B2B Lending

Step 1: Upload the Source Document

• Upload the company's pitch deck, business plan, or loan application into Data Agent

Step 2: Extract Forecasted Metrics

• Create a Simple Columns to extract: Projected Revenue, Business Credit Score, Requested Loan Amount from the uploaded file.

• Create a Smart Column to analyze and manipulate extracted data:

  Based on available information in the document calculate a Financial Health Score on a scale of 0-100, where higher scores indicate stronger financial standing.

Step 3: Research Additional Insights Online

• Create a Smart Column with prompt:

  Summarize the key business risks mentioned in the company's public filings or trusted financial news sources.

Step 4: Compare Internal Forecasts to Public Data

• Add a Web Search Column with prompt

  Compare information provided as a source document to company's public fillings on SEC and if any discrepancies found output result in a format: "X Discrepancies", if no discrepancies found write "No Discrepancies" If unable to check write "Manual Check Needed"

  
  

• Optionally, apply conditional formatting to flag major differences.

Step 5: Ask Follow-Up Questions Using Table Chat

• Use the built-in AI chat to query the dataset for deeper insights.

• Example Follow-up Questions:

  Which companies have best financial health?

  List businesses with the highest reported liabilities compared to assets.

  Summarize companies that have highest business associated risks in next 12-24 months?

Best Practices

• Target official sources (SEC.gov, Yahoo Finance, Bloomberg) in web search prompts for highest reliability.

• Refine prompts if data returned is inconsistent or incomplete.

• Keep uploaded documents clean and structured to help extraction accuracy.