---
title: A SPOT in the dark: using AI to assess financial stability risks
url: https://www.ml-quant.com/papers/repec/ecb-ecbwps-20263262/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-10-02
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:ecb:ecbwps:20263262
source_url: https://econpapers.repec.org/RePEc:ecb:ecbwps:20263262
featured: 2026-10-02
citations: unknown
topic: ML & AI Methods
---


# A SPOT in the dark: using AI to assess financial stability risks

Large Language Models extract signals about potential trigger events from financial news, improving forward-looking estimates of downside risks and helping monitor financial stability threats ahead of major events.

- Source: https://econpapers.repec.org/RePEc:ecb:ecbwps:20263262
- Identifier: RePEc:ecb:ecbwps:20263262
- Released: 2026-09-23
- First featured: Quant Letter No. 133 (2026-10-02): https://www.ml-quant.com/issues/2026-10-02/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods
- Authors: Kellner, Domenic, Lang, Jan Hannes, Rusnák, Marek, Nagy, Lukas Joseph

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