Automating commercial insurance is the future of the industry. Artificial intelligence (AI) and machine learning (ML) are improving targeted interactions and risk transfer solutions, but adoption among commercial insurers has been a major hurdle.
Rajesh Datta (pictured), SVP of insurance and healthcare at WorkFusion, an intelligent automation provider, is working to improve the commercial lifecycle through point solutions for specific processes.
“One aspect of automation-driven technology is the focus on task orientation,” he said. “We’ve taken the approach to combine AI with the ability to train models and leverage data enrichment.”
WorkFusion enhances efficiency within commercial insurance by implementing intelligent automation to business processes. The firm also stays on top of technological trends, which are rapidly evolving.
“The pandemic didn’t necessarily trigger [the demand for] data, but it enhanced the need and usage of it, especially when it came to commercial lines and monitoring business,” Datta explained. “On the automation side, many have gone down the path of rules-based automation.”
Using AI and ML to intuitively automate processes, rather than using the technology for a definitive set of rules, offers a more comprehensive integrative strategy if the end goal is to eliminate manual review.
“There has always been an issue of people spending ample time on multiple tasks that may not be specific to the vocation, especially in commercial insurance,” he said. “That’s where our philosophy of digital workers comes into play.”
Datta mentioned that digital workers leverage what has already been learned and they help to overcome challenges in the commercial lines space by collecting data.
“It’s an ongoing effort to get the data necessary to train models,” he added.
When working with commercial carriers, it is important that data is being used to train models, according to Datta.
Over the past two years, there has also been an uptick in submissions, and automation has changed the game when it comes to picking up those submissions and underwriting commercial business.
“There was an efficiency problem so we asked ourselves: What we can do from an automation perspective to approach underwriting?” Datta emphasized.
A common industry misconception is that digital processes will take work away from underwriters, but it actually helps prioritize time on what needs to be done.
“We want to apply efficiency, demonstrate immediate costs savings, and sustain those savings,” he said. “Our digital worker strategy is not to go in and replace someone, it is to act as a supplemental role and handle backlog that occurs from increased volume.”
Hiring staff to handle excessive backlogs takes a lot of time and training, whereas technology is able to work in tandem with experienced underwriters.
A submission could contain multiple core forms, loss runs, statements of values, unstructured data in the form of an email, and evaluating all of that is a lengthy process.
"Automation, in the form of our digital worker Ilana, is a time-saving scenario for the underwriter and allows agents to deliver timely quotes, increasing opportunities to win business," Datta added.
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“At the end of the day, you want to beat your competitor and give a faster and more comprehensive response to the agent,” he said. “The purpose of this whole process is to identify the aspects that can be automated, learn, and train the model to limit those types of interactions going forwards.”