The Vision of Surety Automation

The objective of surety automation is to employ technology to streamline processes, reduce redundancies and increase productivity in the surety bond process, which spans the application for the bond, the execution and submission of the bond and the processing of premium. The objectives of surety automation are realized fully when methodologies involving transmission, security, verification and data integration encourage the broadest participation by surety companies, surety bond producers, contractors, project owners, risk managers and other parties in the bond process. Any methodology should seek to maximize interoperability among disparate systems. Broad participation in surety automation is the vision. Interoperability through open standards and systems is the way to that vision.

Surety Data Standards

See a useful, brief infographic on the value of surety data standards. To learn about the Surety Data Standards Toolkit and how to realize value from its implementation, visit the Toolkit page.  You can find out about the Standards Pledge here. View the recorded webinar introducing the Toolkit. For more updates on surety data standards, please visit the XBRL and ACORD Surety Forms pages.

Surety Innovation Center

The First Surety Innovation Center was held at the 2017 NASBP Annual Meeting in Boca Raton, Florida. Learn more by clicking here.

Latest Automation News

AI ROI for insurers: Budget for governance, not just tokens Insurance companies and their policyholders share the struggle of scaling their AI use without letting costs (or fraud) get out of control. Pricing AI risk requires measuring governance, not adoption AI fluency will become an underwriting consideration, but it must be demonstrated through operating evidence. How should underwriters assess law firm ransomware risk? Law firms that best survive a cyber incident will accept the risk, prepare for recovery and protect their reputation as carefully as their data. AI can misread paperwork. Insurers have three ways to catch it Submission intake is one of the first places AI is landing at carriers and MGAs. It reads clean documents well and bad ones quietly wrong, writes Isha Sharma, a member of Mezdoc\'s founding team. SMEs are easy targets for AI attacks. How can carriers help? Travelers, Beazley and Coalition are among the companies addressing a surge in cyber risk targeting small and medium-sized enterprises. Consumer groups call on insurers to slow AI, keep humans deciding Individual policyholders and consumer advocates object to the black box nature of AI claims denials and coverage decisions. Consumer Federation of America and Greenlining Institute call for more oversight and slowing down adoption of AI. GlobalData: Insurers should spell out AI in SME cyber policies The adoption gap is more a result of confusion than it is of price or disinterest, according to \nGlobalData. Carriers must use AI and shared data to prevent losses AI, data and know-how can make insurers more resilient to climate losses, writes Mike Gulla, co-founder and CEO of Adaptive Insurance. Why insurers are questioning AI budgets As AI becomes more operational, there are questions coming up like which models make sense, what it should cost and when should the AI stop and hand the work to someone else? Insurance commissioner candidates cite AI risks, benefits In the November 3 general election, voters in California, Georgia, Kansas and Oklahoma will choose among candidates who serve four-year terms. Georgia is the only state with an incumbent commissioner running for re-election.