working in technology for opening its own platform up to new technologies. These collaboration of banks wants to increase its access to emerging technologies, especially artificial intelligence (AI). According to report of International Institute of Communications (IIC), in 2020, APAC governments invested heavily in developing their own homegrown AI capabilities by financing research, development, and deployment efforts.
Furthermore, the high requirement for chatbots in banking industry, for reducing training cost of agents, personalizing experience for the customers, improving customer service and resolving customer queries quickly are the key factors for growth of AI in Banking Industry. For example, Amy is an AI Chatbot specifically designed by The Hongkong and Shanghai Banking Corporation Limited (HSBC) for corporate banking customer support at HSBC Bank, based in Hong Kong. It is available on desktop and mobile in Chinese and English language. Amy is a great solution for one of the busiest Chinese banks and has made a significant contribution to improving the bank’s support system. Moreover, surge in demand for real-time information about the stock market is also fastening the artificial intelligence (AI) in banking market. For example, In India, NSE (leading stock exchange) introduced a Knowledge Hub on artificial intelligence (AI) which driven learning ecosystem to assist the banking and financial services sector in enhancing the skills of their employees in 2020.
However, lack of required infrastructure and skilled AI professionals may hamper the growth of AI in Banking Industry. Moreover, adoption of technological advancements and growing awareness regarding the innovative cloud technologies may create wide opportunities for the players operating in the AI in Banking Industry.
The effect of the pandemic has augmented the adoption of a broader range of AI in banking. During Covid 19, the lockdown to prevent the spread of the Covid-19 has stopped economic activity across many sectors. For example, the banking sector is affected indirectly. Whereas banking services can be provided remotely and do not depend on direct customer contact, the linkage of the sector with the real sector as provider of payment, credit savings, and risk management services extends the negative effect of the Covid-19 crisis to banks and other financial institutions. In spite of that, due to the pandemic, it is found that half of consumers are using digital products for transaction. For example; digital wallet to transfer money from one to another. Thus, the COVID-19 pandemic is providing more opportunities for adoption of AI in banking industry because of social distancing is only solution developed for minimizing exposure of COVID-19.
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North America is expected to dominate the global AI in Banking Industry with the potential rate due to rising use of fast-emerging digital technologies, such as data analytics, AI, block chain, IoT, cloud computing and all Internet-based services in this region. According to recent report of United Nations Conference on Trade and Development, an estimated that IoT devices were grew from 9.9 billion in 2019 to 21.5 billion in 2025 and the United States accounts for around 50% of global IoT spending on the devices. Also, rising banking fraud cases, quick adoption of advanced technologies coupled with the presence of leading players in the region are also fostering the market growth in this region. For instance; the USAA (the United Services Automobile Association) is a San Antonio-based working in financial services and uses AI to monitor fraud and fraud prevention. For instance, ZestFinance is the leader in artificial intelligence (AI) software for credit category including personal loans, credit cards, auto, mortgages and student loans and it is based in Los Angeles, California, United states.
The Asia Pacific is expected to emerge as the fastest-growing regional market for AI in banking due to growing digitalization of the banking sector in this region. Also, growing government policies and initiatives to increase the adoption of artificial intelligence (AI) across various sectors, including banking and adoption of innovative technology in developing countries such as China and India, will further drive the market growth in this region during the forecast period. According to news published on Nov 21, 2020, the South Korean government has an AI strategy to become a top leader in artificial intelligence by 2030.
Global AI in Banking Industry report is segmented on the basis of component, technology, application, solution and region & country level. Based upon component, global AI in Banking Industry is classified into service, hardware and software. Based upon technology, the market is classified into natural language processing, deep learning & machine learning, computer vision and others. Based upon application, global AI in Banking Industry is classified into customer service, back office, financial advisory, compliance & security, risk management and others. Based upon solution, the market is classified into customer behavior analytics, data analytics & visualization, fraud detection, customer relationship management, Chatbot and others.
Global AI in Banking Market Segmentation:
- Natural Language Processing
- Deep Learning & Machine Learning
- Computer Vision
- Customer Service
- Back Office
- Financial Advisory
- Compliance & Security
- Risk Management
- Customer Behavior Analytics
- Data Analytics & Visualization
- Fraud Detection
- Customer Relationship Management
The regions covered in this AI in Banking Industry report are North America, Europe, Asia-Pacific and Rest of the World. On the basis of country level, market of AI in banking is sub divided into U.S., Mexico, Canada, U.K., France, Germany, Italy, China, Japan, India, South East Asia, GCC, Africa, etc.
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Key Players AI in Banking Industry Report:
Some major key players for global AI in Banking Industry report cover prominent players are Microsoft Corporation, Google LLC, Intel Corporation, Oracle Corporation, Amazon Web Services Inc., Salesforce.com, Inc., SAP SE, Zest AI, IBM, DataRobot, Inc., Accenture and others.
News: Intel and Consilient Joined Forces to Fight Financial Fraud with AI
December 8th, 2020; Intel and Consilient associated to fight financial fraud with AI in the banking market. Consilient is a newly formed company focused to forming a next-generation system for anti-money laundering and countering the financing of terrorism (AML/CFT) had launched a new secure, federated learning platform powered by Intel Software Guard Extensions (Intel® SGX). The artificial intelligence (AI) platform further used to prevent financial crime and allows secure collaboration among financial institutions while helping to protect privacy and secure data.
Key Benefits for Global AI in Banking Industry Market Report–
- Global AI in Banking Industry Market report covers in-depth historical and forecast analysis.
- Global AI in Banking Industry Market research report provides detail information about Market Introduction, Market Summary, Global market Revenue (Revenue USD), Market Drivers, Market Restraints, Market Opportunities, Competitive Analysis, Regional and Country Level.
- Global AI in Banking Industry Market report helps to identify opportunities in marketplace.
- Global AI in Banking Industry Market report covers extensive analysis of emerging trends and competitive landscape.
By Regional & Country Level:
- North America
- Asia Pacific
- Southeast Asia
- Latin America
- Middle East and Africa
- Rest of Middle East and Africa
Table of Content:
1. Chapter – Report Methodology
1.1. Research Process
1.2. Primary Research
1.3. Secondary Research
1.4. Market Size Estimates
1.5. Data Triangulation
1.6. Forecast Model
1.7. USP’s of Report
1.8. Report Description
2. Chapter – Global AI in Banking Industry Market Overview: Qualitative Analysis
2.1. Market Introduction
2.2. Executive Summary
2.3. Global AI in Banking Industry Market Classification
2.4. Market Drivers
2.5. Market Restraints
2.6. Market Opportunity
2.7. AI in Banking Industry Growth
2.8. Porter’s Five Forces Analysis
2.9. Market Attractiveness Analysis
3. Chapter – Global AI in Banking Industry Market Overview: Quantitative Analysis
4. Chapter – Global AI in Banking Industry Market Analysis: Segmentation By Type
5. Chapter – Global AI in Banking Industry Market Analysis: Segmentation By Application
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