The global artificial intelligence (AI) market in Banking, Financial Services, and Insurance (BFSI) sector is expected to post a compound annual growth rate of more than 32 percent during the period 2019 to 2023, according to the latest market research report by Technavio.
According to another report by Allied Market Research, Artificial Intelligence in BFSI Market by Deployment Type (Cloud and On-Premise) and Technology (Machine Learning, Natural Language Processing, Image Processing & Video Recognition, Cognitive Computing, and Others) – Global Opportunity Analysis and Industry Forecast, 2019-2026, the global AI in BFSI market is expected to register substantial growth in the near future, attributed to a rapid demand for anti-money laundering pattern detectors, rapid digitalization in the financial market, and adoption of chatbots in banking and financial services. The need for personalized financial services and rise in demand for data-driven solutions for imparting decision-making capabilities further drive the market growth.
AI takes many forms for BFSI, including machine learning (ML), natural language processing (NLP), image processing and video recognition, and cognitive computing.
Several vendors target the finance and banking markets with AI technologies. We highlight market leaders below.
AlphaSense provides an AI-based market intelligence search engine for investment firms and corporations. The platform combines clients’ internal content with the world’s most valuable business and market information including broker research, call transcripts, company reports, news, and trade journals. Seamlessly aggregating thousands of data sources, its semantic search engine captures variations in human language, accurately recognizing millions of business and financial terms and their synonyms, as well as companies, industries, topics, and trends. Leveraging AlphaSense, corporations and financial firms make confident, quick decisions, enabling them to win in their markets. Used globally by many of the world’s top financial and corporate firms, AlphaSense is headquartered in New York with offices in London, Helsinki, India, and across the U.S.
Brighterion, a Mastercard company, was founded in 2000 and acquired by Mastercard in 2017. The company delivers a leading AI and ML platform that provides real-time, mission critical intelligence from any data source, regardless of type, complexity, or volume. Its AI solution secures billions of transactions monthly and is used by many of the world’s leading organizations and governments in payments, compliance, financial markets, security and defense, healthcare, Internet of Things, and marketing. Brighterion currently serves 74 out of 100 of the largest U.S. banks and more than 2,000 customers worldwide, processing more than 75 billion transactions annually.
IBM Watson Customer Insight for Banking uses advanced prebuilt industry-specific analytic models that combine predictive and cognitive capabilities. The solution enables dynamic behavioral segmentation to uncover actionable customer insights allowing banks to create personalized sales offerings and marketing campaigns. The solution provides intuitive user interfaces and role-specific dashboards specifically designed for line of business users.
IPsoft is an enterprise AI provider and the home of Amelia, a digital AI colleague. Amelia’s ability to learn, interact, and improve over time allows her to fully understand user needs and intentions. Amelia can be trained to recognize words and phrases in more than 100 languages. She delivers real-life business benefits including lower operating costs, higher customer satisfaction, and increased employee productivity. IPsoft was the first company to launch an end-to-end digital platform, 1Desk, to deliver shared enterprise services. By connecting front office conversations to back-end systems, IPsoft automates business processes that serve employees, customers, and citizens, resulting in rapid resolutions, satisfied users, and substantial organizational savings.
Infosys is a global leader in next-generation digital services and consulting. The company enables clients in 46 countries to navigate their digital transformation. With over three decades of experience in managing the systems and workings of global enterprises, it strives to steer its clients through their digital journey. They do this by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. It also empowers the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Its always-on learning agenda drives the continuous improvement through building and transferring digital skills, expertise, and ideas from its innovation ecosystem.
Inbenta Technologies Inc.
Inbenta powers BBVA’s online support experience with a conversational chatbot. The company helps banks increase the quality of customer care without sacrificing time to redundant user queries. With Inbenta, agents can focus on only the most critical issues and divert everything else to our chatbot and semantic search tools for seamless, 24/7 online support. The Inbenta chatbot understands customers in their natural, colloquial language. Using Ibenta’s semantic technologies, the company says it is able to match customer queries to existing answers with 80 to 95 percent accuracy, without relying on keywords or exact phrase matches. In instances during which a chatbot can’t help, or live agent is requested by the customer, the conversation is automatically escalated to the next available agent. The agent is given key insights from previous dialogs for a seamless hand off. Inbenta provides solutions to customer issues in real time as they type problems into support request forms. This allows the technology to solve user issues before they become tickets for support agents. Customers are able to securely access account information, such as account balance, via Inbenta’s web hook processing capabilities. The Inbenta chatbot allows users to integrate with third-party systems to let customers find answers and perform tasks that typically require a human agent.
According to MicroStrategy, this is an era of unprecedented economic, regulatory, and technological challenges in the banking industry. Economic conditions are volatile and low interest rates have impacted profitability. Regulatory requirements continue to increase in scope and complexity, heavily influencing bank operating costs associated with compliance. The explosive growth of mobile devices has helped to make financial information and investment tools readily available to consumers. To compete, the Intelligent Enterprise capitalizes on new technologies and data analytics.
To keep up with massive computing demands, financial institutions like HSBC move their data to the Google Cloud Platform (GCP). GCP runs on the same infrastructure and private fiber network that power Google, giving you the scale you need to run training algorithms, portfolio analysis, and risk modeling at the speed of your business. Whether you are conducting quantitative research, risk simulations, or stress testing, you can spin up workloads faster than you can on other clouds, including clusters with a few hundred—or thousand—cores in minutes. Scale up when you need, and then only pay for the compute seconds you use.
Google’s solutions are easily adaptable for multi-cloud or hybrid environments, and the company provides services to help you migrate quickly and securely.
According to a Microsoft ebook, Banking on AI, AI isn’t going to replace bankers. It’s going to optimize how banks work by helping them become more agile, make smarter decisions, and ultimately stay more competitive. The resource provides real examples, including Metro Bank using AI to analyze customer interactions and track key performance indicators, including customer satisfaction. That way, the bank can identify and address problems before they begin to affect the customer relationship. For regulatory use, as analysts at Mitsubishi UFJ Securities became increasingly overwhelmed by the volume and complexity of regulations, they enlisted Microsoft Azure to help process more than 100 gigabytes of data every night and on weekends—without buying additional servers or leasing a new datacenter. For better productivity, with the help of Office 365, TD Bank is looking to the future of banking by empowering bankers to be more productive, which in turn attracts new talent to join the ranks. To fight fraud, based on Microsoft Azure and Power BI, UBS uses an automated screen engine to catch any sanctioned entities trying to slip through manual “Know Your Customer” checks.
NVIDIA Corporation aims to support massive datasets, perpetual market fluctuations, provide swift analysis, and provide immediate personalized assistance with its AI solutions for the banking industry. According to the company, its intelligent technology addresses critical challenges within the modern financial services industry. With it, institutions can boost risk management, data-backed decisions, security, and customer experiences with NVIDIA’s AI, deep learning, ML, and NLP tools.
Several financial industries are reaping the benefits of AI technologies. Here, we present a case study from SEB, a Nordic retail bank headquartered in Stockholm, Sweden.
Facing increasing IT issues, the company decided it needed to take action to improve efficiency for its employees, especially in relation to IT service. It first implemented IPsoft’s Amelia technology, which was known as Aida at the time, for internal IT helpdesk support. The AI tool helped handle password resets, network connectivity issues, and business application support. Amelia communicates with employees with NLP through a chat interface, if she isn’t able to handle an inquiry; it is escalated to human support with a full chat history of the issue.
Due to its internal success, SEB decided to deploy the AI tool as a customer-facing chat agent to facilitate a variety of customer service requests including booking meetings with branch staff and providing general account and branch office information.
According to IPsoft, the AI tool Amelia is capable of properly determining intent during 93 percent of her conversations. If she can’t determine intent, the company says she escalates the conversation to a human employee.
AI for Finance
Financial institutions look to AI technologies in a variety of formats, including ML, NLP, image processing and video recognition, and cognitive computing. By automating tasks internally and externally, these companies are able to improve customer satisfaction and employee productivity.
AI Applied Magazine, Dec2019
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