Docsumo Multi-Account Bank Statement Processing

Processing bank statements from clients with multiple accounts (checking, savings, credit cards) is standard practice for accounting firms. When these accounts appear in a single consolidated PDF, your processing tool needs to identify account boundaries, extract data separately, and maintain accuracy across all account types.

Docsumo offers multi-account processing capabilities through its auto-splitting and consolidated statement features. The platform can handle statements with multiple account types, but the approach requires upfront configuration and ongoing manual validation that creates workflow friction at scale.

For firms processing dozens of clients monthly, the difference between configurable splitting and automatic detection directly impacts throughput and error rates.

Docsumo's approach to multi-account processing combines two main features: auto-splitting and consolidated statement handling. Both require configuration before they work correctly.

Auto-Splitting Configuration

Docsumo's auto-split feature can divide documents based on four methods:

• Fixed Number: Split every N pages (requires you to know page counts per account in advance)
• Text Pattern: Split when specific text appears (requires you to identify and configure the separator text)
• QR Code: Split at QR code markers (requires banks to include QR codes, which most don't)
• Custom API: Build your own splitting logic (requires development resources)

Each method requires you to configure splitting criteria before processing. If your client's bank changes statement formatting, or you onboard clients from new banks, you need to reconfigure splitting rules.

Consolidated Statement Handling

When Docsumo processes consolidated statements with multiple account types, it extracts data for each account but generates separate error messages per account type. This means exceptions require manual review for each account in the statement.

The platform flags multi-account data for validation through custom workflows. This ensures accuracy but adds manual touchpoints that slow down batch processing operations.

The difference between configurable splitting and automatic detection becomes clear when processing client statements at scale. Consider a bookkeeping firm managing 50 clients, each with an average of 2.5 accounts (checking, savings, credit card).

Maintenance Burden

Configuration-based approaches also create ongoing maintenance work. When Wells Fargo updates their statement layout (which major banks do 2-3 times per year), you need to:

• 1.Identify which clients are affected by the format change
• 2.Update splitting configurations for the new format
• 3.Test configurations with sample statements
• 4.Reprocess any statements that failed with old configurations

With automatic detection, Zera AI adapts to format changes without intervention. The system processes new formats the same way it processed old ones.

This is particularly valuable for firms handling diverse client portfolios where clients bank with dozens of different institutions across regional banks, credit unions, and national chains.