Partner Content Articles and Reports
This section features our sponsored interviews, articles, reports in partnership with some of the most exciting brands in artificial intelligence. Explore our library of partner content below:
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.
In the past, we’ve explored the need for insurance companies to adapt to millennial buying preferences through customized policy offerings and a more personalized customer experience. AI could help to these ends, but how could insurance carriers reach this point of AI transformation?
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.
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.
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.
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.