Equisoft conducted a series of interviews with eight prominent industry experts, to get their insights into key issues shaping the future of the life insurance industry. and maximizing value from digital transformations. The discussions centered around topics that are critical to insurers’ ability to maximize value in their digital transformations, including digital transformation best practices, data transformation & data governance, and the future of customer experience. These interviews shed light on what a variety of experts believe about the potential impact of AI, large language models, and analytics as well as strategies for leveraging solutions most effectively.
Featured experts include:
- Kartik Sakthivel – VP & Chief Information Officer, LIMRA
- John Keddy – Senior Principal, Datos Insights
- Russ Bostick – Managing Partner, MVP Advisory Group
- Keith Raymond – Principal Analyst, Insurance, Celent
- Nanda Rajgopal – Principal Analyst, Insurance, Celent
- Matthew Scott – International Director, Altus Consulting
- Caribou Honig – Chairman and Cofounder, InsurTech Connect
- Amanda Turcotte – Principal Owner, Turcotte Consulting LLC.
Insights on Governance and Best Practices #
In this video interview, industry experts unveil the crucial steps insurance companies must take today to leverage their data to shape tomorrow's solutions.
Interview Question: What governance, organizational and best practices should insurers be working on today to lay the data foundations for tomorrow’s solutions?
- Kartik Sakthivel, VP & Chief Information Officer, LIMRA
Edited transcript featured answer: Kartik Sakthivel, VP & Chief Information Officer, LIMRA
“For the past several years, ever since the implementation of the of the first insurance policy, the industry has collected tons and tons and tons of data, right? But I think the problem the industry faces isthat we've been treating data as a byproduct of our systems and not as a product, not as a first-class citizen. So, you can't necessarily take all of these practices or malpractices around data and just pivot them over into monetization of data, commoditization of data, using that same data to feed artificial intelligence and machine learning models.
“So, organizations need to take a step back and make sure that your data is clean, accurate, secure, reliable, in one place at one time, of pristine quality, to be able to do anything with your artificial intelligence programs. And that starts with data strategy and governance. Lots of organizations have data strategy and governance programs. But at the end of the day, with all these governance programs, it's not about a tool. It's not about a process. Yes, it's all of those things. But at the end of the day, it's about culture. And treating data with the respect that it deserves.
“Within an organization, it's about culture. So, my guidance to organizations continues to be, make sure that you're espousing a culture and evangelizing a culture where data is treated with the appropriate respect. Your employees are data literate. That means they are on the front lines to be able to discern good data from bad data and they know how to handle data; they know how to treat data through the entirety of your value chain. So, all of the data governance and strategy, programs and organizations are predicated on organizational culture around data.”
Innovative Approaches that are Reshaping the Landscape of Data Management #
In this video interview, insurance industry experts reveal actionable solutions for harnessing the power of data to enhance customer experiences and operational efficiency.
Interview Question: What are some of the interesting ways industry stakeholders are leveraging data to create value for their business and clients?
- John Keddy, Senior Principal, Datos Insights
Edited transcript featured answer: John Keddy – Senior Principal, Datos Insights
“So, in 2023, this has really been the year of AI. Therefore, there's intense focus on data, which of course is needed to fuel machine learning in so many aspects of artificial intelligence. Over the past several years, virtually every insurer that I know of has made significant investments in data. Now those companies are finding out, were those investments strategic enough to support artificial intelligence, or are some of those investments more sub-optimized because they were more operational? That doesn't mean that operational investments in data don't have value, they do, but it doesn't always mean it can be leveraged for artificial intelligence.
“I think one of the most critical things that we're seeing in 2023 around data is a real focus. Will this help us advance in the world of AI? Will this investment something that we can leverage and really make something of the capabilities that we're seeing throughout the AI domain?”
The Potential of AI, Large Language Models, and Analytics Solutions #
The key to harnessing the full potential of your data lies in understanding the opportunities that data presents, particularly in the realms of AI, large language models (LLM), and analytics solutions. In this video, experts reveal how data will impact the next wave of technology – from BI to AI and beyond.
Interview Question: What opportunities does data present for the next wave of technology – especially AI, large language models, and analytics solutions?
- Russ Bostick, Managing Partner, MVP Advisory Group
Edited transcript featured answer: Russ Bostick – Managing Partner, MVP Advisory Group
“Most people want to know on the insurance side, how can I better serve prospects, agents and policyholders? And a lot of that can be improved upon if you're able to collect public data about individuals and then present to them potential ideas and solutions that they wouldn't otherwise have considered. You have to work around privacy and permissions to do that. But organizations that have a strong sense of who their buyers are, who has a proclivity to buy and how they can architect offers and deliver them to those people through the agent of choice or directly depending upon the model and play are going to succeed more- a in addition to that find, that the people that they're working with are more loyal to them after they've joined.”
The Future of Customer Experience #
Organizations affecting change across the entire value chain and placing the customer at the center are poised for the most significant success. In this video interview, industry experts shed light on what CX will look like 5 years from now – a future that will arrive faster than we imagine.
Interview Question: What do you think customer experience will look like for life insurance consumers in 5 years?
Keith Raymond, Principal Analyst, Insurance, Celent
Edited transcript featured answer: Keith Raymond – Principal Analyst, Insurance, Celent
“Hyperpersonalization is coming, and I think artificial intelligence is going to get us there. Generative AI is going to help. It's going to increase the more humanistic responses for intelligent automation, especially in chatbots and other areas. I look at the agent, the customer, and the CSR all in the same bucket as far as the possibilities and I think generative AI and AI in general are going to be able to accelerate the personalization experience.”
Getting Value from Digital Transformation #
Discover actionable tips and best practices for successful implementation of your digital transformation journey, ensuring greater levels of automation, better CX, lower costs and faster, more impactful new product development.
Interview Question: What’s your best piece of advice for carriers seeking to get value from their digital transformation quickly?
Nanda Rajgopal, Principal Analyst, Insurance, Celent
Edited transcript featured answer: Nanda Rajgopal – Principal Analyst, Insurance, Celent
Start with data strategy and the cloud. Those are two very important elements. And then get into low code, no code, and artificial intelligence, not in any particular order. Once you have that, then you can work on your core systems, your corporate systems, and your surrounding systems. And don’t forget the innovation stream that cuts across all of these different elements. So start with data and cloud-first in any transformations.