Topic starter
11/07/2026 8:45 pm
TL;DR: Customer due diligence workflows sit at the intersection of fraud prevention, regulatory compliance, and sensitive data handling, and Prove Identity’s developer guide shows that API design, data minimisation, and verification friction are the main implementation pain points. The governance challenge is that CDD is no longer just an onboarding feature. It is an identity control plane that must be secured, measured, and integrated like any other critical verification system.
Editorial analysis by NHI Mgmt Group, based on content published by Prove Identity: “Integrating Customer Due Diligence Workflows: Challenges and Solutions for Developers”.
Key questions
Q: What breaks when CDD workflows are not governed as part of identity architecture?
A: When CDD is treated as a simple application feature, policy decisions fragment across code, APIs and operations.
Q: Why do CDD flows create both compliance and fraud risk?
A: CDD sits at the point where identity proofing, data collection and risk screening meet.
Q: What are the signs that a CDD workflow is too fragile to scale?
A: Common signs include repeated manual exceptions, inconsistent required fields by region, rising abandonment during verification, and frequent code changes to accommodate regulatory updates.
Practitioner guidance
- Define CDD as a governed control plane Map each verification step to a policy owner, an evidence source and an audit requirement so the workflow is managed like a control, not just a feature.
- Minimise the identity data collected Collect only the fields required for the jurisdiction and risk tier, then separate storage and retention rules for high-sensitivity identity attributes.
- Harden API boundaries around verification data Restrict which services can request, return or cache identity attributes, and log every access to the verification payload.
Bottom line: CDD integration is an identity governance issue because verification logic, data handling and compliance rules all converge in the same workflow.
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11/07/2026 9:11 pm
CDD workflow integration is an identity governance problem disguised as application development. The article shows that verification, risk screening and data handling are not separable implementation details. They are policy decisions that determine who is trusted, what evidence is collected, and how much personal data the business is prepared to expose. Practitioners should treat the workflow as part of the identity architecture, not as a peripheral integration task.
A few things that frame the scale:
- Only 44% of developers are reported to follow security best practices for secrets management, exposing a significant developer behaviour gap, according to the State of Secrets in AppSec.
A question worth separating out:
Q: How can teams balance strong verification with low onboarding friction?
A: Use risk-based flows so the most stringent checks are reserved for higher-risk cases. Combine document validation, biometrics, and trusted data sources to reduce manual review while keeping enough assurance to prevent fraud and support conversion.
👉 Read our full editorial: CDD workflow integration exposes the identity governance gap