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

Where AI cuts insurer friction, and where humans still belong Major insurance companies like Travelers and Allstate are using AI to reduce tedious tasks like data entry, but experts advise caution against letting AI have too much free rein. What can wearable scores replace in accelerated underwriting? Activity- and inactivity-based data offers a new lens for risk selection. How to prevent AI from amplifying adjusters’ inconsistencies Calls for human oversight of AI handling of claims should consider whether teams of adjusters might be subject to “noise” that distorts their findings, an executive of an AI legal work efficiency company said. How exposed is your portfolio to a single AI model failure? A single AI model failure could trigger claims across policyholders in different industries and geographies, writes Trevor Jones, a partner of the insurance practice for West Monroe. How a small reinsurer added automation without a big dev team By connecting with brokers and cedents through a single hub, the reinsurer is reducing claims and accounting administrative demands. Keynova: Mobile options can cut small-business admin burden Insurance carriers are focused on mobile quoting and policy servicing for small businesses, according to the 2026 Small Commercial Insurance Scorecard. What to weigh before putting AI agents on legacy claims tech Modernization takes time, money and resources. Agentic AI offers another option that works on top of legacy systems, writes Jim Girard, vice president of engineering at Benekiva. AI agents that bind policies could leave insurers liable An Accenture survey finds that consumers are receptive to letting AI agents shop, but one broker is carefully managing access – after banning Meta\'s AI agent at first – and it’s ultimately up to the insurers to be responsible for policies bound as a result of agentic AI shopping. Why cyber claims will expand beyond ransomware Cyber insurance claims will soon involve questions about algorithms, automated decision-making, digital ownership, technology governance and the value of digital assets. How Allstate plans to capitalize on agentic AI shopping The company plans to introduce an AI shopping aide, following its successful rollout of its AI Agent for customer service, the insurer said in its third-quarter earnings call.