Scaling Security Design Reviews in Insurance Without Slowing Down Development

Executive summary

What this whitepaper covers

Insurance organizations operate on some of the most sensitive data such as PII, PHI, financial records, claims history, and they're modernizing fast. New digital channels, decomposed monoliths, broker portals, cloud migrations.

Security teams know the risks. The problem is that the pace of change has long outrun their capacity to review it. Traditional SDR processes struggle to keep up with modern development velocity. Reviews are manual, inconsistent, and heavily dependent on documentation quality and reviewer availability.

This whitepaper speaks to the exhausting trade-off AppSec leaders in insurance know well: either slow down delivery to complete reviews, or let changes ship without them and hope for the best. Neither is acceptable. not operationally, and certainly not under NYDFS, NAIC, or PCI DSS.

It also shows how automated security design reviews change that equation, cutting review turnaround from without replacing the human judgment that regulated environments still require. The result is a shift from selective, manual reviews to continuous, system-wide design security. For insurance companies, this not only reduces risk but also strengthens regulatory compliance and audit readiness.

Key findings

What you'll take away

✦Insurance systems demand strong design-stage security controls
✦Manual SDRs create bottlenecks and inconsistent outcomes
✦Limited AppSec capacity leads to reduced review coverage
✦Automation enables consistent, scalable SDR execution
✦Faster turnaround without slowing development cycles

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FAQ

Frequently asked questions

Which regulations most shape SDR in insurance?

The NAIC Insurance Data Security Model Law (now adopted by 22 plus US states), NYDFS Part 500, GLBA, and PCI-DSS where carriers process cards. GDPR and its local equivalents apply in every multinational program.

How realistic is full coverage with 1 to 5 AppSec engineers?

Not with a manual process. With AI-assisted SDR, carriers hit full coverage because the reviewer shifts from executing every review to overseeing output and handling the highest-risk features directly.

How quickly can we stand up an AI-assisted SDR program?

Expect 90 days to first measurable coverage and 180 days to a production program. The case study in this paper moved SDR turnaround from 4 days to 2 hours within the first quarter.

How does this fit with our existing Jira and Confluence workflows?

Seezo integrates directly with both. Engineering continues to write technical specs in the same place, and the security review runs off the same document without creating a separate queue.

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