Regulatory filings demand clean, standardized data. BackOffice Scripts automates entity classification, address normalization, and contact validation — with the audit trails and security controls compliance teams require.
78%
Of financial institutions cite data quality as their top compliance challenge
ABA Compliance Survey, 2024
$4.2M
Average cost of a compliance data quality remediation project
Deloitte Regulatory Cost Study
100%
Of actions logged with timestamps, user IDs, and file details in BackOffice Scripts
HMDA, CRA, ECOA, and state insurance filings all require specific data formats. Misclassified entities or non-standard addresses trigger examiner flags and potential enforcement actions.
Examiners want to see how data was processed and by whom. Manual Excel work leaves no verifiable audit trail.
Third-party data often arrives with quality issues. Compliance teams need systematic validation, not spot-check reviews.
Different analysts classify entities differently. Without automated standards, the same trust might be coded as 'Individual' by one person and 'Trust' by another.
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.
Dirty CRM data leads to failed campaigns, wasted sales time, and inaccurate reporting. BackOffice Scripts validates contacts, classifies entities, and scores data quality — so your team works with data they can trust.
Misclassified entities lead to incorrect premium calculations, wrong policy forms, and compliance violations. BackOffice Scripts uses AI to classify every record consistently — Individual, Joint, Trust, LLC, Corp, and more.
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
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
Classify names as personal (individual) or business entities. Upload a CSV with a name column and get back a true/false classification for each row.
1 credit/record · Max 8,500 rows
Validate phone numbers and email addresses, detect disposable emails, flag invalid formats, and score overall contact quality. Stop wasting time on bad contact data.
1 credit/record · Max 8,500 rows
“Having a consistent, automated classification pipeline with full audit logs transformed our HMDA prep process.”
Chief Compliance Officer
Community bank, $2B in assets
Yes. Every file upload, script run, and data deletion is logged with timestamps, user IDs, and details. You can view and export audit logs from the Settings page.
Automated classification applies the same rules to every record, eliminating analyst-to-analyst inconsistency. The Entity Type Classifier uses the same model for every batch, producing repeatable, defensible results.
Yes. You can configure retention to 1, 7, or 30 days. Files are automatically and permanently deleted after your chosen period. You can also delete all data immediately at any time.
Our infrastructure runs on Vercel (SOC 2 Type II) and Supabase (SOC 2 Type II). All data is encrypted with AES-256 at rest and TLS in transit. We implement row-level security isolation and never use customer data for AI training.
Start with 100 free records. No credit card required.