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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.

According to Fortune, JPMorgan Chase is the largest bank in the U.S. and controls over $2 trillion in total assets. In this article, we detail the types of AI research JPMorgan is doing as well as how they are likely to be using their applied AI applications.

The military is always looking for ways to innovate its technology for weapons and vehicles, and it follows that AI and ML would become part of that work in the current decade. Currently, the Army is testing autonomous vehicles and aircraft for battlefield use. However, most AI applications for these vehicles do not have clearance to operate the weapons attached to them. 

Banks and other financial institutions can be tight-lipped about how they implement AI technologies within their businesses. Citi, however, has been relatively open about their current AI initiatives. Since 2017, they have published press releases and other announcements of AI initiatives that are both internal and customer-facing.

Predictive analytics is perhaps one of the most common AI applications used by financial institutions, banks, insurance companies, and healthcare companies. This type of software allows business leaders across these industries to plan for the most probable outcomes in business areas such as credit, loans, and patient health. Predictive analytics software could make predictions about future business events based on typical company experience using historical enterprise data.

The financial sector was one of the first to start experimenting with machine learning applications for a variety of use-cases. In 2019, banks and other lenders are looking to machine learning as a way to win market share and stay competitive in a changing landscape, one in which people are no longer exclusively going to banks to handle all of their banking needs.

Event Title: PayThink 2019

Date: September 18 - 20

Presentation Title: Artificial Intelligence and the Future of Payments - Critical Use-Cases and Trends

This article was written by Sergii Gorpynich, co-Founder and CTO at Star, co-written by Perry Simpson, Managing Director of Star, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines. Learn more about reaching our AI-focused executive audience on our Emerj advertising page.

Four months ago we launched our AI in Banking podcast where we covered some of the most critical topics related to AI adoption and implementation in banks and financial institutions each month. Our series was based on interviews with AI industry experts, many of whom also shared their valuable insights during our first comprehensive banking research project, the AI Vendor Scorecard and Capability Map.