At a purely theoretical level, you'd be hard pressed to find people in the insurance industry opposed to data standards. The values are clear: lower transaction cost, better data quality and greater ease of doing business. Yet, standards remain far from universal acceptance, and some still make compelling arguments against their deployment. The most common, not surprisingly, come down to time and money, but there are other reasons as well. So, what does the future hold for industry data standards? The effort to standardize business-to-business transactions is an ancient one. The historical record reveals the use of standards as far back as ancient Egypt and Sumeria. Indeed, the business logic behind standardization - uniformity, interoperability, stability - is still the same whether a transaction is done via XML, EDI, carbon copy or cuneiform. "It's just an evolution of how we capture data; the actual elements themselves are critically important but the medium is constantly evolving," says Spero Zacharias, international field operations manager, at Warren N.J.-based Chubb Group of Insurance Cos. "We're just keeping pace with the medium in which forms are captured." Zacharias knows all too well. In addition to his work at Chubb, he chairs the P&C, surety and steering committee for Pearl River, N.Y.-based ACORD, which was conceived in 1970 to help set standards for the insurance industry. He says that the governance process at ACORD is conducive to collaboration. "From an industry perspective, I think the ACORD process is a very open, equitable and transparent process to achieve standards." he says. "The standards setting process requires consensus building, so it's not really an obstacle, it's an activity."  Costs and Quality

According to Zacharias, the value proposition for standards in the insurance industry is threefold: lower transaction cost, better data quality and greater ease of doing business. While the enthusiasm for the first factor is largely self evident, the latter two bear consideration. The strict regulatory environment in which insurance companies operate puts a premium on data quality. The events of the past year seem to indicate this issue will not go away anytime soon, and information mapped in a consistent standard is a good start to ensure compliance. "The more you standardize, the easier it is to validate and verify the accuracy of your data," Zacharias says. "If you're not going to standardize applications, you at least have to standardize data elements to check for quality." The third factor, ease of doing business, is especially import considering the ever-expanding array of actors in the insurance value chain. A primary insurer may deal with agents, brokers, reinsurers, regulators and vendors in the course of business. It is the role of standards to improve the flow of information between these disparate entities. "The expectation of service has changed over time, and data standards do facilitate responsiveness throughout the value chain," Zacharias says, stressing that standards offer value for all players-a quicker quote helps producer and carrier alike. Insurance companies use standards to communicate with partners, suppliers, intermediaries and entities such as the National Securities Clearing Corp. While standards are especially important to insurers utilizing independent producers, who may be leery of proprietary applications, one additional sign that standards are gaining in acceptance is that even carriers that rely on captives are using ACORD. "Historically, we've always been an ACORD download participant," says Kevin Hunter, chief architect at Schaumburg, Ill.-based Zurich North America. "Now, we're embracing the standards more fully to take upload-type transactions from agents and brokers as well." Another set of standards gaining ground is Security Assertion Markup Language (SAML). Insurers can use SAML as a way to enable single sign on, which is popular with producers. Carriers are also increasingly adopting standards, such as XML, that are not necessarily insurance specific, but preferable to the flat files and mainframe copy books that have been used historically.

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