KYC Risk Profiling
Submits KYC details via form to AI for instant risk classification.
finance and accounting teamsops and IT teams
What it does
You instantly classify customer risk by submitting KYC details through an n8n form, which sends the data to OpenAI for automated profiling. High-risk cases automatically save to a Google Sheet and trigger a Slack alert, while lower-risk submissions are logged separately for your review.
Step by step
- Configure the n8n Form node to capture fields like name, date of birth, and country.
- Set up a Switch node in n8n to route data based on the 'risk_level' property returned by the AI.
- Create two distinct Google Sheets: one for high-risk alerts and another for low-risk logging.
Where the LLM does the work
- Draft the system prompt that defines specific risk criteria such as PEP status, sanctions lists, and geographic restrictions.
- Design the output schema to ensure the AI returns a structured JSON object with clear 'risk_level' and 'reasoning' fields.
- Refine the classification logic to handle edge cases like ambiguous names or mixed-risk jurisdictions.
Watch out for
PII data sent to OpenAI may violate privacy regulations so you must implement strict data masking before the API call.
Google Sheets API quotas are low for bulk operations, batch insert rows instead of writing them one by one in the workflow.
Tools that fit
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
You are helping me build the following AI agent workflow. ## Goal KYC Risk Profiling: Submits KYC details via form to AI for instant risk classification. ## Specification - What it does: You instantly classify customer risk by submitting KYC details through an n8n form, which sends the data to OpenAI for automated profiling. High-risk cases automatically save to a Google Sheet and trigger a Slack alert, while lower-risk submissions are logged separately for your review. - Trigger: Triggered by an event (Event · on form submission) - Autonomy: Fully hands-off - Expected setup effort: about an afternoon - Tools/services involved: - n8n: Workflow orchestration and form collection - OpenAI: Automated risk classification and profiling - Google Sheets: Logging high-risk and normal-risk records - Slack: Alerting teams on high-risk cases ## Known pitfalls, handle each one explicitly in your implementation 1. PII data sent to OpenAI may violate privacy regulations so you must implement strict data masking before the API call. 2. Google Sheets API quotas are low for bulk operations, batch insert rows instead of writing them one by one in the workflow. ## Reference implementation https://n8n.io/workflows/15852 (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/automate-kyc-risk-profiling-with-ai/ via usecasesforagents.com
Frequently asked questions
Can I use a different Automation Platform than n8n?
Yes. n8n is only the example automation platform in this recipe. The same flow works with Home Assistant. Swap the automation platform connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Built for finance and accounting teams who'd rather review a draft than build one from scratch.
Ops-IT teams triaging their own internal requests get the same pattern, different queue.