Mitsubishi UFJ Financial (MUFG) is a Japanese holdings bank and financial services company ranked 5th on S&P Global’s list of the top 100 banks, and the largest Japanese bank on the list.
Large insurance companies have been experimenting with AI since the middle of the 2010s, piloting chatbots and collecting telematics data for future AI projects. The insurance industry more than many others relies on the collection of data to make critical business decisions. Whether writing policies, or processing claims efficiently the way insurers employ data will determine the lifetime value of the customer.
The financial sector was among the first to adopt artificial intelligence in business by automating fraud prevention with anomaly detection technology. Now financial institutions, including lenders, stand to benefit from automating back-end processes by digitizing documents and eliminating manual data entry.
Event Title: Launch of the OECD AI Policy Observatory
Event Host: OECD
Applying AI to the real world is much more difficult than applying it in digital ecosystems; this is what makes robotics use-cases in business so much more difficult than applications such as AI-enabled fraud detection.
Large enterprises are eager to use artificial intelligence software, but many of them aren't aware of the hardware required to execute many AI capabilities. To get a better idea of these hardware considerations, Emerj spoke with Victoria Rege, Director of Alliances & Strategic Partnerships and Graphcore, for Kisaco Research's AI Hardware Summit in Europe, which takes place October 29 - 30 in Munich, Germany.
In banking and finance, chatbots have the potential to improve the customer experience by allowing customers to check their account balances, transfer money, learn about interest rates, change their billing addresses, and more.
This article is based on a presentation given by Emerj CEO Daniel Faggella in Geneva, at the 2019 New Shape Forum: Weapons Governance for the Geneva Disarmament Platform. To learn more about Emerj's AI presentations and speaking, visit our presentations page.
AI may have a role to play in digitizing the paper-heavy mortgage process, facilitating more streamlined search and discovery for entities across a variety of digital and scanned PDF documents. We spoke with Dan Cortright, Senior Director of Product Management at Iron Mountain, about just that. Courtright discusses how AI could help approve loans quicker, better assess risk, and allow employees to pull up documents they need to respond to customer requests.
Event Title: NEXT Technology Conference
Event Host: Syracuse University
Financial institutions have challenges around data accessibility. They want to leverage their large amounts of data so their employees, such as customer service agents, can find the information they need quickly.
Many of the key processes in industries such as banking and insurance are still done on paper. That said, many large enterprises seem to be in the process of digitizing parts of these processes in order to prepare for forays into automation and artificial intelligence.
Event Title: 2019 New Shape Forum: Weapons Governance
Date: September 30, 2019 - October 1, 2019
When it comes to process automation, digital transformation leaders are now navigating the artificial intelligence hype. Although AI can yield some impressive results when it comes to digitizing processes that still involve paper and reducing the time customer service agents spend searching for customer information, leaders are perhaps too excited to jump into AI without knowing the fundamentals of what it entails.
Event Title: PayThink 2019
Date: September 18 - 20
Presentation Title: Artificial Intelligence and the Future of Payments - Critical Use-Cases and Trends
Event Title: Countering Terrorism Through Innovative Approaches and the Use of New and Emerging Technologies
Robotic process automation, or RPA, has dominated much of the automation conversation in the insurance industry for several years. RPA is able to capture manual steps that employees take to log into software, search documents, and enter data and replicate them.
We set out to create a report that would be particularly useful for executives and business leaders who are looking to get started with an AI initiative, as well as IT and management consultants who want to competently and effectively guide their clients through AI adoption.
Event Title: INTERPOL World 2019
Event Host: INTERPOL
Date: July 2 - 4, 2019
Ten years into the longest economic expansion on record, auto lenders are looking for ways to leverage new opportunities for growth and risk reduction.
We interviewed Jay Budzik, CTO at Zest AI, about the business value of machine learning for auto lending. We speak with Budzik about how underwriting, lending, and credit scoring is evolving as a result of advances in machine learning - both in terms of new data sources, and more advanced algorithms.
Oil and gas companies face many of the same challenges as large banks and established insurance firms when it comes to searching through their backlogs of documents. They want to use the data stored within these documents to make decisions on where to drill and determine whether or not they’re in compliance with laws and regulations.
Customer data is essential for insurance firms to stay competitive in the coming decade. Insurance companies at present have backlogs of data on past and existing customers in the form of policy agreements, applications, and claims forms. They’ve also collected millions of images showing car damage, property damage, and personal injuries.
Large banks deal with millions of documents every day across their corporate offices and numerous branches. Although one might assume that these documents are digital, in many cases, even the largest banks store old physical documents in file cabinets and boxes off the bank’s premises, and even those that are kept on-site might be relegated to storage units amongst hundreds of thousands of other documents.
Event Host: Harvard Univesity
Date: April 12, 2019
Team Member: Daniel Faggella, Emerj Founder and CEO
Event Title: Artificial Intelligence and Robotics: Reshaping the Future of Crime, Terrorism, and Security
Machine learning has far-ranging applications in the finance space broadly from document digitization to document search, chatbots to fraud detection. The insurance space in particular, however, stands to benefit from AI and machine learning applications in a few unique ways. They could help insurance firms with a challenge that’s at the forefront of the insurance world: attracting and meeting the needs of millennial customers.
In the last year, interest in so-called “autoML” has risen greatly in part due to its promise of bringing artificial intelligence to businesses that have been blocked from accessing it due to its serious time, talent, and budget requirements. Although machine learning may still be widely unavailable to small businesses, medium-sized businesses may find that autoML allows them to make use of it in the coming years.
The finance sector has proven itself an early adopter of AI in comparison to other industries. As such, the applications of artificial intelligence and machine learning in finance are myriad. Traders, wealth managers, insurers, and bankers are likely well aware of this in some form.