Affirm's primary defense against credit losses is its proprietary underwriting technology. This creates a continuous need to invest in data science talent, data infrastructure, and machine learning platforms to enhance model accuracy and performance.
Filing excerpt
To manage this risk, we utilize our proprietary underwriting models to make lending decisions, score, and price loans in a manner that we believe is reflective of the credit risk.
What this signalsFilings often name leadership changes, deals and spending plans.
Technologies
sec-10qaiInvestmentGet every 10-Q signal for Affirm and the companies you sell to, in the tools you already use.
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This page shows a preview. The full sec-10q 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/e9dcb8a2-39ab-47b8-887f-3aca788d6f11 returns this record as JSON. POST /v1/companies/enrich returns every signal for affirm.com.
{
"signal_id": "e9dcb8a2-39ab-47b8-887f-3aca788d6f11",
"signal_type": "sec-10q",
"signal_subtype": "aiInvestment",
"detected_at": "2026-02-10T08:23:30.729+00:00",
"company": {
"name": "Affirm",
"domain": "affirm.com"
},
"data": {
"detail": "Affirm's primary defense against credit losses is its proprietary underwriting technology. This creates a continuous need to invest in data science talent, data infrastructure, and machine learning platforms to enhance model accuracy and performance.",
"metrics": {
"timeframe": "current_quarter"
},
"summary": "Relies on proprietary underwriting models to manage credit risk across its loan portfolio.",
"excerpts": "To manage this risk, we utilize our proprietary underwriting models to make lending decisions, score, and price loans in a manner that we believe is reflective of the credit risk.",
"relevance": 0.7,
"sentiment": "neutral",
"confidence": "high",
"source_url": "https://www.sec.gov/Archives/edgar/data/1820953/000162828026005855/afrm-20251231.htm",
"filing_date": "2026-02-05",
"filing_year": 2026,
"fiscal_year": 0,
"fiscal_year_end": "12/31",
"sales_relevance": "Target for AI vendors",
"signal_category": "technology",
"technologies_mentioned": [
"proprietary underwriting models"
]
}
}
curl https://signals.autobound.ai/v1/signals/e9dcb8a2-39ab-47b8-887f-3aca788d6f11 \
-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.