Part two of a conversation with Amanda Turcotte, senior vice president and chief actuary at Amalgamated Life Insurance Company.
Editor's Note: This article is from a longer interview and edited for clarity.
How is AI being applied to customer service?
It's the ability for a customer service rep to obtain information faster, from policy documents that previously they had to skim or read through. They could miss things. When an AI agent is able to skim through data from a policy administration system or policy documents, and merge those so that information is at the fingertips of the customer service rep, that allows them to resolve customer issues in one call quickly, rather than having multiple back and forths. It's a way better customer experience.
This is not exclusive to insurance, but insurance carriers are making that customer sentiment feedback available to the customer service rep. It's being able to see how the AI is analyzing that person's tone, voice and word usage to raise a red flag early. If someone is getting upset, it can help de-escalate the situation or call for help. If you're busy and you're answering a lot of calls a day, you might not notice that an AI agent can recognize that customer sentiment faster than an analyzer can. It's making a lot of the reps that work with our clients every day a lot more effective in their interactions.
How can technology address issues with data for actuaries?
There are definitely tools that the actuary can use today. Emerging techniques on the actuarial side are natural language processing, which we can apply to claims data, general medical briefs, emerging medical briefs, and trends in morbidity and mortality. You can use transfer learning, and apply pre-based or pre-trained models to some of the data sets you already have. These wouldn't necessarily be used for assumption setting or deciding what your baseline assumptions are.
They are very good at highlighting areas to stress test. In actuarial practice, whether it's the valuation or the assumption side, we don't ever have one answer and say, that's the answer. We have a base model, then if a factor changes by 5%, here's how it changes the outcome. If that factor changes by 15%, this is the outcome. These emerging technologies let you see what areas we should stress test that maybe we didn't two years ago. They help make sure that premiums are sufficient, that the reserves that we're holding in the company are sufficient to cover claims, and that they're sufficient under a variety of circumstances.
What's the biggest challenge that you have in your role at Amalgamated?
Getting up to speed as fast as possible on the history of a company that's 70 years old, and has a lot of business on its books. But it's interesting because I've worked in large companies, and obviously at a large company, you have tons of actuaries and lots of resources. Amalgamated is a smaller company, for sure. We have a great actuarial team, but we're small and mighty. It's an interesting transition, like learning where my network is and making sure that network is connected to the rest of my team.
We're cross training, staying current on emerging trends and best practices. Large insurance carriers are often the ones at industry meetings setting best practices. They have a ton of resources to put into the research. We want to make sure that we advocate in the industry for smaller carriers whose priorities aren't always the priorities of the big guys. That's my focus in the next year or two.
