This post is part of a series sponsored by IAT Insurance Group.
Data is both a gift and a curse. Across all industries, companies have more information at their fingertips than ever before. Yet not all organizations have the infrastructure or tech-savvy resources needed to efficiently exchange and unlock the benefits of all this data.
In the world of insurance, access to data — and speed of sharing it — can make it easier to apply for insurance, adapt to regulations, and prevent and detect fraud among other uses. Businesses that want to take full advantage of all the data a company collects need flexible systems, common standards, and adaptable processes. Quick and efficient exchange of information between MGA, insurance carrier, regulator, and other stakeholders allow for better customer service, quicker payment of claims and expenses, and a more current view of the performance of a book of business.
This is especially true for the insurance program segment of the P&C industry. Not only does technology improve the buying experience for the MGAs’ distribution network, but it also enables them to optimize risk selection, pricing, and underwriting to ensure the profitability of their portfolio. Technology can also increase efficiencies and enable differentiation, which can create a competitive advantage in the market.
4 key considerations to optimize data for insurance uses
Optimizing technology can be daunting, but advancements aren’t slowing down anytime soon. As of 2021, almost a third of U.S. companies are actively using data to transform their business outcomes.[1] Technology is reshaping the insurance industry, from claims, to distribution to underwriting and pricing. What can and should businesses do to stay ahead of the curve managing and integrating their data?
1. Understand your data model.
Every business is structured differently and has a unique data “language” that describes the information important to their operations. In the insurance industry this “language” often centers around describing policies, premiums, coverages, claims, invoicing, and customer data. For a business partner, such as an MGA, to share its data with an insurance carrier, their data needs to “speak the same language” as the insurance carrier. Some companies already have a data model that may need tweaking, while other companies must start from scratch. Either way, knowledge of the current data model – and where it may have gaps for desired business purposes – is a good place to start. The goal is to first understand how the data is organized, as well as its intended business uses, so a company can plan for sharing it.
There are a couple of P&C insurance industry data definitions business partners can use to exchange data more easily: ISO and ACORD.
- ISO has several standards related to insurance data, and focuses primarily on standardizing the definition of forms, coverages, loss costs, and statistical reporting.
- ACORD defines standards around organizing and exchanging policy and claim details for specific insurance lines of business between companies. These standards streamline data exchange, so organizations represent a policy or claim the same way when integrating systems and processes.
Use of standards like these can result in significantly less effort than having to spend time coming to an agreement on how to do so from scratch. Regardless of the standard used, the key is to agree on one shared definition of insurance data to use together.
2. Engage in best practices for data security and privacy.
Insurance data often includes personal information that, in the wrong hands, could be damaging. Protecting sensitive information is essential, which is why there are rules and regulations that dictate the handling and sharing of data. It’s critical that insurance companies and their business partners work together to develop privacy and security standards and practices. Encryption is one such practice that helps protect the stealing and misuse of data. Essentially, it converts information into an encoded format that can’t be read or processed unless it’s decrypted by a trusted and authorized partner.
3. Expect regulatory change and prepare for it.
The nature of the insurance industry is one of constant change, especially when it comes to regulations at the state and federal level. If new legislation requires a change to be quickly implemented, having access to a broad range of relevant data can help companies swiftly pivot to maintain compliance. If a business doesn’t have a handle on its data and doesn’t have a way to efficiently communicate the impact of changing rules, it has put itself in a potentially sticky compliance situation.
4. Look ahead to emerging tech.
As the industry evolves and the amount of data collected continues to explode, insurers will use artificial intelligence (AI) and machine learning (ML) even more to make informed decisions. Some leading-edge companies are using ML algorithms to make faster underwriting decisions through ML’s ability to make sense of large data sets and evaluate risk in minutes or even seconds.[2] Also, AI and ML could automate the more commoditized underwriting and claims processing tasks, allowing experts to focus on more intricate situations requiring a human touch. Many of these technologies have already been put in place in the insurance industry and beyond.
Blockchain is another example of an emerging technology creating headlines because of its relationship to cryptocurrency. It’s an automatic and secure way to exchange data that, while in its infancy, may eventually blossom in the insurance market. Industry adoption is the biggest challenge with any new technology, but savvy carriers know it’s prudent to stay on top of trends that could shape the future.
IAT Insurance Group constantly evaluates current and future technology trends. With respect to our Programs business, we partner with MGAs to help them become more nimble, adaptable, and successful. Contact IAT to get started on your data-sharing journey.
By: Mark Plamann, Assistant Vice President, Application Development at IAT Insurance Group
[1] Statista “Big data – Statistics & Facts,” June 13, 2021.
[2] McKinsey & Company “Insurance 2030—The impact of AI on the future of insurance,” March 12, 2021.
Topics
Data Driven
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