---
title: Artificial Intelligence and Firm Financing
url: https://www.ml-quant.com/papers/ssrn/7626298/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-10-23
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 7626298
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7626298
featured: 2026-10-23
citations: unknown
topic: ML & AI Methods
---


# Artificial Intelligence and Firm Financing

As firms adopt AI, they hold less cash, shift from revolving to term credit, pay higher spreads, and rely more on non-bank lenders while expanding investment and employment.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7626298
- Identifier: SSRN 7626298
- Released: 2026-10-19
- First featured: Quant Letter No. 136 (2026-10-23): https://www.ml-quant.com/issues/2026-10-23/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods
- Authors: Suleyman Gozen

## Related

- [The AI Productivity Index (APEX)](https://www.ml-quant.com/papers/arxiv/2509.25721/): The AI Productivity Index (APEX) is a new benchmark for evaluating the economic value of AI models in sectors like investment banking, consulting, law, and medical care.
- [Artificial Intelligence and Relationship Lending](https://www.ml-quant.com/papers/ssrn/5241807/): The research explores the impact of AI adoption in credit scoring and relationship lending by banks, suggesting that AI investments can help banks manage the effects of relationship lending on credit supply and decisions.
- [My Advisor, Her AI and Me: Evidence from a Field Experiment on Human-AI Collaboration and Investment Decisions](https://www.ml-quant.com/papers/arxiv/2506.03707/): A study with a European bank reveals customers are more likely to follow investment advice from a human-AI collaboration than pure AI, indicating human involvement can improve consumer outcomes.
- [Explainable Machine Learning for Basel and IFRS 9 Credit Risk: A Placebo-Controlled Test of Narrative Features](https://www.ml-quant.com/papers/ssrn/7622180/): A placebo test reveals that features like central bank tone can raise credit model accuracy merely by indicating when loans were made, not by predicting defaults.
- [Dynamic Graph Neural Networks for Real Time Systemic Risk Surveillance: An Explainable AI Framework for Financial Stability](https://www.ml-quant.com/papers/ssrn/7522878/): The research proposes a temporal graph neural network with explainability tools for real-time systemic risk surveillance, achieving early warning signals 3-4 quarters ahead of financial distress on bank data.
- [AI Fraud Detection in Financial Crimes](https://www.ml-quant.com/papers/ssrn/4938417/): The advent of digital banking has escalated risks like fraud and identity theft, prompting financial institutions to adopt Machine Learning and AI for efficient fraud detection.