Fortune 500 Fintech: PCI DSS Automation with AuditBoard | ComplianceCow

ComplianceCow Case Study: Large Fintech Company's GRC Automation and Assurance Journey

16 PCI controls automated; full-population assurance; human hours reduced by ~80%.

This case study shows how a Fortune 500 fintech implemented PCI DSS automation using ComplianceCow’s middleware with AuditBoard, Jira, Slack, Snowflake, and GitHub. The program automated 16 PCI controls, shifted from manual sampling to full-population controls testing, and reduced human hours by roughly 80%—while preserving existing GRC investments.

Industry: Fintech & Payments  |  Company size: Fortune 500, publicly traded

AuditBoard Jira Slack Snowflake GitHub SaaS deployment

Case Study Fast Facts – Compliance Automation and GRC Integration Overview

Company Type

Publicly traded, Fortune-500 fintech.

Compliance Challenges

  • Quarterly PCI scope with 18 controls; manual, sampling-based reviews.
  • 30+ person GRC org without dedicated engineering capacity.
  • Manual evidence collection and ticket creation across tools.
  • Rising audit volume (15–20/year) and technical debt from ad-hoc scripts.

Key Use Cases

  • Automating quarterly PCI reviews (16 controls completed in the latest cycle).
  • Full-population checks replacing five-item samples (e.g., change-management).
  • Slack-driven owner prompts and Jira ticket creation to drive completion.
  • Evidence upload and review continuity in AuditBoard.

Technology Stack

See full list below.

1. Problem Statement

  • Resource Constraints: A 30+ person GRC team with no dedicated engineering support.
  • Inadequate Assurance: Manual sampling that provided insufficient coverage and lacked data QA.
  • Manual Process Overload: Evidence collection and ticket creation across multiple tools.
  • Scalability Crisis: 15–20 annual audits; headcount could not keep pace.
  • Technical Debt: Ad-hoc internal scripts not suitable for production.
  • Compliance Burden: Quarterly security operations reviews required testing 18 different controls.

2. What options did the customer evaluate?

Internal Development

Building an internal engineering team (minimum 3 dedicated engineers).

Traditional GRC Tools

Considered vendors like Drata but found rigid/incomplete integrations.

Replacement Solutions

Considered replacing AuditBoard; rejected due to existing investment.

Augmentation Tools

Searched for middleware to enhance the existing AuditBoard investment.

3. Why did the customer select ComplianceCow?

The Only True Middleware Solution

Coordinate activities, collect evidence, manipulate data, and upload to AuditBoard.

Non-Disruptive

Augments rather than replaces existing GRC investments.

Customizable

Build features based on specific needs; avoids rigid, incomplete integrations.

Engineering Alternative

Eliminates need to build an internal engineering team.

Partnership Approach

Custom solutions and dedicated support.

4. Solution Provided by ComplianceCow

Automated Quarterly Reviews: Automated security operations review procedures for 16 controls in ~8 weeks.

Key Integrations: GitHub, AuditBoard, Jira, Snowflake, Slack, and Cloud Infrastructure services.

Evidence Automation: Automated evidence collection, manipulation, and upload to AuditBoard.

Full Population Testing: Complete data analysis rather than sampling.

Engineering Capital: Acted as an extended GRC engineering team; implemented fallback plans and training sessions.

How we automated 16 PCI controls

  • Data plumbing: Connected Snowflake, GitHub, and change sources; normalized datasets for assurance.
  • Rules & checks: Encoded quarterly review procedures as full-population control tests (no small samples).
  • Tasking in Slack/Jira: Owner prompts, evidence requests, and tickets created automatically with due dates.
  • Automated evidence: Collected, transformed, and uploaded artifacts to AuditBoard for review continuity.
  • Fail-safes & enablement: Fallback plans kept cycles moving; training improved ramp time and consistency.

5. Key Benefits of the Solution

0%
Reduction in human hours
0%
Data coverage via full-population
0
Controls automated
  • Reduced cognitive load; no manual queries or specialized technical skills.
  • Reduced bias; automation of assurance process and remediation flows.
  • Reduced operator toil; Slack follow-ups meet owners where they are.
  • Improved engagement of GRC teams with Security and Engineering.
  • Scalability without proportional headcount increase.
  • Continuous assurance; continuous evidence collection across audit cycles.

6. Results

  • Operational Success: 16 PCI controls automated in the recent quarter.
  • Strategic Vision Progress: Moving toward automating annual audits end-to-end.
  • Continuous Improvement: Each controls attestation process shows improvement over the previous.
  • Human hours reduced by ~80% through workflow automation and consolidated execution.
  • Future Roadmap: AI-powered automation; self-serve build for assessments/rules/workflows; measurement hygiene (hours saved, time-to-complete).
  • Expansion Plans: Iterative rollout to additional divisions.
  • Marketing Value: Logo usage and testimonials in progress.

Before vs After

Area Before After
Assurance Manual sampling Full-population checks
Controls coverage Ad-hoc scripts 16 controls automated
Human effort Heavy manual effort each quarter ~80% fewer human hours
Evidence Manual collection & uploads Automated evidence to AuditBoard

Technology Stack

Integrations used in this engagement:

Technology Stack (semantic list)

  • GRC/Assurance: AuditBoard
  • Workflow/Collab: Jira, Slack
  • Data: Snowflake
  • Code/Changes: GitHub
  • Deployment: SaaS (current scope)

FAQ — Key Questions

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