A contractor bidding on a public school renovation gets asked, mid-underwriting, what happens if the project management system goes down for a week. Not hypothetical. A ransomware incident at a competitor the year before froze scheduling and subcontractor payments for eleven days. Multiple bonds triggered claims as a direct result.
131 construction firms showed up as recorded ransomware victims in Q1 2026 alone. That’s a 44% jump year-over-year, per GuidePoint Security’s threat intelligence team. Twenty-two distinct threat groups claimed victims in the sector during that period. Sureties noticed.
Why Financial Statements Stopped Being Enough
Surety underwriting ran for decades on a narrow set of inputs. Working capital. Bonding capacity. Project history. Management track record. None of that predicts whether a ransomware attack freezes payroll for two weeks. And payroll freezes are exactly what turns a healthy contractor into a bond claim.
The connection is mechanical, not abstract. A surety bond guarantees project completion and subcontractor payment. Core systems go dark, and the contractor doesn’t just fall behind schedule. They miss payment deadlines that can trigger lien claims and bond claims at the same time. Sureties absorbing those losses now price cyber resilience the way they’ve always priced working capital: as a proxy for whether the guarantee holds up under stress.
The data backs it up. Construction ranked the third most targeted sector for ransomware between April 2023 and March 2024, per a GlobalData report. Credential exposure incidents now make up roughly 75% of digital risk alerts flagged for the sector by threat intelligence firm ReliaQuest. The exposure isn’t new. Who’s reading the reports is.
The AI Layer Doing the Actual Scoring
Surety underwriting used to run on a submitted questionnaire. A contractor filled it out once and rarely revisited it. That model is breaking down. Platforms like BitSight and SecurityScorecard now feed continuous, machine-generated risk ratings straight into bonding decisions. They scan IPs and domains across more than 1,500 ports on a rolling basis. They cross-reference findings against active malware and dark-web indicators daily, not annually.
BitSight’s ratings already sit inside underwriting workflows at Lloyd’s, AIG, and Chubb. SecurityScorecard went further, partnering with a generative-AI-driven cyber insurance provider to offer premium discounts tied to security ratings — the first arrangement of its kind. It’s the same pattern showing up across how generative AI gets used in cybersecurity more broadly: models that used to just flag threats now drive pricing and access decisions in real time. Sureties watching that model succeed in cyber insurance are adapting it for construction bonding, where the core logic barely changes. Can this company keep operating through an incident?
The numbers back the shift. AI-assisted underwriting cuts cycle time by more than 30% on complex policies. It improves risk assessment accuracy by an average of 43%, per research from SoftServe. Straight-through processing rates for automated pipelines climbed from roughly 10–15% into the 70–90% range for carriers running continuous, data-fed models instead of static applications, per a March 2026 WTW survey.
What This Looks Like Inside a Real Underwriting File
The contractors moving fastest through bonding renewals aren’t the ones with zero incidents on record. Regulators and underwriters stopped expecting that a while back. They’re the ones with a documented recovery time objective for core systems. Tested backup procedures for scheduling and payment platforms. A specific account of what changed after a prior incident.
One general contracting firm profiled by Engineering News-Record took a ransomware hit in 2024 that exposed personal data for over 1,000 employees. Their backup infrastructure was already tested and current. They recovered every file without paying the ransom. That’s the exact story an AI-fed risk score now surfaces on its own, instead of an underwriter digging for it manually.
Manufacturing faces a version of this same pressure, and the parallels with AI-driven manufacturing cybersecurity are close: continuous monitoring replacing point-in-time audits, machine-readable posture data replacing self-reported checklists. Construction is just catching up to where manufacturing already sits.
Getting to that level of documented readiness rarely happens inside a company alone. It’s why firms offering support for construction companies increasingly land in conversations that used to belong entirely to the CFO and the bonding agent.
The Gap Widens for Everyone Else
Contractors treating bonding and cybersecurity as separate departments, reviewed on separate timelines, are the ones caught off guard when a resilience question shows up mid-underwriting. That gap gets more expensive as continuous risk scoring replaces the annual questionnaire across more of the surety market. Bonding capacity now tracks two curves at once. The financial one everyone’s always tracked. And a cybersecurity one, scored by an algorithm running in the background, whether the contractor knows it or not.
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