A large enterprise bank was fielding hundreds of due diligence questionnaires each year across a complex multi-entity structure, and the process was breaking down. Manual spreadsheets, an internal AI tool, and no external trust center meant every inbound request consumed security team capacity, produced inconsistent answers, and stalled deals that depended on fast security reviews. They needed more than a faster way to answer questions. They needed a controlled, auditable workflow that could handle entity-specific accuracy requirements, gate access to sensitive compliance artifacts, and generate the metrics leadership needed to see compliance as a revenue driver, not a cost center.
[ The Problem ]
Hundreds of DDQs a year, no system built to handle them
The team was managing an estimated 500 compliance questionnaires annually using spreadsheets and a homegrown AI tool, with no external trust center and no automated distribution path for documents like SOC 2 reports. Every request required manual answer gathering, accuracy validation against the correct legal entity, and SME escalation before anything could go out.
Answer consistency and controlled disclosure were non-negotiable in a regulated banking environment where entity-specific registration details, addresses, and licenses had to be accurate and not overshared across jurisdictions. Monthly metrics reporting to leadership was also done by hand. The business consequence was direct: security reviews were stalling deals, and the compliance function had no way to demonstrate its impact on revenue.
[ What they needed ]
The team set out to find a solution that could handle the full workflow, not just one piece of it.
- Standardize DDQ responses across a multi-entity, multi-jurisdiction structure
- Gate access to sensitive compliance artifacts with NDA and click-wrap controls
- Automate questionnaire ingestion from external portals used by banking partners
- Enable role-based collaboration across infosec and compliance teams
- Capture deflection, time-to-complete, and deal-influence metrics for leadership
- Integrate with existing tools including Slack, Okta, and CRM systems
- Replace manual monthly reporting with automated analytics tied to business outcomes
[ Why Drata won ]
Drata won by delivering end-to-end workflow breadth that no single-point alternative could match, at a price the procurement team could defend against cheaper options.
End-to-end workflow coverage: the combination of trust center gating, AI-assisted questionnaire completion, portal ingestion, Slack collaboration, and CRM-linked analytics addressed the full operational requirement. Alternatives were evaluated as narrower tools that solved one part of the problem, not the whole chain.
Implementation and partnership posture: the buyer explicitly contrasted a poor onboarding experience with an incumbent vendor against the expectation of white-glove implementation and phased project management. The willingness to engage deeply during the POC and procurement process was a direct factor in the decision.
Defensible ROI against a price premium: the solution carried a higher price point than the top two alternatives. Providing structured commercial options, bullet differentiators, and a lightweight ROI narrative gave the procurement owner the artifacts needed to justify the delta internally and keep the buying motion moving.
[ How Drata solved it ]
Drata's Trust Center gave the team a gated, self-serve distribution layer for compliance artifacts, with NDA and click-wrap controls, product-segmented pages, and permission profiles that matched the bank's need for controlled disclosure across entities. AI Questionnaire Automation (AIQA) addressed the core DDQ volume problem by providing AI-assisted answers with citations, reducing the manual effort required to respond accurately at scale.
Portal ingestion via plugin connected the workflow to the external DDQ systems banking partners already used, eliminating the need to rekey or reformat incoming requests. Slack integration brought notifications and response collaboration into the tools the team already worked in, while Salesforce linkage tied trust center analytics to CRM context so leadership could see deal influence, not just activity volume. Where workflow gaps remained, such as in-platform signing, the team adopted interim steps while roadmap alignment was established, because the trust center deflection and analytics value was strong enough to move forward.
[ Before and after Drata ]
Before Drata, an estimated 500 compliance questionnaires per year were handled through spreadsheets and a homegrown AI tool, with no external trust center, no automated distribution, and manual monthly reporting to leadership.
After, a gated trust center handles self-serve artifact distribution and AI-assisted questionnaire responses reduce direct team involvement, with analytics automatically surfacing deal influence and deflection metrics for leadership.
[ Business outcome ]
The bank now has a structured, auditable path for distributing compliance artifacts and responding to due diligence requests at scale, replacing a process that was consuming team capacity and producing inconsistent results. Security reviews that previously stalled deals can now be resolved through a self-serve trust center, with gated access and entity-appropriate content, reducing the volume of requests that require direct team involvement.
Compliance metrics are now tied to business outcomes rather than reported manually each month, giving leadership a defensible view of how the security function contributes to revenue acceleration. The foundation is in place to expand automation coverage as multi-entity questionnaire handling matures on the roadmap.