Standardize borrower data, normalize addresses for HMDA compliance, and classify entities across your loan pipeline — all from a simple CSV upload. Processing that used to take days now takes minutes.
$1.2M
Average HMDA-related fine for data quality violations
CFPB Enforcement Actions, 2023
34%
Of loan files contain address format inconsistencies
MBA Data Quality Survey
12 min
Average time to process 5,000 borrower records with BackOffice Scripts
Home Mortgage Disclosure Act reporting requires standardized addresses, correct entity types, and clean borrower names. Non-compliant data leads to regulatory scrutiny and potential fines.
Borrower names come in dozens of formats — joint applications, trusts, LLCs. Each needs to be parsed and classified correctly before entering your LOS.
Accurate addresses determine rate territories, flood zones, and title search areas. Non-standard address formats cause misquotes and processing delays.
The same borrower appearing with slight name variations across multiple files creates confusion in pipeline tracking and CRM systems.
HMDA Loan Application Register filing requires standardized addresses, correct entity classifications, and clean borrower data. BackOffice Scripts automates the data normalization that used to take weeks.
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.
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 · Max 8,500 rows
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 · Max 8,500 rows
Classify records into granular entity types: Individual, Joint, Trust, Estate, LLC, Corporation, Partnership, Government, Nonprofit. Critical for insurance underwriting and loan processing.
1 credit/record · Max 8,500 rows
“HMDA season used to be a nightmare. We'd spend weeks standardizing address data. BackOffice Scripts cut that to hours.”
Compliance Director
Mid-size mortgage lender, 2,000+ loans/year
Yes. It normalizes addresses to USPS standard format and splits them into structured fields (street, city, state, ZIP) — exactly what HMDA LAR filing requires.
Yes. The Name Parser detects joint names like 'John and Mary Smith' or 'Smith, John & Jane' and splits them into individual borrower records with first/middle/last for each person.
Upload your CSV with a name column. The Entity Type Classifier will identify each record as Individual, Joint, Trust, LLC, Corporation, Partnership, Government, or Nonprofit — with a confidence score.
Yes. We process data in isolated environments, encrypt everything in transit and at rest, auto-purge files after your retention period, and maintain full audit logs. Our infrastructure (Vercel + Supabase) is SOC 2 Type II certified.
Start with 100 free records. No credit card required.