{ "id": "WVxaI3QS8NkVm2Pc", "name": "2. Detecting Financial Distress & Credit Risk with Bright Data & n8n", "tags": [], "nodes": [ { "id": "3b9a501c-5f1e-4d70-8764-d81b4aebbd67", "name": "Run Financial Risk Scan", "type": "n8n-nodes-base.manualTrigger", "position": [ 64, 1392 ], "parameters": {}, "typeVersion": 1 }, { "id": "abc8a0a1-dcf6-40e6-a2c7-149e50e27821", "name": "Set Company & Risk Parameters", "type": "n8n-nodes-base.set", "position": [ 288, 1392 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "32c706ed-8497-43f2-9fd9-11f47da3cced", "name": "company", "type": "string", "value": "Wirecard AG" }, { "id": "d2f402fd-3861-4e5d-b325-dabfd079d0e0", "name": "country", "type": "string", "value": "Germany" }, { "id": "63a628bc-da00-4354-b487-27b78be3e836", "name": "riskIndicators", "type": "array", "value": "[\"audit fraud\", \"insolvency\", \"regulatory investigation\"]" }, { "id": "31fd3091-3dc7-45b5-95ed-98547fd3cd25", "name": "batchMode", "type": "boolean", "value": true } ] } }, "typeVersion": 3.4 }, { "id": "fe04ca3e-f104-490a-9e2c-7be918d677be", "name": "Validate Company Input", "type": "n8n-nodes-base.if", "position": [ 912, 1392 ], "parameters": { "options": {}, "conditions": { "options": { "version": 3, "leftValue": "", "caseSensitive": true, "typeValidation": "strict" }, "combinator": "and", "conditions": [ { "id": "781e4035-ef6f-4006-bc46-55c0768bcfdb", "operator": { "type": "string", "operation": "notEmpty", "singleValue": true }, "leftValue": "={{ $json.company }}", "rightValue": "" } ] } }, "typeVersion": 2.3 }, { "id": "a20bf44f-7fae-4696-b40e-f17886f2acc0", "name": "Scrape Financial Filings", "type": "@brightdata/n8n-nodes-brightdata.brightData", "onError": "continueErrorOutput", "position": [ 1216, 1120 ], "parameters": { "url": "=https://www.google.com/search?q={{encodeURIComponent($json.company)}}%20financial%20filings", "zone": { "__rl": true, "mode": "list", "value": "n8n_unlocker" }, "format": "json", "country": { "__rl": true, "mode": 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"list", "value": "n8n_unlocker" }, "format": "json", "country": { "__rl": true, "mode": "list", "value": "us" }, "requestOptions": {} }, "retryOnFail": true, "typeVersion": 1 }, { "id": "0158d04b-cc43-4a20-bb9b-23e34043ce48", "name": "Log Scraping Error", "type": "n8n-nodes-base.googleSheets", "position": [ 1488, 1872 ], "parameters": { "columns": { "value": { "hasError": "True", "errorCode": "={{$json.statusCode || $json.code || 'N/A'}}", "timestamp": "={{ $now }}", "errorSource": "Bright Data Scraper", "errorMessage": "={{$json.error?.message || $json.message || 'Unknown Bright Data Error'}}" }, "schema": [ { "id": "errorSource", "type": "string", "display": true, "required": false, "displayName": "errorSource", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "errorMessage", "type": "string", "display": true, "required": false, "displayName": "errorMessage", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "errorCode", "type": "string", "display": true, "required": false, "displayName": "errorCode", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "timestamp", "type": "string", "display": true, "required": false, "displayName": "timestamp", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "hasError", "type": "string", "display": true, "required": false, "displayName": "hasError", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "defineBelow", "matchingColumns": [], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "list", "value": 299945015, "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1-VJbc3CQi7F9ROjcQnfeVmtM6pQ0-MgCKzpXI_HzqCI/edit#gid=299945015", "cachedResultName": "BD log error" }, "documentId": { "__rl": true, "mode": "list", "value": "1CMaAm-dAZELQ05AkBkjSsitPNVdw2p5DDeiMI0MA7GE", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1CMaAm-dAZELQ05AkBkjSsitPNVdw2p5DDeiMI0MA7GE/edit?usp=drivesdk", "cachedResultName": "2. Bright Data Financial Distress & Credit Risk Intelligence Engine" } }, "typeVersion": 4.7 }, { "id": "12c21197-6cf8-40a9-88a8-7192bcdc3aea", "name": "Detect Filing Distress Signals", "type": "n8n-nodes-base.code", "position": [ 1568, 1104 ], "parameters": { "jsCode": "// Get HTML safely from Bright Data node\nconst html =\n $input.first().json.body ||\n $input.first().json.data ||\n \"\";\n\nconst text = html.toLowerCase();\n\n// Financial filings distress keywords\nconst keywords = [\n \"bankruptcy\",\n \"chapter 7\",\n \"chapter 11\",\n \"chapter 15\",\n \"liquidation\",\n \"restructuring\",\n \"default\",\n \"going concern\",\n \"credit downgrade\"\n];\n\nlet found = [];\n\nfor (const word of keywords) {\n if (text.includes(word)) {\n found.push(word);\n }\n}\n\nreturn [\n {\n source: \"financial_filings\",\n distressSignals: found\n }\n];\n" }, "typeVersion": 2 }, { "id": "cf2833e9-35a2-4ffd-86e0-d3aaf3fddaf5", "name": "Detect Insolvency Signals", "type": "n8n-nodes-base.code", "position": [ 1568, 1360 ], "parameters": { "jsCode": "const html =\n $input.first().json.body ||\n $input.first().json.data ||\n \"\";\n\nconst text = html.toLowerCase();\n\n// Insolvency register focused keywords\nconst keywords = [\n \"insolvency\",\n \"bankruptcy\",\n \"liquidation\",\n \"administrator\",\n \"receivership\",\n \"dissolution\",\n \"court filing\"\n];\n\nlet found = [];\n\nfor (const word of keywords) {\n if (text.includes(word)) {\n found.push(word);\n }\n}\n\nreturn [\n {\n source: \"insolvency_register\",\n distressSignals: found\n }\n];\n" }, "typeVersion": 2 }, { "id": "d3028be5-0062-425e-8ba3-9f26acfc7eca", "name": "Detect News Distress Signals", "type": "n8n-nodes-base.code", "position": [ 1568, 1632 ], "parameters": { "jsCode": "const html =\n $input.first().json.body ||\n $input.first().json.data ||\n \"\";\n\nconst text = html.toLowerCase();\n\n// Financial news distress keywords\nconst keywords = [\n \"bankruptcy\",\n \"insolvency\",\n \"financial distress\",\n \"missed payment\",\n \"default\",\n \"debt restructuring\",\n \"credit downgrade\",\n \"chapter 11\"\n];\n\nlet found = [];\n\nfor (const word of keywords) {\n if (text.includes(word)) {\n found.push(word);\n }\n}\n\nreturn [\n {\n source: \"financial_news\",\n distressSignals: found\n }\n];\n" }, "typeVersion": 2 }, { "id": "a6068d94-af8f-4b7d-b682-ca9c625f8390", "name": "Merge All Distress Signals", "type": "n8n-nodes-base.merge", "position": [ 1872, 1344 ], "parameters": { "numberInputs": 3 }, "typeVersion": 3.2 }, { "id": "7d61d212-525d-4fab-93a0-d66edc88e59a", "name": "Categorize & Normalize Signals", "type": "n8n-nodes-base.code", "position": [ 2608, 1360 ], "parameters": { "jsCode": "// Collect all distress signals WITH source tracking\nlet allSignals = [];\nlet signalDetails = [];\n\n// Merge se multiple items aate hain\nfor (const item of $input.all()) {\n\n const source = item.json.source || \"unknown\";\n\n if (item.json.distressSignals) {\n\n for (const signal of item.json.distressSignals) {\n\n allSignals.push(signal);\n\n signalDetails.push({\n signal: signal,\n source: source\n });\n\n }\n }\n}\n\n// Remove duplicate signals (but keep detail list intact)\nallSignals = [...new Set(allSignals)];\n\n\n// Categorization buckets\nlet bankruptcy = [];\nlet insolvency = [];\nlet restructuring = [];\nlet filingIssues = [];\n\n// Categorize signals\nfor (const signal of allSignals) {\n\n if (signal.includes(\"bankruptcy\") || signal.includes(\"chapter\")) {\n bankruptcy.push(signal);\n }\n\n if (signal.includes(\"insolvency\") || signal.includes(\"administrator\")) {\n insolvency.push(signal);\n }\n\n if (signal.includes(\"restructuring\") || signal.includes(\"liquidation\")) {\n restructuring.push(signal);\n }\n\n if (signal.includes(\"default\") || signal.includes(\"late filing\")) {\n filingIssues.push(signal);\n }\n}\n\n\n// Return normalized + source-aware structure\nreturn [{\n categorizedSignals: {\n bankruptcySignals: bankruptcy,\n insolvencySignals: insolvency,\n restructuringSignals: restructuring,\n filingIssueSignals: filingIssues\n },\n allSignals: allSignals,\n signalSourceMap: signalDetails,\n sourcesAnalyzed: [...new Set(signalDetails.map(s => s.source))]\n}];\n" }, "typeVersion": 2 }, { "id": "4269f0c3-afac-4e52-af10-30e6f17da734", "name": "Prepare Signals for AI Analysis", "type": "n8n-nodes-base.set", "position": [ 2848, 1360 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "ebe066cb-31ec-4fe1-b22e-68894a7bd95f", "name": "company", "type": "string", "value": "={{ $('Set Company & Risk Parameters').first().json.company }}" }, { "id": "7bdf8b01-4409-4437-8d16-3400e1daa1ae", "name": "country", "type": "string", "value": "={{ $('Set Company & Risk Parameters').first().json.country }}" }, { "id": "9431d16f-5db8-4a00-b0c4-3f3275d009b6", "name": "distressSignals", "type": "array", "value": "={{ $json.allSignals }}" } ] } }, "typeVersion": 3.4 }, { "id": "961b5b39-e67c-4eb2-86fe-941aa8abe12e", "name": "AI Financial Distress Classifier", "type": "@n8n/n8n-nodes-langchain.agent", "position": [ 3088, 1360 ], "parameters": { "text": "=Analyze the following financial distress signals:\n\n{{ $json.distressSignals }}\n\nInstructions:\n- Base your decision ONLY on the provided signals.\n- If signals are weak or limited, assign LOW probability.\n- Be conservative in scoring.\n- Do not assume missing information.\n\nClassify:\n1. Primary distress type\n2. Probability (Low / Medium / High)\n3. Numerical risk score (0\u2013100)\n4. Short explanation (1\u20132 lines max)\n\nRespond ONLY in strictly valid JSON format:\n\n{\n \"distressType\": \"\",\n \"probability\": \"\",\n \"riskScore\": 0,\n \"explanation\": \"\"\n}\n", "options": { "systemMessage": "You are a financial credit risk classification assistant.\n\nYou MUST:\n- Return strictly valid JSON.\n- Return no extra text outside JSON.\n- Be conservative and risk-aware.\n- Never invent facts not present in the signals.\n\nIf signals are minimal, classify as LOW probability.\n" }, "promptType": "define", "hasOutputParser": true }, "typeVersion": 3.1 }, { "id": "40ca3141-99de-4157-96be-642be38010ff", "name": "Validate AI Distress Output", "type": "@n8n/n8n-nodes-langchain.outputParserStructured", "position": [ 3248, 1632 ], "parameters": { "schemaType": "manual", "inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"distressType\": {\n \"type\": \"string\",\n \"description\": \"Primary financial distress classification\"\n },\n \"probability\": {\n \"type\": \"string\",\n \"enum\": [\"Low\", \"Medium\", \"High\"],\n \"description\": \"Estimated probability of distress\"\n },\n \"riskScore\": {\n \"type\": \"number\",\n \"minimum\": 0,\n \"maximum\": 100,\n \"description\": \"Numerical financial risk score from 0 to 100\"\n },\n \"explanation\": {\n \"type\": \"string\",\n \"description\": \"Short explanation of the classification\"\n }\n },\n \"required\": [\n \"distressType\",\n \"probability\",\n \"riskScore\",\n \"explanation\"\n ],\n \"additionalProperties\": false\n}\n" }, "typeVersion": 1.3 }, { "id": "9e282fec-c212-4537-a5d6-6dc748539696", "name": "Apply Probability Weighting", "type": "n8n-nodes-base.code", "position": [ 3440, 1360 ], "parameters": { "jsCode": "// Get AI Agent output safely\nconst aiOutput = items[0].json.output || {};\n\n// Extract AI values\nconst distressType = aiOutput.distressType || \"\";\nconst probability = aiOutput.probability || \"Low\";\nconst aiRiskScore = aiOutput.riskScore || 0;\nconst explanation = aiOutput.explanation || \"\";\n\n// Start with AI risk score\nlet correlatedScore = aiRiskScore;\n\n// Probability weighting (conservative adjustment)\nif (probability === \"High\") {\n correlatedScore += 10;\n} else if (probability === \"Medium\") {\n correlatedScore += 5;\n} else {\n correlatedScore += 0;\n}\n\n// Cap score between 0\u2013100\nif (correlatedScore > 100) correlatedScore = 100;\nif (correlatedScore < 0) correlatedScore = 0;\n\n// Return final structured output\nreturn [{\n distressType,\n probability,\n aiRiskScore,\n correlatedScore,\n explanation\n}];\n" }, "typeVersion": 2 }, { "id": "48d74bc4-633c-45bf-b769-4bfdf5778069", "name": "Apply Confidence Guardrails", "type": "n8n-nodes-base.code", "position": [ 3968, 1360 ], "parameters": { "jsCode": "// Get previous enriched output\nconst data = items[0].json;\n\n// Extract base values safely\nconst distressType = data.distressType || \"\";\nconst probability = data.probability || \"Low\";\nconst aiRiskScore = data.aiRiskScore || 0;\nconst correlatedScore = data.correlatedScore || 0;\nconst explanation = data.explanation || \"\";\nconst signalSourceMap = data.signalSourceMap || [];\n\n// Count unique sources (internal use only)\nlet uniqueSources = new Set();\n\nfor (const entry of signalSourceMap) {\n if (entry.source) {\n uniqueSources.add(entry.source);\n }\n}\n\n// Confidence Guardrail Logic\nlet confidenceLevel = \"Low\";\nlet confidenceScore = 30;\n\n// Strong multi-source confirmation\nif (uniqueSources.size >= 3 && correlatedScore > 75) {\n confidenceLevel = \"High\";\n confidenceScore = 90;\n}\nelse if (uniqueSources.size === 2 && correlatedScore > 60) {\n confidenceLevel = \"Medium\";\n confidenceScore = 70;\n}\nelse if (uniqueSources.size === 1) {\n confidenceLevel = \"Low\";\n confidenceScore = 40;\n}\n\n// News-only penalty\nif (uniqueSources.size === 1 && uniqueSources.has(\"financial_news\")) {\n confidenceScore -= 15;\n confidenceLevel = \"Low\";\n}\n\n// Blend AI + correlation influence\nconfidenceScore = Math.round(\n (confidenceScore * 0.7) + (aiRiskScore * 0.3)\n);\n\n// Cap between 0-100\nif (confidenceScore > 100) confidenceScore = 100;\nif (confidenceScore < 0) confidenceScore = 0;\n\n// Final structured return\nreturn [{\n distressType,\n probability,\n aiRiskScore,\n correlatedScore,\n confidenceLevel,\n confidenceScore,\n explanation\n}];\n" }, "typeVersion": 2 }, { "id": "a1a0ffc3-b849-442e-931b-ea8054a3f63f", "name": "Generate Business Risk Decisions", "type": "@n8n/n8n-nodes-langchain.agent", "position": [ 4192, 1360 ], "parameters": { "text": "=You are given final structured financial distress analysis.\n\nDistress Type: {{ $json.distressType }}\nProbability: {{ $json.probability }}\nAI Risk Score: {{ $json.aiRiskScore }}\nCorrelated Score: {{ $json.correlatedScore }}\nConfidence Level: {{ $json.confidenceLevel }}\nConfidence Score: {{ $json.confidenceScore }}\nExplanation: {{ $json.explanation }}\n\nApply the following business rules:\n\nSUPPLIER MONITORING:\n- confidenceScore >= 70 \u2192 High Risk\n- 50\u201369 \u2192 Moderate Risk\n- below 50 \u2192 Low Risk\n\nONBOARDING DECISION:\n- confidenceScore >= 75 \u2192 Reject\n- 55\u201374 \u2192 Manual Review\n- below 55 \u2192 Approve\n\nPORTFOLIO EXPOSURE:\n- confidenceScore >= 70 \u2192 Critical\n- 50\u201369 \u2192 Elevated\n- below 50 \u2192 Normal\n\nReturn STRICTLY valid JSON.\nDo NOT wrap the result in quotes.\nDo NOT return a string.\nReturn a direct JSON object.\n\nOutput format:\n\n{\n \"supplierMonitoring\": {\n \"riskStatus\": \"\",\n \"distressType\": \"\",\n \"probability\": \"\",\n \"confidenceScore\": 0\n },\n \"onboardingSnapshot\": {\n \"approvalRecommendation\": \"\",\n \"distressType\": \"\",\n \"confidenceScore\": 0\n },\n \"portfolioExposure\": {\n \"exposureCategory\": \"\",\n \"portfolioRiskWeight\": 0\n }\n}\n", "options": { "systemMessage": "You are a senior financial risk intelligence engine.\n\nYour task is to transform structured financial risk analysis data into three business-ready outputs:\n\n1) Supplier Monitoring Risk View\n2) Onboarding Credit Decision Snapshot\n3) Portfolio Exposure Feed\n\nRules:\n- Return STRICTLY valid JSON.\n- No extra commentary.\n- No markdown.\n- No explanations outside JSON.\n- Be conservative and risk-aware.\n- Base all decisions ONLY on provided scores and confidence values.\n- Do not invent data.\n- Maintain numerical integrity of provided scores.\n- Use structured decision logic.\n" }, "promptType": "define", "hasOutputParser": true }, "typeVersion": 3.1 }, { "id": "39058a33-7e3d-471f-8bc7-13d6d12e04e9", "name": "Validate Business Decision Output", "type": "@n8n/n8n-nodes-langchain.outputParserStructured", "position": [ 4336, 1616 ], "parameters": { "schemaType": "manual", "inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"supplierMonitoring\": {\n \"type\": \"object\",\n \"properties\": {\n \"riskStatus\": {\n \"type\": \"string\",\n \"enum\": [\"Low Risk\", \"Moderate Risk\", \"High Risk\"]\n },\n \"distressType\": {\n \"type\": \"string\"\n },\n \"probability\": {\n \"type\": \"string\",\n \"enum\": [\"Low\", \"Medium\", \"High\"]\n },\n \"confidenceScore\": {\n \"type\": \"number\",\n \"minimum\": 0,\n \"maximum\": 100\n }\n },\n \"required\": [\n \"riskStatus\",\n \"distressType\",\n \"probability\",\n \"confidenceScore\"\n ]\n },\n \"onboardingSnapshot\": {\n \"type\": \"object\",\n \"properties\": {\n \"approvalRecommendation\": {\n \"type\": \"string\",\n \"enum\": [\"Approve\", \"Manual Review\", \"Reject\"]\n },\n \"distressType\": {\n \"type\": \"string\"\n },\n \"confidenceScore\": {\n \"type\": \"number\",\n \"minimum\": 0,\n \"maximum\": 100\n }\n },\n \"required\": [\n \"approvalRecommendation\",\n \"distressType\",\n \"confidenceScore\"\n ]\n },\n \"portfolioExposure\": {\n \"type\": \"object\",\n \"properties\": {\n \"exposureCategory\": {\n \"type\": \"string\",\n \"enum\": [\"Normal\", \"Elevated\", \"Critical\"]\n },\n \"portfolioRiskWeight\": {\n \"type\": \"number\",\n \"minimum\": 0\n }\n },\n \"required\": [\n \"exposureCategory\",\n \"portfolioRiskWeight\"\n ]\n }\n },\n \"required\": [\n \"supplierMonitoring\",\n \"onboardingSnapshot\",\n \"portfolioExposure\"\n ]\n}\n" }, "typeVersion": 1.3 }, { "id": "c545d1d9-2bfa-45ee-b792-e8718d3fff94", "name": "Is High Supplier Risk?", "type": "n8n-nodes-base.if", "position": [ 4624, 1168 ], "parameters": { "options": {}, "conditions": { "options": { "version": 3, "leftValue": "", "caseSensitive": true, "typeValidation": "strict" }, "combinator": "and", "conditions": [ { "id": "e8cf7a4e-a6a0-492d-90d5-f31641c75beb", "operator": { "type": "string", "operation": "equals" }, "leftValue": "={{ $json.output.supplierMonitoring.riskStatus }}", "rightValue": "High Risk" } ] } }, "typeVersion": 2.3 }, { "id": "5fe0e38e-3d97-4af8-8728-4d1d14f086d3", "name": "No Action Required", "type": "n8n-nodes-base.noOp", "position": [ 4912, 1280 ], "parameters": {}, "typeVersion": 1 }, { "id": "2d6cb93b-5af0-4451-974c-2d65b295a4b7", "name": "Log Supplier Monitoring Risk", "type": "n8n-nodes-base.googleSheets", "position": [ 4912, 1056 ], "parameters": { "columns": { "value": { "country": "={{ $node[\"Set Company & Risk Parameters\"].json[\"country\"] }}", "riskStatus": "={{ $json.output.supplierMonitoring.riskStatus }}", "companyName": "={{ $node[\"Set Company & Risk Parameters\"].json[\"company\"] }}", "explanation": "={{ $('Apply Confidence Guardrails').item.json.explanation }}", "lastUpdated": "={{ $now }}", "probability": "={{ $json.output.supplierMonitoring.probability }}", "distressType": "={{ $json.output.supplierMonitoring.distressType }}", "confidenceScore": "={{ $json.output.supplierMonitoring.confidenceScore }}" }, "schema": [ { "id": "companyName", "type": "string", "display": true, "required": false, "displayName": "companyName", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "country", "type": "string", "display": true, "required": false, "displayName": "country", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "riskStatus", "type": "string", "display": true, "required": false, "displayName": "riskStatus", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "distressType", "type": "string", "display": true, "required": false, "displayName": "distressType", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "probability", "type": "string", "display": true, "required": false, "displayName": "probability", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "confidenceScore", "type": "string", "display": true, "required": false, "displayName": "confidenceScore", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "lastUpdated", "type": "string", "display": true, "required": false, "displayName": "lastUpdated", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "explanation", "type": "string", "display": true, "required": false, "displayName": "explanation", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "defineBelow", "matchingColumns": [], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "list", "value": "gid=0", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1-VJbc3CQi7F9ROjcQnfeVmtM6pQ0-MgCKzpXI_HzqCI/edit#gid=0", "cachedResultName": "Supplier Monitoring" }, "documentId": { "__rl": true, "mode": "list", "value": "1CMaAm-dAZELQ05AkBkjSsitPNVdw2p5DDeiMI0MA7GE", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1CMaAm-dAZELQ05AkBkjSsitPNVdw2p5DDeiMI0MA7GE/edit?usp=drivesdk", "cachedResultName": "2. Bright Data Financial Distress & Credit Risk Intelligence Engine" } }, "typeVersion": 4.7 }, { "id": "3826f3ba-4656-4c16-8d71-3c0ed59499fb", "name": "Log Onboarding Decision", "type": "n8n-nodes-base.googleSheets", "position": [ 4624, 1360 ], "parameters": { "columns": { "value": { "Country": "={{ $node[\"Set Company & Risk Parameters\"].json[\"country\"] }}", "TimeStamp": "={{ $now }}", "CompanyName": "={{ $node[\"Set Company & Risk Parameters\"].json[\"company\"] }}", "distressType": "={{ $json.output.onboardingSnapshot.distressType }}", "confidenceScore": "={{ $json.output.onboardingSnapshot.confidenceScore }}", "approvalRecommendation": "={{ $json.output.onboardingSnapshot.approvalRecommendation }}" }, "schema": [ { "id": "CompanyName", "type": "string", "display": true, "required": false, "displayName": "CompanyName", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Country", "type": "string", "display": true, "required": false, "displayName": "Country", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "approvalRecommendation", "type": "string", "display": true, "required": false, "displayName": "approvalRecommendation", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "distressType", "type": "string", "display": true, "required": false, "displayName": "distressType", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "confidenceScore", "type": "string", "display": true, "required": false, "displayName": "confidenceScore", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "TimeStamp", "type": "string", "display": true, "required": false, "displayName": "TimeStamp", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "defineBelow", "matchingColumns": [], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "list", "value": 1770084134, "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1CMaAm-dAZELQ05AkBkjSsitPNVdw2p5DDeiMI0MA7GE/edit#gid=1770084134", "cachedResultName": "Onboarding Snapshot Sheet" }, "documentId": { "__rl": true, "mode": "list", "value": "1CMaAm-dAZELQ05AkBkjSsitPNVdw2p5DDeiMI0MA7GE", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1CMaAm-dAZELQ05AkBkjSsitPNVdw2p5DDeiMI0MA7GE/edit?usp=drivesdk", "cachedResultName": "2. Bright Data Financial Distress & Credit Risk Intelligence Engine" } }, "typeVersion": 4.7 }, { "id": "81847e2d-6049-486d-aaf0-935e5884b4d1", "name": "Log Portfolio Exposure Status", "type": "n8n-nodes-base.googleSheets", "position": [ 4624, 1584 ], "parameters": { "columns": { "value": { "company": "={{ $node[\"Set Company & Risk Parameters\"].json[\"company\"] }}", "countryName": "={{ $node[\"Set Company & Risk Parameters\"].json[\"country\"] }}", "exposureCategory": "={{ $json.output.portfolioExposure.exposureCategory }}", "portfolioRiskWeight": "={{ $json.output.portfolioExposure.portfolioRiskWeight }}" }, "schema": [ { "id": "countryName", "type": "string", "display": true, "required": false, "displayName": "countryName", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "company", "type": "string", "display": true, "required": false, "displayName": "company", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "exposureCategory", "type": "string", "display": true, "required": false, "displayName": "exposureCategory", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "portfolioRiskWeight", "type": "string", "display": true, "required": false, "displayName": "portfolioRiskWeight", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "defineBelow", "matchingColumns": [], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "list", "value": 511663763, "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1CMaAm-dAZELQ05AkBkjSsitPNVdw2p5DDeiMI0MA7GE/edit#gid=511663763", "cachedResultName": "portfolioExposure" }, "documentId": { "__rl": true, "mode": "list", "value": "1CMaAm-dAZELQ05AkBkjSsitPNVdw2p5DDeiMI0MA7GE", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1CMaAm-dAZELQ05AkBkjSsitPNVdw2p5DDeiMI0MA7GE/edit?usp=drivesdk", "cachedResultName": "2. Bright Data Financial Distress & Credit Risk Intelligence Engine" } }, "typeVersion": 4.7 }, { "id": "0d63908f-8832-4808-9eae-9de45468c1d8", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [ -784, 816 ], "parameters": { "color": 4, "width": 512, "height": 560, "content": "## Financial Distress & Credit Risk Intelligence Engine\n\nThis workflow scans a company across financial filings, insolvency registers, and financial news to detect early distress signals.\n\nIt:\n\n- Collects multi-source financial risk indicators\n- Detects bankruptcy, insolvency, restructuring & default signals\n- Classifies financial distress using AI\n- Applies probability weighting and confidence guardrails\n- Converts analysis into business-ready credit decisions\n\nOutputs include:\n\u2022 Supplier Monitoring Risk Status \n\u2022 Onboarding Approval Recommendation \n\u2022 Portfolio Exposure Classification \n\nWhat you need:\n- Bright Data account (for web scraping)\n- OpenRouter API key (for AI analysis)\n- Google Sheets (for output dashboards)\n\nBuilt for conservative, signal-based risk intelligence.\n" }, "typeVersion": 1 }, { "id": "033bf803-f566-4366-8bf6-f81b202db4aa", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [ 848, 768 ], "parameters": { "color": 7, "width": 1200, "height": 1328, "content": "## Multi-Source Financial Signal Collection\n\nCollects and consolidates financial distress indicators from multiple verified public sources for early credit risk detection.\n\n- Scrapes financial filings for bankruptcy or restructuring disclosures \n- Monitors insolvency registers for liquidation or court filings \n- Extracts distress-related financial news mentions \n- Detects filing, insolvency, and news-based distress signals \n- Merges signals into a unified structured dataset \n- Logs scraping failures for monitoring and debugging \n\nCreates a reliable multi-source foundation for downstream financial distress classification." }, "typeVersion": 1 }, { "id": "f39697db-e09e-4fb1-9836-1b267cadb052", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [ 2512, 976 ], "parameters": { "color": 7, "width": 1104, "height": 816, "content": "## AI Financial Distress Classification & Risk Scoring\n\nAnalyzes detected financial distress signals using AI to estimate credit risk exposure and refine scoring reliability.\n\n- Categorizes and normalizes detected distress signals \n- Prepares structured inputs for AI evaluation \n- Identifies primary financial distress type \n- Assigns probability of distress occurrence \n- Generates conservative risk score \n- Applies probability-based score weighting \n- Validates AI-generated structured output \n- Applies confidence guardrails to adjust final risk score \n\nEnsures reliable financial risk classification based on multi-source signal strength." }, "typeVersion": 1 }, { "id": "9a675108-b614-4a6c-b637-1739d5d95676", "name": "Sticky Note3", "type": "n8n-nodes-base.stickyNote", "position": [ 3920, 928 ], "parameters": { "color": 7, "width": 1216, "height": 848, "content": "## Confidence Guardrails & Business Decisioning\n\nRefines financial risk scores using confirmation logic and converts validated insights into actionable business decisions.\n\n- Applies confidence guardrails to adjust final risk score \n- Uses multi-source confirmation for validation \n- Generates supplier monitoring risk status \n- Produces onboarding approval recommendation \n- Categorizes portfolio exposure level \n- Logs supplier monitoring decisions \n- Records onboarding and exposure insights \n\nTransforms validated financial signals into operational credit risk decisions." }, "typeVersion": 1 }, { "id": "fa572ec1-0146-49fe-a288-be6a989f2a41", "name": "Financial Distress Classifier", "type": "@n8n/n8n-nodes-langchain.lmChatOpenRouter", "position": [ 3072, 1632 ], "parameters": { "options": {} }, "typeVersion": 1 }, { "id": "61ff7bb5-5076-4f01-a556-68d2bc9a109b", "name": "Business Risk Decision Engine", "type": "@n8n/n8n-nodes-langchain.lmChatOpenRouter", "position": [ 4160, 1616 ], "parameters": { "options": {} }, "typeVersion": 1 }, { "id": "fd928013-5f62-459d-ad02-9ced3cffe868", "name": "Sticky Note5", "type": "n8n-nodes-base.stickyNote", "position": [ -784, 304 ], "parameters": { "color": 4, "width": 512, "height": 480, "content": "## Setup Instructions\n\nBefore running this workflow, configure the following credentials in n8n:\n\n**1. Bright Data API** \u2014 Required for web scraping\n- Sign up at brightdata.com\n- Create an API token\n- Add as \"BrightData account\" credential in n8n\n\n**2. OpenRouter API** \u2014 Required for AI classification\n- Sign up at openrouter.ai\n- Generate an API key\n- Add as \"OpenRouter account\" credential in n8n\n\n**3. Google Sheets OAuth** \u2014 Required for output logging\n- Connect your Google account in n8n\n- See the **Google Sheets Setup** sticky note for required tabs and columns\n- Update each Google Sheets node to point to your new spreadsheet\n\nAfter connecting credentials, edit the configuration node to set your target companies, URLs, or parameters." }, "typeVersion": 1 }, { "id": "6e7ebc20-8eb4-4197-995e-4f9af82a5bee", "name": "Sticky Note4", "type": "n8n-nodes-base.stickyNote", "position": [ 0, 1056 ], "parameters": { "color": 7, "width": 496, "height": 528, "content": "## Input & Risk Configuration\n\nInitial configuration block where company details and financial risk indicators are defined for distress analysis.\n\n- Initiates financial risk scan \n- Sets company name for evaluation \n- Defines country of incorporation \n- Specifies financial distress indicators to monitor \n- Validates input parameters before signal collection \n\nEnables targeted financial risk detection based on configurable inputs." }, "typeVersion": 1 }, { "id": "9357dcf0-2e38-4afa-b08b-b5defec46345", "name": "Sticky Note6", "type": "n8n-nodes-base.stickyNote", "position": [ -784, 1408 ], "parameters": { "color": 4, "width": 508, "height": 464, "content": "## Google Sheets Setup\n\nCreate a Google Spreadsheet with 4 tabs and add these column headers in row 1:\n\n**Tab: Supplier Monitoring**\ncompanyName | country | riskStatus | distressType | probability | confidenceScore | lastUpdated | explanation\n\n**Tab: Onboarding Snapshot Sheet**\nCompanyName | Country | approvalRecommendation | distressType | confidenceScore | TimeStamp\n\n**Tab: portfolioExposure**\ncountryName | company | exposureCategory | portfolioRiskWeight\n\n**Tab: BD log error**\nerrorSource | errorMessage | errorCode | timestamp | hasError\n\nAfter creating the spreadsheet, update each Google Sheets node to point to your document and select the matching tab." }, "typeVersion": 1 } ], "active": false, "settings": { "binaryMode": "separate", "availableInMCP": false, "executionOrder": "v1" }, "versionId": "67f33262-d9f3-45b3-aff0-916cc69964ab", "connections": { "Scrape Financial News": { "main": [ [ { "node": "Detect News Distress Signals", "type": "main", "index": 0 } ], [ { "node": "Log Scraping Error", "type": "main", "index": 0 } ] ] }, "Is High Supplier Risk?": { "main": [ [ { "node": "Log Supplier Monitoring Risk", "type": "main", "index": 0 } ], [ { "node": "No Action Required", "type": "main", "index": 0 } ] ] }, "Validate Company Input": { "main": [ [ { "node": "Scrape Financial Filings", "type": "main", "index": 0 }, { "node": "Scrape Insolvency Register", "type": "main", "index": 0 }, { "node": "Scrape Financial News", "type": "main", "index": 0 } ] ] }, "Run Financial Risk Scan": { "main": [ [ { "node": "Set Company & Risk Parameters", "type": "main", "index": 0 } ] ] }, "Scrape Financial Filings": { "main": [ [ { "node": "Detect Filing Distress Signals", "type": "main", "index": 0 } ], [ { "node": "Log Scraping Error", "type": "main", "index": 0 } ] ] }, "Detect Insolvency Signals": { "main": [ [ { "node": "Merge All Distress Signals", "type": "main", "index": 1 } ] ] }, "Merge All Distress Signals": { "main": [ [ { "node": "Categorize & Normalize Signals", "type": "main", "index": 0 } ] ] }, "Scrape Insolvency Register": { "main": [ [ { "node": "Detect Insolvency Signals", "type": "main", "index": 0 } ], [ { "node": "Log Scraping Error", "type": "main", "index": 0 } ] ] }, "Apply Confidence Guardrails": { "main": [ [ { "node": "Generate Business Risk Decisions", "type": "main", "index": 0 } ] ] }, "Apply Probability Weighting": { "main": [ [ { "node": "Apply Confidence Guardrails", "type": "main", "index": 0 } ] ] }, "Validate AI Distress Output": { "ai_outputParser": [ [ { "node": "AI Financial Distress Classifier", "type": "ai_outputParser", "index": 0 } ] ] }, "Detect News Distress Signals": { "main": [ [ { "node": "Merge All Distress Signals", "type": "main", "index": 2 } ] ] }, "Business Risk Decision Engine": { "ai_languageModel": [ [ { "node": "Generate Business Risk Decisions", "type": "ai_languageModel", "index": 0 } ] ] }, "Financial Distress Classifier": { "ai_languageModel": [ [ { "node": "AI Financial Distress Classifier", "type": "ai_languageModel", "index": 0 } ] ] }, "Set Company & Risk Parameters": { "main": [ [ { "node": "Validate Company Input", "type": "main", "index": 0 } ] ] }, "Categorize & Normalize Signals": { "main": [ [ { "node": "Prepare Signals for AI Analysis", "type": "main", "index": 0 } ] ] }, "Detect Filing Distress Signals": { "main": [ [ { "node": "Merge All Distress Signals", "type": "main", "index": 0 } ] ] }, "Prepare Signals for AI Analysis": { "main": [ [ { "node": "AI Financial Distress Classifier", "type": "main", "index": 0 } ] ] }, "AI Financial Distress Classifier": { "main": [ [ { "node": "Apply Probability Weighting", "type": "main", "index": 0 } ] ] }, "Generate Business Risk Decisions": { "main": [ [ { "node": "Is High Supplier Risk?", "type": "main", "index": 0 }, { "node": "Log Onboarding Decision", "type": "main", "index": 0 }, { "node": "Log Portfolio Exposure Status", "type": "main", "index": 0 } ] ] }, "Validate Business Decision Output": { "ai_outputParser": [ [ { "node": "Generate Business Risk Decisions", "type": "ai_outputParser", "index": 0 } ] ] } } }