How 26AS TDS reconciliation works
CleverBalance follows a structured process to match 26AS and books, starting from data cleaning to rule-based matching and AI-assisted analysis. Designed to handle real-world data where names differ, invoices do not align perfectly, and entries are spread across periods.
Upload 26AS and books
Clean and prepare data
Normalize deductor names
Run system matching rules
Analyze complex cases using AI
Review matched and unmatched results
Download Excel report
From upload to final output, in a few steps
The system handles the heavy lifting, you focus only on exceptions.
Upload 26AS and books
Clean and prepare data
Normalize deductor names
Run system matching rules
Analyze complex cases using AI
Review matched and unmatched results
Download Excel report
Step 1 - Upload 26AS and books data
Start by uploading your 26AS TDS statement and books of account statement. These can be exported from your existing systems or maintained working files.
Upload 26AS
Bring in the source TDS statement.
Upload books
Add your books data to continue the workflow.
Step 2 - Data is cleaned and standardized
Once files are uploaded, CleverBalance prepares the data so both sides can be compared properly.
Cleaning raw values
Aligning formats
Preparing fields required for reconciliation
Removing inconsistencies that block matching
Raw files do not need to be perfect, the system prepares them.
Step 3 - Deductor names are normalized
The same deductor often appears differently in 26AS and books. CleverBalance standardizes these variations so they can be matched correctly.
Without this step, many valid matches would remain unmatched.
Better name alignment leads to better matching accuracy.
Step 4 - System matches records using structured logic
After preparation, CleverBalance runs a rule-based engine to reconcile transactions using deductor name, invoice date, and invoice amount.
Exact matches first
Same amount, same date or within expected period, one-to-one matching.
Period-based matching
Same month or financial year to handle timing differences between 26AS and books.
Grouped matching
One-to-many or many-to-many logic when entries are split or combined.
Contra handling
Identifies reversals or adjustments and matches positive and negative entries.
The system resolves most cases using structured and explainable logic.
Step 5 - AI helps with complex cases
After rule-based matching, some entries may still remain open. CleverBalance uses AI to analyze these cases and identify patterns that are harder to detect using fixed rules.
AI does not force matches.
If confidence is low, entries remain unmatched. This keeps reconciliation accurate and audit-friendly.
Step 6 - Clear matched and unmatched results
After system and AI matching, the final output is generated in two clear buckets.
Matched
Fully matched between 26AS and books.
Unmatched
Present on one side but not found on the other.
Step 7 - Review in UI or download Excel
In the product
- Review matched transactions
- Review unmatched transactions
- Validate results quickly
In Excel
- Download full reconciliation output
- Share with team or clients
- Use for audit or working papers
Your reconciliation stays structured, reviewable, and shareable.
Designed for messy, real-world data
CleverBalance is built to handle real reconciliation challenges.
You do not need perfectly structured data to get meaningful results.
See how it works on real scenarios
Explore industry-specific examples of 26AS TDS reconciliation.
Try 26AS reconciliation with your own data
Upload your 26AS and books, let CleverBalance handle the matching, and review only what actually needs attention.