Data is a cornerstone of the property and casualty (P&C) insurance industry, driving informed decision-making and operational efficiency. It enables insurers to assess risk accurately, price policies competitively, and predict future trends. By leveraging data, companies can enhance claims management, improve customer experiences, and develop innovative products tailored to evolving market needs. In an industry built on mitigating uncertainty, data provides the insights necessary to remain agile, reduce losses, and foster trust with policyholders.
What Is the Problem?
Industries establish universal standards for many things, including data, to increase efficiency in utilization, reporting, and sharing. However, within the U.S. P&C insurance industry, there are few widely adopted common data standards. This lack of standardization causes insurers and others to spend billions of dollars each year translating data into formats for regulatory reporting, catastrophe models, and a myriad of other transactions. The time and cost involved increases resistance for insurers to cooperate with regulators attempting to obtain data to inform constructive legislation and regulation.
With rising catastrophes and growing populations in high-risk areas, access to aggregate data is crucial not only to the insurance industry, but to the U.S. economy, which requires affordable and accessible insurance to function.
Why Does the U.S. Property & Casualty Market Have This Unique Problem with Data Standards?
The U.S. P&C insurance industry is regulated at the state level rather than by the Federal Government. There is overwhelming support among both regulators and insurers for state regulation, and it has been effective in many ways. However, with 50+ regulators and close to 4,000 insurance companies, it is almost impossible to gain a consensus on the need for data standards, much less the standards themselves.
The Association for Cooperative Operations Research and Development (ACORD) has attempted unsuccessfully to create and foster industry adoption of its data standards, both as a not-for-profit and now as a for-profit company. The National Association of Insurance Commissioners (NAIC), the primary body creating national consistency across states, has also worked on the issue for years to no avail.
Why Does It Matter?
The cost and difficulty of converting data to different formats increase the resistance of insurers to share data, especially with regulators. More importantly, converting data between architectures—like translating something from one language to another—can result in loss of clarity and accuracy. When insurers move from one Policy Administration System (PAS) to another, which happens frequently but is still hindered by the high costs of conversion, a key barrier is transforming policy data between different architectures.
Who Cares?
Insurers
Insurers acknowledge the problem, but no insurance association or vendor has successfully taken the lead to build a consensus on a solution. Many insurance executives may not fully realize the costs of lacking data standards, and those who do often feel powerless to address it. For carriers, the solution should create financial savings, enhance efficiencies, and increase the ability to leverage data in more creative ways.
Regulators
Insurer resistance to sharing data due to the associated cost and complication, combined with the lack of a data standard, makes it extremely difficult to create standards of performance from aggregated data that can inform constructive and consistent regulation. Consider that most of the Southeastern states required companies to file a data call for Hurricane Helene and Hurricane Milton losses. While the intent of each data call was the same, each one had a different format and slightly different requirements, increasing the costs and complexity of insurer compliance. Regulators ultimately represent consumers who are required to purchase insurance, as well as their state economies that require a healthy insurance market.
Third-Party Vendors to the Insurance Industry
Many vendors in the insurance industry recognize the challenges posed by the wide variety of data formats and terminology. They often invest significant resources assisting customers with data formatting and interpretation. As a result, quite a few vendors see this as a critical issue and are open to collaborating on a unified solution. Standardizing data would also make it easier for vendors to integrate with and transition between different companies, streamlining operations. However, some vendors may still view exclusive ownership of data models and architecture as a strategic business advantage.
What Might Work?
ACORD’s lack of success in creating a data standard proved that 1) there is no industry support for a not-for-profit organization that exists only to establish data standards, and 2) very few companies will pay for the use of a data standard.
The American Association of Insurance Services (AAIS) maintains proprietary data standards for stat reporting and data contribution for product development, like other Rating and Advisory Organizations do. However, as the only national not-for-profit Rating and Advisory Organization, its business model does not require it to protect that data architecture, which is simply a by-product of its business model. AAIS proposes to make its data model architecture “open source” so that others in the insurance industry can adopt it, in part or fully, at no cost.
How Will AAIS Make it Work?
AAIS was established as a not-for-profit organization with the goal of fostering collaboration among its insurance company Members. This collaboration enables insurers to develop better and more cost-effective solutions that benefit the entire industry—solutions that individual companies could not achieve on their own. In 2021, AAIS created a not-for-profit subsidiary under the Linux Foundation for insurance industry collaboration on data standards and reporting. The Linux Foundation is dedicated to creating and maintaining not-for-profit open-source industry standards with a proven governance framework that allows transparency and participation while ensuring that collaborative work product does not become compromised or proprietary. As a Linux Foundation project, openIDL (Open Insurance Data Link) is an existing platform that is governed by its time-tested governance model.
What Is AAIS’s Proposal?
AAIS will update its stat data model architectures, harmonizing them with existing open-source standards, such as OASISLMF and OMG, as well as others willing to contribute their data structures.
AAIS will donate its data model architecture to openIDL and the Linux Foundation as an open-source model architecture, available at no cost to anyone that would like to use it.
The maintenance and updating of the data model architecture would be owned and developed within the Linux Foundation through openIDL, with participation and support of interested parties in the insurance industry.
How Would the Industry Support and Participate In This Process?
Membership in openIDL follows the proven governance model used by countless industries. Any industry participant may become a member of openIDL and potentially serve on its board. Not-for-profit firms and regulators can join for free. Full memberships are calculated using a formula
based on the number of employees, capping out at about $250,000 per year with a guaranteed board seat. A lower cost membership is available, priced from $10,000 to $50,000 per year, based on enterprise size, creating a class from which additional board members may be selected. Board members collectively govern the organization, and members have the right to participate in the development and maintenance of data standards.
How Would This Get Started?
The openIDL organization was originally developed as a data-sharing platform, created by AAIS and donated to the Linux Foundation, which required a standard data model architecture. While openIDL will continue to support its platform, its focus will shift to data standards. openIDL has funds to continue operations for approximately 12 months, but as AAIS shifts from the openIDL platform to focus on data, it will need to replace a few primary members to continue to fund and build consensus for open-source data standards. There is active interest from insurance regulators, insurance not-for-profits, industry third-party vendors, and some large insurers; efforts are underway to create critical mass.
If You Build It, Will They Come?
Good question! Adoption may be slow in the beginning, but over time, open standards often follow a predictable adoption course. In the initial stage, the adoption of open standards is expected to act as a baseline framework, serving as an intermediary for mapping data before converting it to another standard, like a universal translator. Incremental adoption is anticipated, such as in the case of the aforementioned catastrophe data call by multiple states, where the data standard provides a foundation for them to issue a standardized data call. Over time, creators of new policy administration systems will start integrating elements of the data model architecture, gradually driving broader adoption.
Why Should I Care About This?
The insurance industry plays a vital role in our economy and nation. While improving data flow may pose short-term challenges (each organization would define those challenges differently), the long-term benefits far outweigh the costs. As data becomes increasingly critical for accurate insurance processes, the industry must adopt data standards to manage larger volumes efficiently. Supporting this mission strengthens the industry’s future and upholds our collective responsibility to ensure its continued success.
Contact Information
For more information, please contact the following individuals.
openIDL
Josh Hershman, Executive Director – jhershman@openIDL.org
Lanaya Nelson, Ecosystem Manager – lnelson@openIDL.org
AAIS
Werner Kruck, President & CEO – wernerk@AAISonline.com
