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3 Ways to Target the Right Customers in the Insurance Industry

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.

A Demanding Future for the Insurance Distribution Industry

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.  

Enhancing Customer Engagement in the Insurance Industry

This is part 2 of the blog series, "Data Science Use Cases in Insurance."

Why Data Science is a Game Changer for Insurance Industry Today and Tomorrow

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).

Insights That Power Insurance

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.   

Technology is Key to Surviving in the Modern Insurance Market

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.

Data-Driven Insurance: The Challenges Faced by Data Scientists

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.

Data-Driven Insurance: The New Normal in the Post-Pandemic World

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.

Understanding Agency Sentiment

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.

Using AI for Increasing Agent Productivity

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.

How to Structure the Sentiment Analysis Process for Insurance Data

Sentiment reveals a lot about what customers think about an insurance brand, including how well customer representatives are resolving issues and how happy customers are with the underwriting process. This is where the sentiment analysis of structured and unstructured data can help insurers understand how their customers are feeling.

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