Evidence-Supported Credit Risk Report Generation Using News-Centric Financial Knowledge Graphs
Financial markets evolve in response to real-world events reported in news, yet these drivers often remain implicit in text. To better explain market dynamics, event-market relations must be explicitly modeled through factual, company-centric, and environment-aware knowledge graphs. We present FinKG-News, a framework that automatically constructs such graphs by extracting news events as anchors linked to companies. Using FinKG-News as grounded evidence that integrates events, news, and company data, we develop an in-context learning architecture for credit risk report generation across three c
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- LinkedLinked via arxiv author · 85%Rocio Jimenez-Villen →
“Evidence-Supported Credit Risk Report Generation Using News-Centric Financial Knowledge Graphs”
- LinkedLinked via arxiv author · 85%Ziwei Xu →
“Evidence-Supported Credit Risk Report Generation Using News-Centric Financial Knowledge Graphs”
- LinkedLinked via arxiv author · 85%Ying Chen →
“Evidence-Supported Credit Risk Report Generation Using News-Centric Financial Knowledge Graphs”
- LinkedLinked via arxiv author · 85%Oscar Araque →
“Evidence-Supported Credit Risk Report Generation Using News-Centric Financial Knowledge Graphs”
- LinkedLinked via arxiv author · 85%Ryutaro Ichise →
“Evidence-Supported Credit Risk Report Generation Using News-Centric Financial Knowledge Graphs”