This is Part 3 of our blog series, "Data Science Use Cases in Insurance." The insurance industry isn’t the same as it was 20 years ago. It has become much more competitive as tech companies come into the picture with new and innovative ways to compete in order to gain a foothold in the insurance industry. Consumers want to save money and will make their decisions based on the lowest price available. Some websites will help the consumer compare carriers’ prices and offerings to choose the best deal. Unfortunately, this is causing insurance companies to make price their priority over quality and customer satisfaction.
In our earlier blog, Insurance Agents - Will They Disrupt or Perish?, Aureus' Life Insurance SME Arun Agarwal shared his views on why insurers will remain invested in the agency channel by identifying the successful agent. It was a pleasure to have Tarannum Hasib, Chief Distribution Officer at Canara HSBC OBC Life share her expertise on the current state of insurance distribution as well as strategies to optimize it for the next stage of evolution.
This is part 2 of the blog series, "Data Science Use Cases in Insurance."
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.
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.