These turbulent times make it challenging to manage a commercial loan portfolio while maintaining customer relationships. Staying connected with your customers' challenges and identifying early signs of defaults can help you manage risk across your portfolio 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. Recent advancements in AI have enabled sentiment analysis, key phrase extraction and trending to deliver actionable data, converting qualitative information into quantifiable data for decision-making. Thematic trending and market-level data can also be used to benchmark risk when limited company-specific data is available.
In addition to a general discussion, this white paper highlights the use of unstructured data and sentiment analysis to benchmark risk in two real-world case studies:
- Case 1: Pier 1 Imports
- Case 2: J. Crew
To learn more about how Bitvore Cellenus uses sentiment analysis to help organizations eliminate the time-consuming manual efforts associated with reviewing unstructured data sources to identify emerging risk and opportunity, download the white paper below.
