By definition, data standards are a set of rules and guidelines that provide a common framework for communication. Much like the human body, this common framework, or skeleton, needs to be supported by something that has the ability to pump information out to its various parts and provide life support to the body as it grows.
At the heart of ACORDs Life Standards Program is the ACORD Life Data Model, and it has, by its nature, allowed for data exchange in the life insurance industry to become stronger as it grows into different phases of its life.
If you think of the Standards Program as a living body and the data model as its heart, you can see how the Life Standards Program has been able to grow from a desktop integration standard into the world of XML (eXtensible Markup Language) that enables data sharing across multiple platforms. ACORD XML is the electronic language of the insurance Internet, facilitating real-time, cross-platform, peer-to-peer communication created as a result of the industrys need for a more efficient means of doing business. The data model has made this evolution much simpler than it would have been if starting from scratch.
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The data model was originally created using a data object hierarchy. In simpler terms, the data objects are products that consist of all aspects of traditional life insurance (e.g. term, whole life, variable products) as well as annuities, disability, health, long term care, investments (e.g. mutual funds, stocks and bonds) and so on. Today it is following the same hierarchy and has continued to function efficiently for a wide array of end-users.
The ACORD Life Standards Program began in the early 1990s as the OLifE Program, which used a data model to support its functions. The OLifE standards and early life data model defined the middleware pieces needed to allow applications used in a life agents desktop system to share data. OLifE was developed to provide the framework for “intra” system information sharing between applications running on a single computer or local network.
ACORD XML for Life Insurance built on this early work to expand its focus on cross-system information sharing, meaning that data entered into one application is accessible by all other applications from within and between organizations.
The purpose of the Life Data Model, in both cases, is to allow for the sharing and communication of information. Beyond XML, future languages will be able to reuse the Life Data Model. Its reusability is seen in the evolution from intra-system to widespread sharing of data. This capability is often referred to as Life Standards technology and platform neutrality.
The Life Data Model has been successful in growing the Standards Program for four key reasons: it is reusable, consistent, expandable and interoperable.
As an industry-built and industry-maintained vocabulary of insurance specific domain information, the Life Data Model provides a structured, organized and defined means of sharing complex insurance information among all parties in the industry. This, too, will stay a factor as the industry grows and its counterparts adapt to changes in the business environment.
It is important to keep a keen eye on the future when modeling the data for today. Efforts to do so will allow standards users/developers to easily “plug in” new data requirements to the data hierarchy, expanding on previous achievements rather than breaking and starting over. Standards developers will be able to support critical functions like backward compatibility and interoperability as they move forward to meet the newest needs of the industry.
Keeping the data model intact is critical to achieving interoperability within the life insurance industry. Back office systems that process transactions and send data feeds forth and back to users can use the ACORD Life Data Model. This provides interoperability between the components that make up the enterprise, ensuring that all the pieces fit together.
And you can use the ACORD Life Data Model as the basic business vocabulary for sharing life insurance information between all trading partners. This consistency of meaning as well as structure of life insurance data provides enormous cost benefits, speed to market, and improvement in time and information efficiencieswhich only increases as the number of systems and trading partners increases.