Creating a Modern Insurance Organization

Insurance companies have a big opportunity to take advantage of AI, but they need to get their data strategy right first.

Data is at the heart of insurance organizations, and there has never been more of it available. Most insurers, however, are not confident about the data they produce and their ability to use it.

Workday asked insurance executives if their data is ready to use with AI and machine learning (ML), and 77% said their organization’s data is neither timely nor relevant enough.

“We know why insurance firms need to transform—complexity, regulatory demands, need for growth, AI,” says Caroline Heckathorn, senior solution manager, Workday. “But why is that important? A lack of confidence in their data. And data holds the key to insights and innovation.”

A new report from Celent, “Creating a Modern Insurance Enterprise,” discusses how insurance organizations can focus on key tenets that can transform insurance companies into modern enterprises and help them stay nimble and adaptable: data, cloud, AI , LCNC (low-code/no-code) platforms, core systems, corporate systems, and innovation.

Let’s explore some of the critical insights from this report, particularly relating to data, cloud, and AI.

Getting Data in Order

Why is a focus on data so important?

“If you don’t have your data house in order, it’s going to be challenging for you to realize the value of data and to use AI in any useful capacity,” says Keith Raymond, principal analyst at Celent.

Data exists in many forms across insurance companies. Effectively organizing, governing, and managing it in a secure manner has always been a challenge.

How your data is managed can make a big difference. “As data moves through a siloed system, you start to lose detail,” says Heckathorn. “What that means is that you’re not able to look at a number in a general journal or financial statement and understand where it came from. You have the number but not the insight.”

Insurers sometimes must log in to multiple systems to look up the details, which can be time-consuming and inefficient when they need information quickly to make a decision, notes Heckathorn.

In this scenario, the downstream stakeholders also may not get the insights they need, and they’ll often go back to the source system and try to reconstruct the numbers. But that can lead to errors. “That adds risk and can’t answer the questions you need to answer,” says Heckathorn.

New methods and innovative architectures enable better ways of managing data in real or near-real time. According to Celent’s report, “Emerging technologies, including cloud and AI, are providing much-needed tools and solutions to aid in the data management process.”

A Cloud-Based Data Core

A cloud-based data core can provide a connected view of data through applications with interoperability, creating a single view of the truth and enabling data to coexist with third-party applications, notes Heckathorn.

Interoperability is achieved when enterprise applications can work together with a unified source of data, consistent security, and a composable architecture. It supports analytics, feeds process execution, and works with AI and ML capabilities to augment people.

According to Heckathorn, having a cloud-based data core “means insurance organizations produce fewer errors, and lose less time on manual rote work.” Employees are happier because they don’t have to pinball around within multiple systems to make sure the numbers are accurate. Everyone’s ability to plan is increased, and they have the details they need to make decisions.

Using AI and ML

Data and the cloud are two key areas that will need focus to get right. But once insurers do, it becomes easier to leverage AI and ML.

According to the report: “To leverage AI solutions, insurers need to begin by organizing their data in a repository. They should operate in the cloud, which provides them with flexibility and scalability to train, test, and ensure the quality and security of AI/ML models, including Gen AI and LLMs. Essentially, data, cloud, and AI constitute the top three pillars of a modern insurance enterprise.”

Insurers are looking to AI, automation, and advanced analytics to reduce total workload, streamline operations, and deliver greater value. In practice, that looks like:

• Enhanced underwriting to improve pricing accuracy and risk selection: AI allows for more data-driven underwriting, using ML to analyze massive datasets.

• Supplemented claims management to stem losses: AI- and ML-supported tools have slashed the time it takes to process and assess claims. These tools have also made it easier to spot fraud and improve the accuracy of claims inspections and pricing.

• Streamlined customer support: Chatbots and virtual assistants are helping insurers answer customers’ questions more quickly and easily.

Starting on a Data Transformation Journey

According to Heckathorn, insurance organizations should ensure they’re working with a cloud-based system that has deep experience with data transformation in insurance.

“The system should have insurance use cases as part of its DNA and understand transformation,” says Heckathorn. “Elect the right partner to help you who’s been down that road many times and has data toolkits, templates, and best practices and can speed up time to value.”

Community is critical as well. Insurance can work together, learn from one another, and benefit from one another. Transformation also makes everything better for your customers and employees.

“There used to be a real concern that modernizing tech was not better for customers,” says Heckathorn. “People thought the real white-glove experience was on the telephone. Customers want insurers to meet them where they are from a tech perspective, which is better for business as well.”

To learn more, download the report today and watch the related webinar.

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