Blog Post: Final Blog: ROI of Insurance Data Series & Insurance Data ROI Calculator

By Michael Schwabrow

Our industry is at a crossroads. Insurers who are proactive, strategic, and realistic about adopting emerging technologies stand a lot to gain if they take their data, employee and customer relationships, and processes seriously.  When looking at these dimensions, in this article I will cover specifically:

–             People : How to build and retain a top data science team.

–             Process:  What is needed to ensure compliant insurance analytics programs that protect insurers and the insured?

–             Technology:  Which technologies on the market today should be the staples of every insurance data program?

This post is the final article of our ROI of insurance data series, and we will also unveil the ROI of Insurance Data Calculator after sharing best practices in these core areas.

Digging into Core Best Practices That Can Transform Insurance Data Programs

Recruiting the Best Data Scientists in the Insurance Industry

The people behind insurance analytics programs are one of the most crucial assets besides the actual data. Data science professionals play an influential role in how information is used and what data analytics technologies are purchased. So how can insurers ensure that they end up with the best talent?

First and foremost, the data scientist is not a replacement for the industry expert actuary. Together they can form a powerful team that can bring insurance insights to life to transform an insurance company. The expert analysis that the data scientist can provide with proper context from actuaries is invaluable to the intelligent insurer.

In terms of finding the right data scientist for an insurance business here are some recommendations:

1. Examine Technical and Communication Skills on Equal Footing:  It is obvious that any business hiring a data scientist wants the absolute best technical talent. However, you also want to make sure these hires are solid communicators and listeners to forge quality internal partnerships. This is especially true if a new hire has limited insurance expertise. The quality relationships they can build and maintain will make all the difference as to whether the insights were developed in a technical vacuum or with well-rounded insurance expertise backed by decades of insurance industry experience.
2. Grounded and Passionate Approach to Emerging Technology:  As we’ve seen with GenAI, it is not a race to incorrectly deploy a new technology. As analytics, ML, and other related technologies evolve, you want data scientists who know how to sift through not only big data but through emerging solutions that are getting a lot of buzz within insurance or other industries.
3. Drive for Continuous Improvement:  This is really a skill that every new hire in every role should have. However, it is critical for data scientists to hold this character trait near and dear. You want these professionals constantly bugging you to attend new in-person or online events or trainings, along with taking additional certifications.
4. Ability to Thrive on Challenging Projects:  Insurers need to hire data scientists who have succeeded at breaking down complex data sets from diverse and sometimes perceivable unrelated sources. These insights can give carriers the golden nugget that can be a difference-maker for the business.

Data Privacy & Security Compliance Best Practices

After hiring the right data scientists and actuaries along with other supporting technical/business roles that make up your insurance data program, you must deal with privacy and compliance. Really, this area should be part of your interview questions and annual employee performance review criteria.

Your insurance business should make staying up to date with the most relevant data privacy and regulatory compliance standards considerations part of employee onboarding and continuous development training. There can be ways to set up training portals that are regularly updated with the latest information. A partnership with carrier legal departments is necessary for insurance data teams to ensure they never miss a beat and put the insurer and insured at risk.

Insurers should constantly stay abreast of the latest updates from the NAIC and follow top law firms in these areas like Locke Lord. For example, the NAIC’s Data Security Model Law is an extensive document you should ask your insurance data teams to be familiar with.  Locke Lord’s InsureReinsure blog has a wealth of compliance resources from articles to events to explanations of industrywide or statewide changes that carriers should be aware of.

Five 2025 Insurance Technology Must-Haves

Being in the insurance AI, BI, and analytics business, I am a little biased and would say these are key technologies that can significantly elevate insurer operations, growth, and customer relationships.

Surely at the top of everyone’s minds in the insurance industry is how to better serve and protect the insured in the event of natural disasters. The three-legged foundation of analytics, BI, and AI is important in this area. Additionally, geospatial platforms can make a difference in predicting the impact of disasters including potential storm paths and impacts of hurricanes.  Except for some of the least disaster-prone states in the union, geospatial platforms will be worth considering.

Cybersecurity/cyber insurance is the other main category that many insurers in every state should look at. Without a sound cyber strategy, no matter how strong the insurance data program is, it can quickly come crumbling down if hit by a malicious attack.

As I covered previously in this series, insurers must have a holistic team effort across functions when purchasing technology and managing their insurance data program to have success.

The Glue That Holds Everything Together

An insurer can get every step on paper right when it comes to people, processes, and technology. However, if these three areas are not seamlessly integrated within an insurer this disjunction will be worse than the disjointed insurance data architectures many insurers have today.

The glue that holds these elements together contains quality executive and departmental leadership that creates realistic, challenging goals while cultivating a rewarding company culture that keeps employees engaged and happy.

A solid change management program is vital as businesses modernize technology and business processes to help navigate any concerns as insurers do something that traditionally takes them a long time to do – evolve.

Introducing the ROI of Insurance Data Calculator

Cloverleaf is passionate about helping insurers thrive and we support some of the key parts that I’ve outlined in this article. To demonstrate our commitment to the holistic success of insurers we have developed the ROI of Insurance Data Calculator. The asset touches on most of the core components in the last two blog posts around the Economics of Insurance Data and the program areas that make the most difference.

The purpose of the Calculator is to give insurers a tool that they can leverage throughout the year with an ROI score to measure how they are performing in key areas from a people, process, technology, and business growth/profit perspective.

It is a great tool for senior business leaders to use on a monthly or quarterly basis to keep a proactive eye on their insurance data program. If there are areas of concern related to the Infrastructure Start-up and Maintenance Costs of your insurance data program, this is an area where Cloverleaf’s technology and industry expertise can make a difference for your insurance business.

Here is an example of how a sample run-through of the Calculator:

The following example shows strong ROI

-Annual Revenue: $100,000,000

-Number of Employees: 500

-Annual IT Budget: $10,000,000

Infrastructure Costs:

-Setup Costs: $1,000,000

-Annual Maintenance Costs: $500,000

-Annual Licensing Costs: $300,000

-Integration Costs: $200,000

-Consultancy Fees: $150,000

Employee Resources Costs:

– Salaries and Benefits: $2,500,000

– Training Costs: $200,000

Data Management and Security Costs:

– Data Governance Expenses: $250,000

– Data Security Expenses: $500,000

– Breach Costs: $0 (no breaches)

Revenue and Profitability Increases:

– Revenue Increase: $5,000,000

– Profitability Increase: $2,500,000

Operational Efficiency and Cost Savings:

– Customer Retention Increase: $1,000,000

– Reduction in Claims Fraud: $800,000

– Operational Efficiency Savings: $1,200,000

Regulatory and Compliance Savings:

– Savings from Reduced Fines: $200,000

– Claims and Underwriting Savings: $500,000

ROI Score: 2  (For every dollar spent, the company gains two dollars in benefits, signifying a highly efficient and beneficial program.)

To access the Calculator visit – https://cloverleafanalytics.com/calculator/

Three Things a Successful Tech-Forward Insurer is Continuously Doing

To round out the ROI of Insurance Data series I wanted to briefly share core behaviors that an insurer that is ready to excel in the future is continuously doing.

1. Deriving meaningful insurance insights:  Insurers who are plugged into their business, customers, and the industry with quality insurance intelligence from their data will be nimble, innovative, and productive. Expectations from the insured for smart services and products will continue to increase in the coming years. Insurers will need real insurance intelligence to attract and retain customers. Successful carriers will make insurance intelligence the lifeblood of their business to continuously scale their revenue and profit while finding new ways to boost customer satisfaction.
2. Improving operational excellence:  With insurance insights, carriers can constantly uncover ways to improve the efficiency of their underwriting and claims decisions along with overall client service.
3. Adapting for the future:  Ten years ago, no one in the industry could envision AI delivering any value for the insured or insurers. Most felt the industry would continue along the path of the status quo with minimal technological advancement. This is not the case, and we will not return to the industry of the past that moves at a snail’s pace in adopting modern technologies, developing advanced and customized insurance services, and creating new customer experiences.

The future is bright for our industry and those that take their data, customer relationships, people, process, and technology seriously will thrive.