Loan files arrive from dozens of sources with inconsistent formats. BackOffice Scripts normalizes borrower names, standardizes addresses, and parses joint applications — so your LOS data is clean from day one.
Mortgage loan files contain borrower data from multiple sources — applications, credit reports, title companies, and appraisals. Each source uses different name formats, address conventions, and entity classifications. According to the Mortgage Bankers Association, 34% of loan files contain address format inconsistencies that must be resolved before closing. Inconsistent data slows underwriting, causes title search errors, and complicates compliance reporting.
34%
Of loan files have address inconsistencies
MBA Data Quality Survey
4-6 hrs
Average time spent manually standardizing a batch of 500 loan files
$250-500
Cost per loan of data quality remediation in the pipeline
Pull borrower records from your LOS or pipeline tracker as a CSV with name and address columns.
Normalize all property and mailing addresses to USPS standard format.
Parse borrower names into structured fields, detect co-borrowers, and standardize formatting.
Load the standardized CSV back into your LOS with consistent, clean data across all records.
Normalize addresses to USPS standard format, split into structured fields (street, city, state, zip), and flag invalid or incomplete addresses. Essential for HMDA reporting and rate territory assignment.
2 credits/record
Split full names into first/middle/last/suffix, handle joint names ("John and Mary Smith"), normalize casing, and flag suspicious or fake entries. Built for lending and insurance records.
1 credit/record
Yes. The Name Parser detects joint/co-borrower names and splits them into separate fields for primary and secondary borrowers.
USPS Publication 28 standard format with structured fields: street, city, state, ZIP. Unit/apartment numbers are properly parsed.
A typical batch of 5,000 loan records processes in about 12 minutes. Results include your original data plus new standardized columns.
Start with 100 free records. No credit card required.