Leveraging Sentiment as a Leading Indicator of Loan Defaults

American Banker Webinar


This essential discussion for Commercial/Corporate banking professionals covered how AI and Sentiment Analysis can be embedded into your daily workflows for credit monitoring and credit underwriting to reduce default risk. Bitvore's Mirella Reznic, Head of Product and Innovation, discussed navigating situations when limited data is available and how you can use thematic trending and market-level data to benchmark risk.

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    Discover how risk factors and sentiment can provide a view of a company’s prognosis.

In the Presentation

These turbulent times make it challenging to manage a loan book while maintaining the overall customer relationship. Staying connected with your customer’s challenges and identifying early signs of loan defaults can help you manage risk across your loan book more effectively. Mining unstructured data sources (e.g., news, press releases, SEC filings/proxy statements, earnings call transcripts, etc.) for leading indicators of risk is a powerful way of staying connected with your customers.

The presentation covers how recent advancements in AI have enabled sentiment analysis, key phrase extraction and trending to deliver actionable data, converting qualitative information into quantifiable data.

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Presentation Highlights:

  • How unstructured data can help your teams stay connected with emerging risks across your loan book

  • Sentiment analysis of unstructured data can be an early warning indicator of emerging risks

  • Examples of how risk factors and sentiment can provide a view of a company’s prognosis

  • How Industry benchmarking can provide context and supplement your data sources

  • COVID-19 trends, predictions and recovery

Make better decisions, faster.