---
title: Aureus Insights | Insurance Analytics
description: Insurance Analytics | Aureus Analytics | Aureus Insights
---

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# ![aureus-insights_logo](https://blog.godonna.ai/hs-fs/hubfs/aureus-insights_logo.png?width=200&name=aureus-insights_logo.png)

- [Insurance Analytics](https://blog.godonna.ai/blog/topic/insurance-analytics)
- [Artificial Intelligence](https://blog.godonna.ai/blog/topic/artificial-intelligence)
- [Customer Experience](https://blog.godonna.ai/blog/topic/customer-experience)
- [All](https://blog.godonna.ai/blog/topic/all)
- [Retention](https://blog.godonna.ai/blog/topic/retention)

# [Data and Innovation: 2 Sides of the Same Coin](https://blog.godonna.ai/blog/data-and-innovation-2-sides-of-the-same-coin)

[Read More →](https://blog.godonna.ai/blog/data-and-innovation-2-sides-of-the-same-coin)

- [All (55)](https://blog.godonna.ai/blog/tag/all)
- [Artificial Intelligence (40)](https://blog.godonna.ai/blog/tag/artificial-intelligence)
- [Customer Experience (37)](https://blog.godonna.ai/blog/tag/customer-experience)
- [Insurance Analytics (34)](https://blog.godonna.ai/blog/tag/insurance-analytics)
- [Retention (5)](https://blog.godonna.ai/blog/tag/retention)

<https://blog.godonna.ai/blog/data-and-innovation-2-sides-of-the-same-coin>

## [Data and Innovation: 2 Sides of the Same Coin](https://blog.godonna.ai/blog/data-and-innovation-2-sides-of-the-same-coin)

As we set our feet in 2023, having experienced a roller-coaster ride last year thanks to the geopolitical tensions and some lingering rub-off effects of COVID-19, it drives home that "change is the only constant." Like any other industry, insurance is undergoing paradigm changes at different levels, whether recruiting potential candidates or customer onboarding, to name a few. However, a common thread that ties the myriad business functions of an insurance company has been data and innovation. There has been an ever-increasing need for insurance providers to use data and embrace innovation in their routine activities, eventually to stand the cut-throat competition.

- [Prerana Suvarna](https://blog.godonna.ai/blog/author/prerana-suvarna)
- 8 min read
- Mar 01, 2023

<https://blog.godonna.ai/blog/intelligent-risk-assessment-in-insurance>

## [Intelligent Risk Assessment in Insurance](https://blog.godonna.ai/blog/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.

- [Yogesh Dhavale](https://blog.godonna.ai/blog/author/yogesh-dhavale)
- 8 min read
- Sep 27, 2022

<https://blog.godonna.ai/blog/why-does-the-long-term-nature-of-life-insurance-products-make-customer-retention-difficult>

## [Why Does the Long-term Nature of Life Insurance Products Make Customer Retention Difficult?](https://blog.godonna.ai/blog/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.

- [Arun Agarwal](https://blog.godonna.ai/blog/author/arun-agarwal)
- 6 min read
- Jul 20, 2022

<https://blog.godonna.ai/blog/data-drifted-now-what-identifying-and-responding-to-data-drift>

## [Data Drifted, Now What? Identifying and Responding to Data Drift](https://blog.godonna.ai/blog/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.

- [Paul Thottakkara](https://blog.godonna.ai/blog/author/paul-thottakkara)
- 9 min read
- Mar 23, 2022

<https://blog.godonna.ai/blog/ways-and-means-to-build-trust-in-the-digital-era>

## [Ways and Means to Build Trust in the Digital Era](https://blog.godonna.ai/blog/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.

- [Arun Agarwal](https://blog.godonna.ai/blog/author/arun-agarwal)
- 8 min read
- Mar 16, 2022

<https://blog.godonna.ai/blog/transfer-learning-a-new-age-of-machine-learning>

## [Transfer Learning: A New Age of Machine Learning](https://blog.godonna.ai/blog/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.

- [Paul Thottakkara](https://blog.godonna.ai/blog/author/paul-thottakkara)
- 7 min read
- Dec 16, 2021

<https://blog.godonna.ai/blog/different-ways-to-target-the-right-customers-in-the-insurance-industry>

## [3 Ways to Target the Right Customers in the Insurance Industry](https://blog.godonna.ai/blog/different-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.

- [Yogesh Dhavale](https://blog.godonna.ai/blog/author/yogesh-dhavale)
- 13 min read
- Oct 27, 2021

<https://blog.godonna.ai/blog/enhancing-customer-engagement-in-the-insurance-industry>

## [Enhancing Customer Engagement in the Insurance Industry](https://blog.godonna.ai/blog/enhancing-customer-engagement-in-the-insurance-industry)

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

- [Yogesh Dhavale](https://blog.godonna.ai/blog/author/yogesh-dhavale)
- 15 min read
- Sep 01, 2021

<https://blog.godonna.ai/blog/why-data-science-is-a-game-changer-for-insurance-industry-today-and-tomorrow>

## [Why Data Science is a Game Changer for Insurance Industry Today and Tomorrow](https://blog.godonna.ai/blog/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).

- [Yogesh Dhavale](https://blog.godonna.ai/blog/author/yogesh-dhavale)
- 6 min read
- Jul 29, 2021

<https://blog.godonna.ai/blog/insurance-agents-will-they-disrupt-or-perish>

## [Insurance Agents - Will They Disrupt or Perish?](https://blog.godonna.ai/blog/insurance-agents-will-they-disrupt-or-perish)

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.

- [Arun Agarwal](https://blog.godonna.ai/blog/author/arun-agarwal)
- 6 min read
- Jun 15, 2021

<https://blog.godonna.ai/blog/powering-insurance-agents-with-ai>

## [Powering Insurance Agents with AI](https://blog.godonna.ai/blog/powering-insurance-agents-with-ai)

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?

- [Arun Agarwal](https://blog.godonna.ai/blog/author/arun-agarwal)
- 6 min read
- Apr 21, 2021

- [Aureus Analytics (14)](https://blog.godonna.ai/blog/author/aureus-analytics)
- [Anurag Shah (8)](https://blog.godonna.ai/blog/author/anurag-shah)
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- [Stuti Singh Magdani (4)](https://blog.godonna.ai/blog/author/stuti-singh-magdani)
- [Prerana Suvarna (3)](https://blog.godonna.ai/blog/author/prerana-suvarna)
- [Paul Thottakkara (3)](https://blog.godonna.ai/blog/author/paul-thottakkara)
- [Jackie Vergne (3)](https://blog.godonna.ai/blog/author/jackie-vergne)
- [Neeraja Vaidya (2)](https://blog.godonna.ai/blog/author/neeraja-vaidya)
- [Dr. Nilesh Karnik (2)](https://blog.godonna.ai/blog/author/dr-nilesh-karnik)
- [Pooja Thayyil (1)](https://blog.godonna.ai/blog/author/pooja-thayyil)
- [Tarannum Hasib (1)](https://blog.godonna.ai/blog/author/tarannum-hasib)

<https://blog.godonna.ai/blog/tag/insurance-analytics/page/2>

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