{
  "id": 6682525,
  "title": "Making Alternative Data Work: Context-Augmented LLMs for Financial Forecasting",
  "url": "https://urgent.news/2026/09/10/making-alternative-data-work-context-augmented-llms-for-financial",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-10T14:27:25.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.11607v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "When forecasting a firm's future financial performance, alternative data - data collected from non-traditional sources such as consumer transactions, web traffic, and prediction markets - can provide timely signals about firms' operating activities and broader market conditions. These signals may reveal information that is not captured by traditional public sources and can therefore provide…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}