Financial spreading still feels like a black box in lending workflows. How are teams fixing this?

[jakemiller98]

Financial spreading still feels like a black box in lending workflows. How are teams fixing this?

In our credit process, financial spreading is supposed to be a standardized step. In practice, every analyst has their own way of normalizing statements, adjusting line items, and interpreting ratios. Over time, this creates inconsistencies in risk assessment.

Some challenges we face regularly:

• Different statement formats across borrowers and industries
  
  
• Manual re-keying errors when moving data into spreading templates
  
  
• Time lost normalizing non-standard financials
  
  
• Difficulty comparing spreads done by different analysts
  

We recently started exploring AI-driven financial spreading software for lenders to reduce manual data entry and standardize how financials are converted into credit-ready formats. The biggest improvement so far is consistency, not just speed. Analysts spend less time cleaning data and more time actually interpreting it.

Would love to hear from others:

• How standardized is your spreading process across teams?
  
  
• Do you allow analysts to override automated spreads? If yes, how do you control it?
  
  
• Has automation improved consistency in credit decisions, or just throughput?