It is a whole new world due to the pandemic. The life insurance industry settled more claims in the year 2021 than in 2020 due to this Black Swan event. A sudden demand for life insurance policies and increased claims induced operational changes for the insurance industry. As we head into the new financial year, there is no end yet to the anxiety as variants of the Covid-19 virus continue to emerge. Given improved economic sentiments, greater appreciation for its need and increased vaccinations, life insurance companies are expected to do a lot more in the new Financial Year (FY) 2023.

Machine learning has the potential to generate millions of dollars in savings and revenue growth for organizations. But unless ML models are actually put into production, it's just a bunch of useless code. This is the big data science takeaway from New York Life, which recently adopted an MLOps solution from Domino Data Labs to streamline model deployment. Since it was founded in 1845, statistics have played a central role for New York Life. Like all life insurance companies, New York Life dedicates resources to maintaining accurate actuarial tables, which play a big role in determining premiums, payouts, and profits.

If you ask a lay person on the street what life insurance is, and they'll tell you it is a policy you buy that pays a sum of money to your family when you die. Ask them to explain how life insurance works, and they will probably tell you it is a contract between an insuring company and a policy owner. Now ask them how artificial intelligence (AI) and aging research can help life insurance firms and policy buyers make decisions with conviction, and they'll scratch their heads and likely walk away from this conversation, or give very general answers. And while the customers are pretty much in the dark, some of the more innovative insurance companies are building substantial internal and external capabilities in both aging research and artificial intelligence. And there are hundreds of startups with more or less credible technologies that the life insurance companies are partnering with directly or through the open innovation hubs.

The global life insurance industry has seen significant changes over the past decade. Developing economies--predominantly emerging markets in Asia that were formerly small contributors--have become global growth drivers and now account for more than half of global premium growth (Exhibit 1) and 84 percent of individual annuities growth (Exhibit 2). The availability of data has skyrocketed, and insurers have made progress in advanced analytics and artificial intelligence. Digital and mobile advances have raised the bar on transparency and service quality: customers can now file claims and access agents, insurance quotes, and policy information with a few taps on a screen. The past decade has also introduced new challenges. Life insurers have not benefitted from the bull market (Exhibit 3). Global penetration fell to 3 percent, and premium growth within most developed markets, hovering just below 2 percent per year, struggled to match GDP.

Every crisis presents an opportunity and covid-19 is no different. Like in many others, the pandemic has changed consumer behaviour in the life insurance industry as well, leading to greater interest in pure term insurance plans. Also, self-service usage has seen a sharp uptick in these times, as an increasing number of Gen X and Gen Y customers are adopting self-service options. Not long ago, on-boarding required customers to fill up application forms, a laborious process which involved a lot of paperwork and anxiety. Also, the fulfillment journey required multiple hand-offs and disparate systems leading to customer experience issues.

Tel Aviv, New Delhi - November 7 th, 2019: Tech Mahindra Ltd., a leading provider of digital transformation, consulting and business re-engineering services and solutions, announced today its collaboration with Atidot, an Israel based InsurTech that offers predictive, analytics, Artificial Intelligence (AI) and Machine Learning (ML) tools for the life insurance and annuity companies. Through this partnership, Tech Mahindra and Atidot will provide a one-of-a-kind platform to increase profitability for insurance companies by predicting customer behavior, lapse patterns and improve their cross-sell as well as up-sell capabilities. The solution brings new benefits to life insurance policyholders by offering them policies that are more appropriate, have better coverage as well as protect retirement savings. The solution will also empower insurance providers to assess coverage needs and remedy under or over-insured policies in a timely and responsible manner. For life insurance providers, the solution will help them effectively capitalize on revenue potential - be it addressing and correcting underinsured policies to increase premium collection, leading better customer engagement, and reducing lapse rates thereby maximizing the number of profitable policies for the provider.

Machine learning models enabled by artificial intelligence (later referred also as AI) complement the work of designers by efficiently analyzing vast amounts of quantitative data. Based on the quantitative data collected from customers, AI is able to create various alternative hypothesis on what kind of impact design can achieve. Furthermore, by modeling customer behavior machine learning models can predict which combinations of various possible qualities haves the greatest potential for improving the customer experience. The evidence of Design 2.0 describes a collaboration between a European service design agency and a Nordic life insurance company. Machine learning models predicted that feeling of caring will have the most significant impact on customer satisfaction, customer loyalty and NPS (Net Promoter Score) of the life insurance company.

The U.S. life insurance industry is beginning to understand the vast potential benefits of robotic process automation (RPA) and artificial intelligence (AI). These two related breakthrough technological innovations leverage the power of machine learning to increase productivity and reduce the risks associated with human error. Of course, many professionals in our industry find the names of these technologies unappealing, prompting skepticism from the outset. These reactions are often rooted in fear of the unknown, apprehension that is unnecessary once we understand the essence of the technologies. RPA and AI are often used in tandem to complete a transaction and are currently utilized in many customer servicer interactions we encounter daily.

Fidelio Desbradel and his wife, Leonor Desbradel, of the Dominican Republic, take a selfie in front of a Tulip Magnolia tree in Washington. A selfie reveals more than whether it's a good hair day. A company has developed facial analytics technology to help estimate life expectancy by analyzing your face from a photo you upload online. Life insurance companies are interested in the product because it may help them reduce your wait for coverage and boost their sales. A selfie reveals more than whether it's a good hair day.

A selfie reveals more than whether it's a good hair day. Facial lines and contours, droops and dark spots could indicate how well you're ageing, and, when paired with other data, could someday help determine whether you qualify for life insurance. This new technology would enable people to buy life insurance online in as little as 10 minutes without taking a life insurance medical exam. The facial analytics technology would scan hundreds of points on your face and extract certain information, including your body mass index, physiological age (in layman's terms, how old you look) and whether you're aging faster or slower than your actual age. The insurer would combine the results with your application answers and, if it chooses, any other information it typically pulls.