This article is Part 1 in a 5-part series titled "Data Science Use Cases in Insurance." Today everyone is talking about Artificial Intelligence (AI). But what is AI? AI is a science that enables computers to think like human beings. Is AI a new concept in the field of computer science? No, AI has been around for more than half a century now. (The term “Artificial Intelligence” was coined in 1956).
The past two decades of the insurance industry has seen a lot of experimentation of distribution models: Max Life starting with a multi-level marketing model, Aviva trying to build both agency and bancassurance channels simultaneously, Canara HSBC starting with only bancassurance model and experimented with an agency in between, Pramerica Life & HDFC Life replicated agency sales channels to target a cluster of consumers formed, basis occupation or usage of common services.
In the post-CoVID-19 era, a tremendous amount of focus, time, and energy has been invested in understanding the customer or policyholder based on the insurer's proprietary data and the data collected by many other research agencies. The customer is deeply analyzed and offered customized or personalization, as we call, solutions and offerings. However, the investment made by insurers has only been focused on 5% of the number of policies sold or approximately 11 Lacs policyholders, that are sold by direct sales, web aggregators, and online sales. This begs the question, why are insurers only investing in distribution channels that represent 5% of the number of policies sold?
While the world around us is changing so rapidly, adapting to this change is no longer an option but a necessity to survive. The Indian Insurance Industry, too, as a whole, has proven its resilience in the current dynamic context but nevertheless continues to face various challenges to be dealt with as it navigates through this evolving landscape. As innovators, we at Aureus Analytics felt the urge to aid these giant strides with a little insight from the who's who of the industry. Thus, came about the metamorphosis of 'Aureus Insights' from a weekly blog to a periodically published yearbook in India that encapsulates this changing trend in the inaugural edition, the AI landscape, and a bird's eye view of what we can expect on the road ahead.
The insurance industry in India is expected to reach US $280 billion by 2020-2021. The life insurance industry is expected to increase by 14-15% annually during the next three to five years. With such rapid growth in the life insurance market, the number of fraud casess is also expected to increase. Recent reports suggest that fraud consume more than 8.5% of the revenue that the industry generates.
One of the challenges faced by data scientists is dealing with unstructured data using traditional machine learning models. These models are trained on structured data that have input features with corresponding output labels. When using unstructured data, the data cannot be directly used as an input feature. One approach is to use Artificial Neural Networks (ANN) to unlock business insights from unstructured data.
Digital is the key player in this time of the Covid-19 pandemic. Insurance companies are embracing digital channels now more than ever to reach out and connect with current and prospective customers. Covid-19 has changed the public’s outlook on insurance. Its value is perceived to be more critical as folks are considering the consequences of not being covered. Because of this, it’s essential now more than ever to provide consumers the ability to research products online without the assistance of agents, and at the convenience of their own home. Insurance companies must provide the tools and means to analyze various insurance products, provide price transparency, and a clean digital environment that is easy to navigate and execute.
In my earlier blog, “Data-Driven Insurance: The New Normal in the Post-Pandemic World,” I concluded that in the future, the insurance industry would be data-driven. Not only data-driven, but we’ll see the use of emerging technologies like Artificial Intelligence, Image Recognition, and Natural Language Processing BOTs will be the buzz words in the corridors of the Insurance industry.
This is the age of data. This pandemic has forced us to find new ways to get our work done without putting ourselves in danger. Consumer buying behaviours have changed in order to adjust to this new normal in the post-pandemic world. Before we talk about the changes in the business to navigate in the next two years, we should have a glimpse of the insurance business: What, How, and Why of the insurance business.
In our previous blog article, “Using AI for Increasing Agent Productivity,” we discussed how many insurance companies can only analyze agent productivity based on the premiums written and the loss ratio of their network of independent agencies. In part 2 of our series of articles on “The Top 3 Emerging Trends for Agent/Advisor Analytics Using AI”, we will focus on the benefits of understanding agency sentiment for insurance companies that utilize a network of independent agencies.
Currently, many insurance carriers can only analyze agent productivity based on the premiums written and the loss ratio of their network of independent agencies. Looking only at past results doesn’t necessarily provide an accurate view of how an insurance carrier can increase agent productivity going forward. By using AI for increasing agency productivity, insurers can now predict the best course of action as opposed to waiting to review past results.