Case Study · Finance Automation
How PTAS AI combines document intelligence and finance automation to support reconciliation, exception handling and controlled financial workflows.
Case study 03 · The challenge
The information needed to reconcile an account is spread across bank statements, the ledger, invoices and the vendor master. Comparing them by hand is slow, and it is slowest on the lines that matter most. This case study follows one statement from arrival to a proved book-to-bank position.
Today
The bank rec is weeks behind
Statements are downloaded at month end and matched line by line in a spreadsheet by the one person who knows the accounts. Everything else they own waits while they do it.
Today
A credit nobody can place
A customer pays two invoices in one transfer, with a narration that names neither clearly. Matched on amount alone it finds nothing, so it goes to suspense and stays there.
Today
The statement is retyped first
PDF statements from banks without a feed are keyed or copied into a sheet before matching can start. A dropped line shows up only when the closing balance fails to agree, if anyone checks.
Underneath
Four sources, no common key
The statement, the ledger, the invoices and the vendor master each hold part of the answer. The narration is the only thread between them, and nobody wrote it to be read by a machine.
Underneath
Breaks with no owner and no age
An unmatched item from last quarter sits in the same list as this morning's. Nothing escalates, so the oldest breaks are the least likely to be looked at.
Underneath
Adjustments without evidence
A write-off or a reclassification is posted with a journal narration and no link to the statement line or the approval. The auditor asks, and someone reconstructs it from email.
The PTAS AI approach
DocPro understands documents. FinSuite executes finance workflows. Here DocPro turns statements into proved transaction lines, and FinSuite matches them to the ledger, explains what it can and routes the rest to a person.
DocPro's Bank Statement Agent reads each statement, whether PDF, scan or export, into transaction lines: value date, narration, reference or UTR, debit, credit and running balance. It proves the extraction by checking that the opening balance plus every line equals the closing balance, page by page. CSV, MT940 files and bank feeds enter the same structure.
A statement becomes lines you can trust
FinSuite matches each line against what the ledger expects: payment runs, customer receipts, open bills and invoices. It uses amount, date window, UTR, counterparty and narration together, so one transfer can settle several invoices. Your business rules set the tolerances, the date windows and the patterns that count as explained.
Matched on evidence, amount included
Matched lines clear with the rule that matched them stored on the line. Known patterns such as bank charges and interest are explained and booked to the account you name. Everything else goes to the break list with a likely cause, an owner and an age. Adjustments post with the reason and the approval attached.
Clear, explain or hold
The book-to-bank position is proved every time the reconciliation runs, with the statement, the matches and the adjustments attached. By close, the reconciliation has already been done.
Done before the close starts
The figure is one account's daily run once both products have done their part. Most lines clear by rule; three go to the break list with a cause. The counts and amounts are illustrative.
One account, one day's statement · Illustrative example
Illustrative data. A run is finished when every line on the break list has an owner, not when the matching stops.
The balance is the checksum
A statement whose lines do not sum to its closing balance is reported incomplete and never matched.
One to many, many to one
Batch payments and part payments matched, with the rule that matched them stated.
Breaks age
The oldest open item sits at the top of the list, with an owner.
The workflow
Two paths leave the business rules at step six. Lines that match or explain themselves clear at step seven. Lines that do not go to a person at step eight, with the cause stated. Both paths end in the same ledger and the same audit trail.
Bank statement
DocPro
Transaction lines
Balance proof
FinSuite matching
Business rules
Match: cleared
Exception: human review
Ledger posting
Audit
DocPro reads → FinSuite matches → Your ledger holds the proved position
How the two products divide the workStep by step
DocPro owns the first four steps. FinSuite owns everything from matching to the trail. Your people own step eight, and only the lines no rule could settle reach them.
Step four, the balance proof. If opening balance plus every line read does not equal the closing balance, nothing downstream starts. The amounts are illustrative.
Statement page 3 of 7 · Illustrative example
When that sum does not hold, the extraction is reported as incomplete rather than returned looking clean. It is usually a page that never arrived.
Step five, on a line that defeats a spreadsheet. One credit settles two invoices, and the evidence that matched it travels with the line. The values are illustrative.
One statement line, two invoices · Illustrative example
Illustrative data. Matching on amount alone finds nothing here, because no single open item equals ₹ 2,36,000.
Human review
Review is a control, not a failure state. A person sees a break no rule could settle, already separated from the ones that explained themselves, with a likely cause and an age.
Break list — 5 open on this account · Illustrative example
Ageing is what stops the old breaks hiding behind this month's new ones. Three explain themselves; two do not.
Three of the five items explained themselves; two need a person, oldest first. The reviewer sees the statement line and the candidates the matcher rejected, with the reason for each. An adjustment above your limit needs a second approver. The amounts are illustrative, and the human-in-the-loop guide covers keeping a queue like this short.
Products used
DocPro provides the intelligence layer. FinSuite provides the finance workflow layer. FinSuite can also take statements that arrive already structured, as CSV, MT940 or a feed; DocPro is what makes the PDF and scanned ones usable.
Agentic Document Intelligence
Statement→Classify→Read→Prove→Hand over
DocPro owns the reading. Its Bank Statement Agent turns each statement into typed transaction lines, proves them against the running balance and hands them to FinSuite.
AI Finance Operations
Match→Explain→Hold→Post→Prove
FinSuite owns the reconciliation. It matches lines to the ledger under your rules, explains the known patterns, keeps the break list and posts adjustments with their evidence.
FinSuite writes to the ledger through one of four methods: native integration, API integration, file or flat-file integration, or custom integration. SAP, Oracle, Microsoft Dynamics, NetSuite, Tally and Zoho Books are planning examples; which method applies to your instance, and the scope of the mapping, is confirmed during assessment.
How postings and status flowControls
A reconciliation that runs itself also has to explain itself. Each control here is a step in the chain, and each leaves a record. The FinSuite security page has the detail.
Matching rules you can read
Date windows, tolerances and narration patterns are configuration with an owner. Every match traces to the rule that made it, and a rule change does not rewrite history.
A second person on adjustments
A write-off or reclassification above the limit you set needs an approver other than the person who proposed it. Both are recorded on the entry, with the reason.
A position you can reproduce
The statement image, every line, each match and each adjustment are kept, so the book-to-bank position for any past date can be shown again.
Data handling
Statements and account details under role-based access, account numbers masked where a role does not need them, retained for the period your policy sets. Cloud, private cloud or on-premise deployment where supported, with ISO/IEC 27001-aligned practices.
Where it applies
Any business with several bank accounts and narrations nobody standardised has this problem. It shows up first where volume is high and payment references are poor.
Manufacturing
Supplier payment runs and customer receipts across several banks.
ExploreRetail
Card and wallet settlements against store takings.
ExploreE-commerce
Marketplace and gateway payouts taken apart into orders and fees.
ExploreBanking & Financial Services
The institution's own operating accounts, under audit.
ExploreHealthcare
Supplier payments and receipts; finance paperwork only.
ExploreLogistics
Freight payments and customer receipts with references in the narration.
ExploreSupply Chain
Payments to many suppliers, part payments and advances.
ExploreTechnology
Subscription collections and refunds through payment gateways.
ExploreNext step
Pick the account with the most volume or the oldest break list. A month of its statements, the ledger extract for the same month and the break list as it stands today is the test worth running.
Assess your finance workflow
A short assessment of how statements, receipts and payments are reconciled today, scored, with the account we would start with.
See DocPro + FinSuite in action
A working session on your statements, your ledger extract and your matching rules, with both products running.
Read the solution view
Bank Reconciliation Automation as a workflow you can evaluate: what it does and how you would measure it.
Going live is typically four to twelve weeks for a single workflow, an indicative range that varies by document types, workflows, integrations and deployment. The number of banks, which of them offer feeds and how much history sits on the current break list all move it. The workflow on this page is representative; it is not presented as a customer deployment or an independently measured result.
FAQ
No. This case study describes a representative workflow built from DocPro and FinSuite. It is not presented as a customer deployment or an independently measured result, and the numbers in the figures are illustrative.
Less than you might expect. DocPro reads PDF and scanned statements into lines, with the running balance used as a check on the extraction. A feed arrives daily without anyone downloading anything, which helps, but the matching and the rules are the same whichever way the statement comes in.
It goes on the break list with a likely cause, an owner and an age. The reviewer matches it by hand, proposes an adjustment or chases someone, and whatever they do is recorded against the line. Because the list ages, an item from last quarter cannot hide behind this morning's.
Yes, and the reverse. A single transfer can be matched to several open invoices when the amounts and the narration support it, and several receipts can be matched to one invoice. A part payment leaves the remaining balance open against the original invoice.
Explained items such as bank charges post by rule to the account you specify. Write-offs and reclassifications are proposed from the break and post only once approved, by a second person above the limit you set. Every posting links back to its statement line.
Keep reading
Bank Reconciliation Automation
The solution this case study runs, as a workflow you can evaluate.
Read more →FinSuite Bank Reconciliation
The module that matches, explains and keeps the break list.
Read more →Case study 01: Document-to-Finance Automation
DocPro and FinSuite together, from invoice to payment status.
Read more →Case study 02: Intelligent Document Processing
DocPro on its own: a mixed intake turned into trusted data.
Read more →Next step
Tell us how many bank accounts you reconcile, how the statements arrive and how long the break list is. We will point to the account to start with and the rules it needs.
