Read lease applications and prepare credit checks

AI reads lease applications from vendors into the core system, then gathers registry details and credit bureau scores into a memo for the credit reviewer.

  • Leasing
  • Credit review
  • Operations & orders

The problem today

Vendor lease applications arrive by PDF or fax, in a different format from every vendor. Staff type them into the core system by hand and, for every review, look up registry details and credit bureau scores on separate sites. RPA with OCR helped, but staff now spend their time correcting what OCR read and fixing robots whenever a screen changes.

The workflow in Kitewell

  1. Add applications from the inbox folder to a batch sheetAutomatic
  2. AI reads the lessee, vendor, equipment, lease term, and monthly paymentAI judgment
  3. Collect registry details and the credit bureau score from each siteWeb
  4. Summarize points to check in a credit memo from the application and collected dataAI judgment
  5. The credit reviewer checks what was read and the memo, and approves registrationApproval
  6. Register the application in the core systemWeb

What AI does

Reads the needed fields from applications in each vendor's own format, quoting the part of the application each value came from. It compares the application with the registry details and score, and lists points to check, such as a mismatched address or representative.

Where people decide

The credit reviewer checks the memo and what was read before approving registration. Credit decisions stay with the reviewer, as today.

Features used

What a PoC checks

  • Whether the needed fields are read correctly from your main vendors' application formats
  • Whether registry and credit bureau services allow this retrieval under their terms of use
  • Whether the memo's content and format fit how your credit team works

Discuss a PoC for this work

We check whether this workflow runs on your own work and screens.