Home Breadcrumb caret Your Business Breadcrumb caret Tech How you can make artificial intelligence more than just a ‘sexy sound bite’ Artificial intelligence may make for a wonderful sound bite, but insurance providers need to use this emerging technology to cut costs and serve customers better, two financial services executives warn. The financial services industry is “still at a stage where AI is about companies coming out with sexy sound bites,” Kamana Tripathi, vice president of […] By Greg Meckbach | May 22, 2018 | Last updated on October 30, 2024 2 min read Artificial intelligence may make for a wonderful sound bite, but insurance providers need to use this emerging technology to cut costs and serve customers better, two financial services executives warn. The financial services industry is “still at a stage where AI is about companies coming out with sexy sound bites,” Kamana Tripathi, vice president of global markets at TD Securities, said during a recent webinar. But AI “has to evolve” such that it has an actual “impact” on customers, she added, citing omni-channel communication as an example. She made her comments this past Thursday during Sharpen Your Competitive Edge – Drive action from AI & Advanced Analytics in Insurance, a webinar hosted by Insurance Nexus, a unit of FC Business Intelligence Ltd. Also on the webinar was Craig Milroy, director of enterprise data architecture at Sun Life Financial, who described how people conceived of “Big Data” 10 years ago. “Everyone was doing it, and not doing it well,” Milroy said of Big Data. “No one could quite understand what Big Data is, and today I think we are in the same space [with AI],” Milroy suggested. In essence, AI is when computers can mimic human cognition and activities such as identifying patterns, making decisions and taking actions, Mark Breading, a partner with Boston-based Strategy Meets Action, wrote in a paper published in 2017. Machine learning is described by data analytics provider SAS Institute Inc. as a branch of AI in which computers can act without being explicitly programmed to do so. Some everyday examples of machine learning include receiving content in news feeds on Facebook, receiving recommendations for content to watch on Netflix, and e-mail servers that flag messages as spam, Jeffrey Baer, manager of advanced analytics for Economical Insurance, told Canadian Underwriter earlier. Sun Life is exploring how the insurer can “start to augment machine learning techniques within the claims handling process,” Milroy said during the Insurance Nexus webinar on May 17. Using larger data sets, insurers could “fast-track certain claims,” reducing the processing time and ultimately the cost to process those claims, he adds. Insurers can also use AI to administer documents such as form, e-mail, invoice and claim, and policy comparisons, much of which is processed manually, Tripathi said. Competing against new insurtech startups is one challenge for large established insurers, Milroy suggested. At Sun Life Financial, company officials are asking how they can “change the culture to be more data centric” and how to have “more of a startup mentality” when it comes to using technology, Milroy suggested. Greg Meckbach Save Stroke 1 Print Group 8 Share LI logo