Cheng Siong Chin This workflow corresponds to n8n.io template #13598 — we link there as the canonical source.
This workflow follows the Agent → Agenttool recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "cphR_KAxJohQxF55aVcHu",
"name": "AI-powered transaction fraud detection and compliance monitoring",
"tags": [],
"nodes": [
{
"id": "51c177b4-5c51-4e3f-9bbd-21563edf26c4",
"name": "Schedule Trigger",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
-2816,
32
],
"parameters": {
"rule": {
"interval": [
{
"field": "minutes",
"minutesInterval": 15
}
]
}
},
"typeVersion": 1.3
},
{
"id": "814d0d9f-9d3f-4918-8194-4f00198b339b",
"name": "Workflow Configuration",
"type": "n8n-nodes-base.set",
"position": [
-2592,
32
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "id-1",
"name": "riskThresholdHigh",
"type": "number",
"value": 80
},
{
"id": "id-2",
"name": "riskThresholdMedium",
"type": "number",
"value": 50
},
{
"id": "id-3",
"name": "complianceFramework",
"type": "string",
"value": "AML/KYC"
},
{
"id": "id-4",
"name": "investigationDepth",
"type": "string",
"value": "comprehensive"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "e8cc329e-209e-4b28-b52d-5aa448deccef",
"name": "Fetch Pending Transactions",
"type": "n8n-nodes-base.airtable",
"position": [
-2368,
32
],
"parameters": {
"base": {
"__rl": true,
"mode": "id",
"value": "<__PLACEHOLDER_VALUE__Airtable Base ID__>"
},
"table": {
"__rl": true,
"mode": "id",
"value": "<__PLACEHOLDER_VALUE__Transactions Table ID__>"
},
"options": {},
"operation": "search",
"filterByFormula": "={Status} = \"Pending\""
},
"typeVersion": 2.1
},
{
"id": "3062cb09-5b65-4103-bee1-afce57578af9",
"name": "Transaction Signal Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-2144,
32
],
"parameters": {
"text": "={{ $json }}",
"options": {
"systemMessage": "You are a Transaction Signal Validation Agent specialized in analyzing on-chain blockchain transactions.\n\nYour task is to:\n1. Validate transaction data structure and completeness\n2. Extract key transaction signals (amount, sender, receiver, timestamp, chain, contract)\n3. Identify anomalies or suspicious patterns (unusual amounts, blacklisted addresses, rapid transfers)\n4. Calculate preliminary risk score (0-100) based on transaction characteristics\n5. Flag transactions requiring deeper investigation\n6. Provide reasoning for risk assessment\n\nConsider: transaction velocity, amount thresholds, address reputation, contract interactions, and historical patterns.\n\nReturn structured output with validated signals and risk assessment."
},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 3.1
},
{
"id": "dc6383d4-5674-47b9-86f5-cce2597efb08",
"name": "OpenAI Model - Transaction Signal",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-2176,
256
],
"parameters": {
"model": {
"__rl": true,
"mode": "id",
"value": "gpt-4o"
},
"options": {},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "94166fdc-3be3-4562-a15a-b98832caf90a",
"name": "Transaction Signal Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
-2000,
256
],
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"transactionId\": {\"type\": \"string\"},\n \"validationStatus\": {\"type\": \"string\", \"enum\": [\"valid\", \"invalid\", \"incomplete\"]},\n \"riskScore\": {\"type\": \"number\", \"minimum\": 0, \"maximum\": 100},\n \"riskLevel\": {\"type\": \"string\", \"enum\": [\"low\", \"medium\", \"high\"]},\n \"signals\": {\n \"type\": \"object\",\n \"properties\": {\n \"amount\": {\"type\": \"number\"},\n \"sender\": {\"type\": \"string\"},\n \"receiver\": {\"type\": \"string\"},\n \"timestamp\": {\"type\": \"string\"},\n \"chain\": {\"type\": \"string\"},\n \"contractAddress\": {\"type\": \"string\"}\n }\n },\n \"anomalies\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n \"requiresInvestigation\": {\"type\": \"boolean\"},\n \"reasoning\": {\"type\": \"string\"}\n },\n \"required\": [\"transactionId\", \"validationStatus\", \"riskScore\", \"riskLevel\", \"signals\", \"anomalies\", \"requiresInvestigation\", \"reasoning\"]\n}"
},
"typeVersion": 1.3
},
{
"id": "d04daab8-5b4b-4e79-a5bd-05415b8aca71",
"name": "Route by Risk Level",
"type": "n8n-nodes-base.switch",
"position": [
-1792,
0
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "High Risk",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": false,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.riskLevel }}",
"rightValue": "high"
}
]
},
"renameOutput": true
},
{
"outputKey": "Medium Risk",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": false,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.riskLevel }}",
"rightValue": "medium"
}
]
},
"renameOutput": true
},
{
"outputKey": "Low Risk",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": false,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.riskLevel }}",
"rightValue": "low"
}
]
},
"renameOutput": true
}
]
},
"options": {
"fallbackOutput": "extra",
"renameFallbackOutput": "Unclassified"
}
},
"typeVersion": 3.4
},
{
"id": "fb209cf4-caf5-4c1d-b6d0-49a195edb833",
"name": "Compliance Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-1040,
32
],
"parameters": {
"text": "={{ $json }}",
"options": {
"systemMessage": "You are a Compliance Orchestration Agent coordinating regulatory compliance and investigation workflows for blockchain transactions.\n\nYour task is to:\n1. Assess compliance requirements based on transaction risk level and signals\n2. Coordinate specialized agent tools for investigation, risk scoring, and reporting\n3. Call Investigation Agent Tool for high-risk transactions requiring deep analysis\n4. Call Risk Scoring Agent Tool to refine risk assessment with additional context\n5. Call Reporting Agent Tool to generate compliance reports\n6. Use Airtable Tool to query historical compliance records and update case status\n7. Determine final compliance action (approve, flag, escalate, block)\n8. Provide comprehensive reasoning for compliance decisions\n\nConsider: regulatory frameworks (AML/KYC), risk thresholds, investigation findings, and historical patterns.\n\nReturn structured compliance action with detailed justification."
},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 3.1
},
{
"id": "85def18f-b407-4719-bea9-75c4c44a6aa9",
"name": "OpenAI Model - Compliance",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-1568,
256
],
"parameters": {
"model": {
"__rl": true,
"mode": "id",
"value": "gpt-4o"
},
"options": {},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "f3140370-649e-43af-b4f0-5fc94fe885fc",
"name": "Compliance Action Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
-448,
256
],
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"transactionId\": {\"type\": \"string\"},\n \"complianceAction\": {\"type\": \"string\", \"enum\": [\"approve\", \"flag\", \"escalate\", \"block\"]},\n \"finalRiskScore\": {\"type\": \"number\", \"minimum\": 0, \"maximum\": 100},\n \"investigationSummary\": {\"type\": \"string\"},\n \"complianceFrameworks\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n \"requiredActions\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n \"escalationRequired\": {\"type\": \"boolean\"},\n \"reportGenerated\": {\"type\": \"boolean\"},\n \"reasoning\": {\"type\": \"string\"}\n },\n \"required\": [\"transactionId\", \"complianceAction\", \"finalRiskScore\", \"investigationSummary\", \"complianceFrameworks\", \"requiredActions\", \"escalationRequired\", \"reportGenerated\", \"reasoning\"]\n}"
},
"typeVersion": 1.3
},
{
"id": "16e60986-e6cc-4a8c-8597-7fa0f8d2953b",
"name": "Investigation Agent Tool",
"type": "@n8n/n8n-nodes-langchain.agentTool",
"position": [
-1440,
256
],
"parameters": {
"text": "={{ $fromAI(\"transactionData\", \"Transaction data and signals for investigation\", \"json\") }}",
"options": {
"systemMessage": "You are an Investigation Specialist Agent conducting deep analysis of suspicious blockchain transactions.\n\nYour task is to:\n1. Analyze transaction patterns and behavioral indicators\n2. Cross-reference sender/receiver addresses against known threat databases\n3. Examine transaction graph and fund flow patterns\n4. Identify potential money laundering, fraud, or sanctioned entity involvement\n5. Assess transaction context (timing, amount patterns, counterparty relationships)\n6. Determine investigation findings and evidence quality\n7. Provide detailed investigation report with supporting evidence\n\nConsider: address clustering, transaction velocity, layering patterns, and regulatory red flags.\n\nReturn structured investigation findings with evidence and recommendations."
},
"hasOutputParser": true,
"toolDescription": "Conducts deep investigation of suspicious transactions including pattern analysis, address verification, and fund flow tracking"
},
"typeVersion": 3
},
{
"id": "f3c52b44-2d5f-4345-afcc-71e2e75e2178",
"name": "OpenAI Model - Investigation",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-1488,
464
],
"parameters": {
"model": {
"__rl": true,
"mode": "id",
"value": "gpt-4o"
},
"options": {},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "f42a10f0-bfc7-468b-aaa8-2cf6084edead",
"name": "Investigation Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
-1328,
464
],
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"investigationId\": {\"type\": \"string\"},\n \"findings\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n \"threatLevel\": {\"type\": \"string\", \"enum\": [\"none\", \"low\", \"medium\", \"high\", \"critical\"]},\n \"evidenceQuality\": {\"type\": \"string\", \"enum\": [\"weak\", \"moderate\", \"strong\", \"conclusive\"]},\n \"suspiciousPatterns\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n \"addressFlags\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n \"recommendations\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n \"reasoning\": {\"type\": \"string\"}\n },\n \"required\": [\"investigationId\", \"findings\", \"threatLevel\", \"evidenceQuality\", \"suspiciousPatterns\", \"addressFlags\", \"recommendations\", \"reasoning\"]\n}"
},
"typeVersion": 1.3
},
{
"id": "79d499c6-f1a4-458e-98f6-c78a2e8a1843",
"name": "Risk Scoring Agent Tool",
"type": "@n8n/n8n-nodes-langchain.agentTool",
"position": [
-1152,
256
],
"parameters": {
"text": "={{ $fromAI(\"transactionData\", \"Transaction data and investigation findings for risk scoring\", \"json\") }}",
"options": {
"systemMessage": "You are a Risk Scoring Specialist Agent providing advanced risk assessment for blockchain transactions.\n\nYour task is to:\n1. Analyze transaction characteristics and investigation findings\n2. Apply multi-factor risk scoring model (amount, velocity, counterparty, geography)\n3. Weight risk factors based on compliance framework requirements\n4. Calculate refined risk score (0-100) with confidence level\n5. Identify primary risk drivers and contributing factors\n6. Provide risk score justification and sensitivity analysis\n7. Recommend risk mitigation strategies\n\nConsider: transaction context, historical patterns, investigation evidence, and regulatory thresholds.\n\nReturn structured risk assessment with detailed scoring breakdown."
},
"hasOutputParser": true,
"toolDescription": "Calculates refined risk scores using multi-factor analysis and investigation findings"
},
"typeVersion": 3
},
{
"id": "fca0c80d-fe05-49a7-96f4-550588fdfc86",
"name": "OpenAI Model - Risk Scoring",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-1152,
464
],
"parameters": {
"model": {
"__rl": true,
"mode": "id",
"value": "gpt-4o"
},
"options": {},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "dec39fa5-b161-4b3b-b5c5-29af729028b8",
"name": "Risk Score Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
-928,
464
],
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"riskScoreId\": {\"type\": \"string\"},\n \"refinedRiskScore\": {\"type\": \"number\", \"minimum\": 0, \"maximum\": 100},\n \"confidenceLevel\": {\"type\": \"string\", \"enum\": [\"low\", \"medium\", \"high\"]},\n \"primaryRiskDrivers\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n \"riskFactors\": {\n \"type\": \"object\",\n \"properties\": {\n \"amountRisk\": {\"type\": \"number\"},\n \"velocityRisk\": {\"type\": \"number\"},\n \"counterpartyRisk\": {\"type\": \"number\"},\n \"geographyRisk\": {\"type\": \"number\"}\n }\n },\n \"mitigationStrategies\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n \"reasoning\": {\"type\": \"string\"}\n },\n \"required\": [\"riskScoreId\", \"refinedRiskScore\", \"confidenceLevel\", \"primaryRiskDrivers\", \"riskFactors\", \"mitigationStrategies\", \"reasoning\"]\n}"
},
"typeVersion": 1.3
},
{
"id": "6441c3b1-b470-43f8-9cef-ffd0eca5e25d",
"name": "Airtable Tool - Compliance Records",
"type": "n8n-nodes-base.airtableTool",
"position": [
-864,
256
],
"parameters": {
"base": {
"__rl": true,
"mode": "id",
"value": "<__PLACEHOLDER_VALUE__Airtable Base ID__>"
},
"table": {
"__rl": true,
"mode": "id",
"value": "<__PLACEHOLDER_VALUE__Compliance Records Table ID__>"
},
"options": {},
"operation": "search",
"descriptionType": "manual",
"toolDescription": "Query and update compliance records in Airtable including historical cases and investigation status"
},
"typeVersion": 2.1
},
{
"id": "fbac0627-c5e1-4fd5-92f5-65c0a3e8eb8b",
"name": "Reporting Agent Tool",
"type": "@n8n/n8n-nodes-langchain.agentTool",
"position": [
-736,
256
],
"parameters": {
"text": "={{ $fromAI(\"complianceData\", \"Compliance assessment and investigation data for reporting\", \"json\") }}",
"options": {
"systemMessage": "You are a Compliance Reporting Specialist Agent generating regulatory compliance reports.\n\nYour task is to:\n1. Compile comprehensive compliance report from investigation and risk assessment data\n2. Structure report according to regulatory requirements (AML/KYC, SAR format)\n3. Include executive summary, findings, evidence, and recommendations\n4. Highlight key risk indicators and compliance violations\n5. Provide actionable next steps for compliance team\n6. Format report for regulatory submission if required\n7. Generate report metadata (timestamp, case ID, severity)\n\nConsider: regulatory reporting standards, evidence documentation, and audit trail requirements.\n\nReturn structured compliance report ready for review and submission."
},
"hasOutputParser": true,
"toolDescription": "Generates comprehensive compliance reports including findings, evidence, and regulatory recommendations"
},
"typeVersion": 3
},
{
"id": "b43defb1-68c4-451e-a60b-8fd09a191cb6",
"name": "OpenAI Model - Reporting",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-720,
464
],
"parameters": {
"model": {
"__rl": true,
"mode": "id",
"value": "gpt-4o"
},
"options": {},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "eb9055b1-b197-487b-ae37-568fa5b2924e",
"name": "Report Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
-512,
464
],
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"reportId\": {\"type\": \"string\"},\n \"reportType\": {\"type\": \"string\", \"enum\": [\"investigation\", \"compliance\", \"SAR\", \"summary\"]},\n \"executiveSummary\": {\"type\": \"string\"},\n \"findings\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n \"evidence\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n \"recommendations\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n \"nextSteps\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n \"severity\": {\"type\": \"string\", \"enum\": [\"low\", \"medium\", \"high\", \"critical\"]},\n \"timestamp\": {\"type\": \"string\"},\n \"reasoning\": {\"type\": \"string\"}\n },\n \"required\": [\"reportId\", \"reportType\", \"executiveSummary\", \"findings\", \"evidence\", \"recommendations\", \"nextSteps\", \"severity\", \"timestamp\", \"reasoning\"]\n}"
},
"typeVersion": 1.3
},
{
"id": "77cffc19-5598-4a11-b7bc-7f9361d31719",
"name": "Merge Results",
"type": "n8n-nodes-base.merge",
"position": [
-240,
16
],
"parameters": {
"numberInputs": 3
},
"typeVersion": 3.2
},
{
"id": "9bd90c48-f19f-4a7b-9290-4fb631443ee5",
"name": "Update Transaction Records",
"type": "n8n-nodes-base.airtable",
"position": [
-16,
32
],
"parameters": {
"base": {
"__rl": true,
"mode": "id",
"value": "<__PLACEHOLDER_VALUE__Airtable Base ID__>"
},
"table": {
"__rl": true,
"mode": "id",
"value": "<__PLACEHOLDER_VALUE__Transactions Table ID__>"
},
"columns": {
"value": {
"Status": "={{ $json.complianceAction }}",
"Report ID": "={{ $json.reportId }}",
"Risk Score": "={{ $json.finalRiskScore }}",
"Updated At": "={{ $now.toISO() }}",
"Compliance Action": "={{ $json.complianceAction }}",
"Investigation Summary": "={{ $json.investigationSummary }}"
},
"mappingMode": "defineBelow"
},
"options": {},
"operation": "update"
},
"typeVersion": 2.1
},
{
"id": "7feb3a96-92e2-49d0-a771-7b6250673753",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1696,
-496
],
"parameters": {
"color": 5,
"width": 400,
"height": 304,
"content": "## Prerequisites\nn8n (cloud or self-hosted), OpenAI API key (GPT-4), Airtable account with configured base and appropriate table schema \n## Use Cases\nCompliance teams automating AML screening and suspicious transaction flagging across high transaction volumes\n## Customization\nReplace OpenAI GPT-4 with Anthropic Claude or NVIDIA NIM in any agent node\n## Benefits\nAutomates end-to-end fraud detection and compliance reporting, eliminating manual transaction reviews"
},
"typeVersion": 1
},
{
"id": "0d8a22bb-6c48-4c43-89f0-ecb1c106d137",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2080,
-480
],
"parameters": {
"width": 320,
"height": 304,
"content": "## Setup Steps\n1. Import workflow JSON into your n8n instance.\n2. Add OpenAI API credentials.\n3. Set Schedule Trigger frequency aligned to your transaction processing cycle.\n4. Update Workflow Configuration node with risk thresholds and compliance rule parameters.\n5. Connect Airtable credentials and configure base/table IDs for Fetch Pending Transactions."
},
"typeVersion": 1
},
{
"id": "f41397e7-523b-4f23-9f7a-e7df8cad2241",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2880,
-416
],
"parameters": {
"width": 752,
"height": 256,
"content": "## How It Works\nThis workflow automates financial transaction monitoring, fraud detection, and regulatory compliance using OpenAI GPT-4 across coordinated specialist agents. It targets compliance officers, fraud analysts, and fintech operations teams managing high transaction volumes where manual review is too slow to catch emerging fraud patterns and compliance breaches in time. On schedule, the system fetches pending transactions from Airtable and routes them through a Transaction Signal Agent that classifies each by risk level\u2014High, Medium, Low, or Unclassified. A Compliance Agent then coordinates three specialist agents: Investigation, Risk Scoring, and Reporting. Airtable stores all compliance records throughout. Results merge and update transaction records directly, giving compliance teams a fully automated, audit-ready pipeline that flags fraud, scores risk, and generates regulatory reports without manual intervention."
},
"typeVersion": 1
},
{
"id": "fc0e8d05-651a-4d05-a13e-82151504037d",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2864,
-112
],
"parameters": {
"color": 7,
"width": 624,
"height": 560,
"content": "## Fetch Pending Transactions\n**What:** Retrieves unreviewed transaction records from Airtable.\n**Why:** Provides a structured, live transaction queue for AI risk analysis."
},
"typeVersion": 1
},
{
"id": "7859ba61-f5ad-4fcf-9230-13771fc1cd13",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1616,
-112
],
"parameters": {
"color": 7,
"width": 1328,
"height": 800,
"content": "## Compliance Records Storage\n**What:** Airtable Tool logs all compliance findings and agent outputs throughout processing.\n**Why:** Maintains a real-time, audit-ready record of every transaction reviewed.\n"
},
"typeVersion": 1
},
{
"id": "d442892f-139e-484f-a091-3ea616d683f2",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-272,
-128
],
"parameters": {
"color": 7,
"width": 464,
"height": 784,
"content": "\n## Merge & Update Records\n**What:** All agent outputs are consolidated and transaction records updated in Airtable.\n**Why:** Ensures a single, unified compliance status per transaction for downstream reporting."
},
"typeVersion": 1
},
{
"id": "77171a3c-079b-4d48-81f1-7d887475df66",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2208,
-112
],
"parameters": {
"color": 7,
"width": 576,
"height": 640,
"content": "## Specialist Agent Processing\n**What:** Investigation, Risk Scoring, and Reporting agents run per risk routing path.\n**Why:** Each agent targets a distinct compliance function, improving detection accuracy.\n"
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"availableInMCP": false,
"executionOrder": "v1"
},
"versionId": "85479073-b0d8-4fa6-8826-bb9f5888841d",
"connections": {
"Merge Results": {
"main": [
[
{
"node": "Update Transaction Records",
"type": "main",
"index": 0
}
]
]
},
"Report Parser": {
"ai_outputParser": [
[
{
"node": "Reporting Agent Tool",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Compliance Agent": {
"main": [
[
{
"node": "Merge Results",
"type": "main",
"index": 0
},
{
"node": "Merge Results",
"type": "main",
"index": 1
},
{
"node": "Merge Results",
"type": "main",
"index": 2
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "Workflow Configuration",
"type": "main",
"index": 0
}
]
]
},
"Risk Score Parser": {
"ai_outputParser": [
[
{
"node": "Risk Scoring Agent Tool",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Route by Risk Level": {
"main": [
[
{
"node": "Compliance Agent",
"type": "main",
"index": 0
}
],
[
{
"node": "Compliance Agent",
"type": "main",
"index": 0
}
],
[
{
"node": "Compliance Agent",
"type": "main",
"index": 0
}
]
]
},
"Investigation Parser": {
"ai_outputParser": [
[
{
"node": "Investigation Agent Tool",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Reporting Agent Tool": {
"ai_tool": [
[
{
"node": "Compliance Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Workflow Configuration": {
"main": [
[
{
"node": "Fetch Pending Transactions",
"type": "main",
"index": 0
}
]
]
},
"Risk Scoring Agent Tool": {
"ai_tool": [
[
{
"node": "Compliance Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Compliance Action Parser": {
"ai_outputParser": [
[
{
"node": "Compliance Agent",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Investigation Agent Tool": {
"ai_tool": [
[
{
"node": "Compliance Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"OpenAI Model - Reporting": {
"ai_languageModel": [
[
{
"node": "Reporting Agent Tool",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Transaction Signal Agent": {
"main": [
[
{
"node": "Route by Risk Level",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Model - Compliance": {
"ai_languageModel": [
[
{
"node": "Compliance Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Transaction Signal Parser": {
"ai_outputParser": [
[
{
"node": "Transaction Signal Agent",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Fetch Pending Transactions": {
"main": [
[
{
"node": "Transaction Signal Agent",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Model - Risk Scoring": {
"ai_languageModel": [
[
{
"node": "Risk Scoring Agent Tool",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"OpenAI Model - Investigation": {
"ai_languageModel": [
[
{
"node": "Investigation Agent Tool",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"OpenAI Model - Transaction Signal": {
"ai_languageModel": [
[
{
"node": "Transaction Signal Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Airtable Tool - Compliance Records": {
"ai_tool": [
[
{
"node": "Compliance Agent",
"type": "ai_tool",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
openAiApi
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
This workflow automates financial transaction monitoring, fraud detection, and regulatory compliance using OpenAI GPT-4 across coordinated specialist agents. It targets compliance officers, fraud analysts, and fintech operations teams managing high transaction volumes where…
Source: https://n8n.io/workflows/13598/ — original creator credit. Request a take-down →
Related workflows
Workflows that share integrations, category, or trigger type with this one. All free to copy and import.
This n8n automation workflow automates the creation, scripting, production, and posting of YouTube videos. It leverages AI (OpenAI), image generation (PIAPI), video rendering (Shotstack), and platform
Agent, OpenAI Chat, Airtable Tool +7
This workflow automates end-to-end ESG (Environmental, Social, and Governance) sustainability reporting for enterprise sustainability teams, compliance officers, and green governance leads. It solves
Agent, OpenAI Chat, Output Parser Structured +12
Schedules automated vendor pricing analysis across multiple sources. Fetches delivery reliability and contract data, analyzes vendor performance using Claude AI, then distributes consolidated reports
HTTP Request, Airtable, OpenAI Chat +9
The AI-Powered Shopify SEO Content Automation is an enterprise-grade workflow that transforms product content creation for e-commerce stores. This sophisticated multi-agent system integrates GPT-4o, C
Perplexity Tool, Memory Buffer Window, Agent +15
Agent Nodes. Uses lmChatOpenAi, slack, stopAndError, errorTrigger. Event-driven trigger; 72 nodes.
OpenAI Chat, Slack, Stop And Error +12