The company's business model relies on sophisticated machine learning for underwriting and fraud detection, creating a continuous need for advanced MLOps tools and engineering talent. They explicitly state their ability to use AI-powered solutions is a key factor for future success.
Filing excerpt
We prioritize building our own technology and investing in engineering talent, as we believe these are enduring competitive advantages that are difficult to replicate.
What this signalsFilings often name leadership changes, deals and spending plans.
Technologies
sec-10kaiInvestmentGet every 10-K signal for Affirm and the companies you sell to, in the tools you already use.
Connect Autobound to Claude, Claude Code or Cursor with MCP. Then ask: “What changed at Affirm this week?”
The Signal API returns 10-K signals for any list of companies as JSON, for your CRM, warehouse or app.
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This page shows a preview. The full sec-10k record in the Signal API and MCP can also have these 8 fields. Some fields are empty for some signals.
Company
linkedin_urlValue in the APIindustriesValue in the APIemployee_count_lowValue in the APIemployee_count_highValue in the APIrevenueValue in the APIdescriptionValue in the APISignal
signal_nameValue in the APIassociationValue in the APIGET /v1/signals/01e9ae8c-9fd9-427e-8b02-7abd847d163e returns this record as JSON. POST /v1/companies/enrich returns every signal for affirm.com.
{
"signal_id": "01e9ae8c-9fd9-427e-8b02-7abd847d163e",
"signal_type": "sec-10k",
"signal_subtype": "aiInvestment",
"detected_at": "2026-09-01T07:03:20.044+00:00",
"company": {
"name": "Affirm",
"domain": "affirm.com"
},
"data": {
"detail": "The company's business model relies on sophisticated machine learning for underwriting and fraud detection, creating a continuous need for advanced MLOps tools and engineering talent. They explicitly state their ability to use AI-powered solutions is a key factor for future success.",
"metrics": {
"timeframe": "current_year"
},
"summary": "Affirm prioritizes investment in proprietary AI and machine learning for risk modeling.",
"excerpts": "We prioritize building our own technology and investing in engineering talent, as we believe these are enduring competitive advantages that are difficult to replicate.",
"relevance": 0.8,
"sentiment": "positive",
"confidence": "high",
"source_url": "https://www.sec.gov/Archives/edgar/data/1820953/000162828026059279/afrm-20260630.htm",
"filing_date": "2026-08-27",
"filing_year": 2026,
"fiscal_year_end": "06/30",
"sales_relevance": "Target for AI vendors",
"signal_category": "technology",
"technologies_mentioned": [
"machine learning",
"artificial intelligence",
"AI"
]
}
}
curl https://signals.autobound.ai/v1/signals/01e9ae8c-9fd9-427e-8b02-7abd847d163e \
-H "X-API-KEY: $AUTOBOUND_API_KEY"curl -X POST https://signals.autobound.ai/v1/companies/enrich \
-H "X-API-KEY: $AUTOBOUND_API_KEY" \
-H "Content-Type: application/json" \
-d '{"domain":"affirm.com","limit":20}'Long text fields are shortened on this page.
Looking up one signal by its id is free. Enrich costs 2 credits per signal returned; a call with no results is free.