The Scenario
Your underwriting team just closed intake on a new batch — 120 small business loan applicants, names and addresses captured in the 'Applicants' sheet of an Excel workbook, columns A and B. The processor who was handling manual KYB verification is out this week, and legal has flagged that you can't advance any file without a verified EIN and confirmed legal entity name.
The bad version:
- Open Enigma's search portal, type each business name and address, read the matched legal entity name and EIN, and type them into columns C and D by hand — 120 times.
- When the match is ambiguous — two "Oak Street Bakery LLC" entries in different states — stop everything to figure out which one is the actual applicant before moving on.
- Finish the batch three days later and discover that twelve rows had trailing spaces in the address field, so those twelve returned no match and now need to be re-run individually.
Your loan pipeline can't sit for three days while someone transcribes API results one row at a time. The lenders are already asking for status.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent built into your Excel workbook. It reads the 'Applicants' worksheet, understands what's in columns A and B, and through its Enigma integration it can run the match API against every row and write results back — without you configuring a single field mapping.
For each row in my Excel 'KYB Queue' table, retrieve the Enigma ID and TIN for each match, and fill columns C and D.
What You Get
- Column C: verified legal entity name from Enigma's business match API
- Column D: EIN (Employer Identification Number) for each matched business
- Column E: state of incorporation
- Rows where no match was found get a clear "no match" marker in column C so you can see exactly which ones need manual follow-up
What If the Data Is Not Quite Ready
The address format is inconsistent across rows
Some applicants entered "123 Main St", others wrote "123 Main Street, Suite 4", and a few left the city out entirely.
Match each business in my Excel 'Applicants' worksheet against Enigma using the name in column A and address in column B. Where the address is missing a city, check whether column F has a city value and include it in the match call. Write matched entity name, EIN, and state into columns C, D, and E.
The business names have legal suffixes stripped out
Applicants submitted names like "Oak Street Bakery" when the registered entity is "Oak Street Bakery LLC."
Run Enigma business match for every row in the 'Applicants' worksheet. For each name in column A, try the match as-is first; if no match is returned, retry with common legal suffixes (LLC, Inc, Corp) appended. Write the best-matched legal name, EIN, and match confidence score into columns C, D, and F.
Only unprocessed rows should be re-run
Columns C and D already have data for some rows from a previous pass.
For all rows in my Excel 'Applicants' worksheet where column C is blank, match the business name in column A and address in column B against Enigma and write the legal entity name, EIN, and state of incorporation into columns C, D, and E. Skip any row that already has a value in column C.
Clean names, match, flag issues, and mark status in one pass
For every row in the 'Applicants' worksheet: trim whitespace from column A and B, run the Enigma business match, write the verified legal name, EIN, and state into columns C, D, and E, mark column F as 'matched' or 'no match', and if match confidence is below 80% flag column G as 'review'.
The pattern: address formatting, matching, writing results, and flagging edge cases all happen in the same instruction — nothing has to wait for a separate cleanup step.
Try It
Get the 7-day free trial of SheetXAI and open any Excel workbook with a column of business names and addresses, then ask it to run Enigma identity enrichment across the batch. For KYB verification on the same dataset, see the batch KYB screening article or return to the Enigma integration overview.