Let's discuss how you can leverage AI to enhance your risk modeling process, particularly if you're in the alternative finance industry, such as revenue-based financing or merchant cash advance.
We'll be using ChatGPT 4, the paid version of ChatGPT, which I highly recommend for both you and your employees. If you need guidance on getting started, check out this video.
As the founder of Cobalt Intelligence, our mission is to help alternative finance professionals like you utilize AI, automation, and data to mitigate risk when lending, dealing with fraud, or managing working capital.
In this example, I've generated a sample dataset using ChatGPT, consisting of businesses, invoice amounts, payment dates, and SOS data indicating whether the business is in good standing. A "1" in the SOS data indicates a red flag, while a "0" means everything is in order. Additionally, credit scores below 300 trigger a high-risk indicator.
The dataset also includes a default indicator, showing whether the loan defaulted. Although the default rate in this sample dataset is unrealistically high at around 50%, it serves to illustrate the concept. I encourage you to analyze your own historical loan data, marking which loans defaulted and when, to identify potential patterns.
By feeding this dataset to our FREE Credit Risk AI Tool and asking it to spot patterns that could help reduce defaults, we can leverage AI to improve our risk assessment process. For instance, the analysis might reveal that businesses from a specific location with a particular credit score range have a higher likelihood of defaulting, allowing you to adjust your lending criteria accordingly.
The key takeaway is that you can use ChatGPT as your data analyst, processing your historical data to identify correlations and patterns that can inform your future lending decisions.
If you're interested in accessing this type of background data or automating your risk assessment process, feel free to reach out to us at Cobalt Intelligence.