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Intelligent Risk Assessment in Insurance

Risk Management is a core function within the insurance industry. It is a vital responsibility of the underwriting team. Insurance companies collect data scattered across different business units in various formats – some of which are paper and digital,  most of which are typically unstructured. The underwriting team doesn't have immediate access to the information required for internal and external decision-making, resulting in delays in making decisions and costly mistakes.

Why Does the Long-term Nature of Life Insurance Products Make Customer Retention Difficult?

Most insurers offer similar products and services, which makes it challenging to attract new customers and retain them. As an industry, insurance is low-touch, and insurers seldom interact with their customers. A report shows that the top companies have an average customer retention rate of 93 - 95 percent, while insurance companies have an average of 84 percent.

A Data Science Approach to Improving Insurance Retention and Persistency

In the Insurance industry, persistency is an essential term to understand. It's all about an insurance company’s ability to retain its customers over a period of time. High persistency means policyholders continue to pay their premiums with little to no lapse. Satisfied customers will continue to pay their premiums. The lack of payment is a good indication of an unhappy customer.

Data Drifted, Now What? Identifying and Responding to Data Drift

“Change is not only likely, it’s inevitable.” – Barbara Sher What is Data Shift or Data Drift? Given human nature, it is very natural that the data we collect will change over time. Changes in data such as behavior and preferences are fast and drastic. It is even more relevant today with the impact of the Covid-19 pandemic making unprecedented changes to businesses. For a data science practitioner, the stability of data and its source are salient to develop and maintain robust ML (machine learning) solutions. Changes or drift in data will degrade the performance of predictive models.

Ways and Means to Build Trust in the Digital Era

This is part 2 of a 2-part series "Trust: The Key Ingredient for a Successful Insurance Customer Journey." In Part 1 of our blog series, we discussed how important it is for an insurer to display and build trust in any customer experience. The trust factor has continued to rise and is becoming much more significant. The buyer's journey is to garner trust. Buyers prior to 2010 usually rated insurance companies' trustworthiness and confidence level based on their responses to their inquiries. He validated information he collected from friends and relatives that were already existing customers. During that time, there was very little information about the insurer's finances in the public domain, so he had to rely on hearsay. In that process, the buyer zeroed in on a particular insurer or seller.

Unveiling a Whole New World of CX Insights

As 2021 came to a close, we couldn't help but notice how what was inevitable in the future was becoming necessary now. While a normal practice would be to predict what lies ahead of us in 2022, we decided to take a different approach this year. In our second edition of the Aureus yearbook, we will take a closer look at what has delivered superior CX (Customer Experience) in the insurance industry this past year. While there is nothing new about focusing on your customers, we shall examine the role data has played in assisting companies up their CX game.

Transfer Learning: A New Age of Machine Learning

In recent years, Machine Learning (ML) algorithms have advanced and are now capable of learning accurate and complex patterns provided large and labeled data samples are available. However, many ML implementations fail to generalize when new data points are encountered, especially data points with different and unseen patterns or conditions from training samples.

Trust in the Evolution of the Customer's Journey

This is part 1 of a 2-part series "Trust: The Key Ingredient for a Successful Insurance Customer Journey." Today, everyone in the business world is talking about the customer journey and experiences starting from E-commerce, banking, and many other industries. So, what is customer experience? What is new about it?

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."

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