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Profit Leakage Detection

Find the Profit That Quietly Leaks Out of Your Business

Work that went out and never got billed. An old rate that stayed in the system after a price revision. Freight paid above contract. None of it is theft and none of it shows as a line in the accounts. AI reads every document and shows you what it is costing.

50+ ERP and software projects. Zero failed projects since 2021.

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Leakage found, last 12 months
Ranked
₹1.42 Cr
Recoverable value identified
Across 640 documents reviewed
Unbilled deliveries₹48 lakhGoods dispatched with no matching invoice raised.
Old price on live orders₹36 lakhRate revision never applied to 112 order lines.
Freight above contract₹31 lakhBilled rate higher than the agreed slab on 208 trips.
Unclaimed supplier credits₹27 lakhRejection and rebate credits due but never claimed.
Each case links to the exact order, invoice or bill
Illustrative figures
100%
Of documents checked, not a sample
8
Leakage types looked for
12 mo
Typical review period
Ranked
By recoverable value
Why It Matters

Your accounts show what you earned, not what you lost on the way

Leakage hides inside normal transactions. No single case is big enough to notice, and every one of them looks like an ordinary entry.

Small and Repeated

One wrong rate on a regular order runs all year

A rate that was never updated after a revision does not trigger anything. It just repeats quietly on every order for that customer until someone happens to look. The AI compares each line against the price that should have applied and shows you the gap in money.

  • Every order line checked against the approved rate.
  • The cumulative cost, not just the single case.
  • The customers and items where it repeats.
Reviewing invoices and pricing records for errors
Beyond the Audit Sample

Reading every document, not the ones that got picked

A sample-based review can only find what happens to be in the sample. The AI reads the full year of orders, invoices, purchase bills, freight documents and stock movements, so a pattern that shows up in a hundred small entries is visible for what it is.

  • The complete period, not a selected set.
  • Patterns across documents, not isolated cases.
  • Findings ranked by what they are worth.
A finance team examining a year of transaction records
Where It Leaks

The findings most businesses see in the first review

Each finding comes with the value at stake, the documents behind it, and who needs to act. You decide which ones are worth chasing.

Rework and rejection cost₹22 lakhJobs run twice, with the cost absorbed rather than recovered or quoted.
Discounts above policy₹19 lakhOrder lines discounted past the approved band with no recorded approval.
Scrap and by-product not billed₹14 lakhSaleable scrap issued out of stock with no corresponding sale entry.
Expired and written-off stock₹12 lakhItems that sat past their sell window while a buyer was available.
Duplicate supplier payments₹9 lakhThe same bill paid twice under a slightly different reference.
Missed contract rebates₹7 lakhVolume slabs reached during the year but never claimed from the supplier.

Illustrative figures

How It Works

From a year of documents to a ranked recovery list

1
Pull the records
We take orders, invoices, purchases, freight, production and stock data for the period.
2
Load the rules
Price lists, contracts, discount policy, standard costs and freight slabs become the reference.
3
Compare every line
The AI checks each document against what should have applied and marks the gaps.
4
Value and rank
Findings are grouped by type, valued in money, and ordered by what is worth recovering.
5
Hand over for action
Each case goes to its owner with documents attached, and a person decides what to do.
What It Checks

Six places money goes missing without anyone noticing

These checks run across the full document set, and can keep running after the first review so new cases surface within days.

🧾

Billing gaps

Deliveries, services and jobs completed with no invoice raised against them.

🏷

Pricing and discounts

Order lines below the approved rate, stale prices, and discounts past policy without approval.

🚚

Freight and logistics

Transport bills above the contracted slab, repeated detention charges and wrong-route costs.

💳

Purchase and payments

Duplicate payments, bills above the purchase order rate, and credits never claimed.

🏭

Production cost

Jobs running above standard cost, rework absorbed silently, and material issued beyond the bill of materials.

📦

Stock and write-offs

Ageing stock heading for write-off, unbilled scrap, and shortages that never got reconciled.

The Difference

What a leakage review changes

Every
Document checked, not a sample
Ranked
Findings by recoverable value
Days
To catch a new case, not a year
Fewer
Repeat pricing errors
Higher
Realised margin per order
Clear
Owner for every case
Why Us

Why finance teams choose TCB Infotech for leakage detection

1
We know the documents
We build ERP, so we read your order, invoice and stock tables as they actually work.
2
Your rules, not generic ones
Checks run against your price lists, contracts and standard costs, so findings are real.
3
Model-agnostic
We pick the approach that fits your document volume and structure, with no lock-in.
4
Evidence attached
Every case links to the exact records, so your team can verify before claiming anything.
5
People approve every action
The system reports and suggests. Raising an invoice or a claim stays a human decision.
6
Proven delivery
50+ projects across industries, with zero failed projects since 2021.
FAQ

Profit leakage detection questions

What is profit leakage?
Profit leakage is money the business earned but never kept: work that was done and not billed, orders priced below the approved rate, discounts given that nobody approved, freight paid above the contracted rate, supplier credits never claimed, and stock written off that could have been sold. Each case is small, which is why it survives, and together they can take a visible share of annual profit.
How does AI find leakage that our audit missed?
An audit samples. The AI reads every order, invoice, purchase, freight bill and stock movement for the period and compares each one against the rate, contract or standard cost it should have followed. It reports the exceptions with the exact documents attached, so nothing depends on which files were picked for review.
What kind of leakage do you usually find first?
The most common findings are billing gaps, where goods or services went out and the invoice never followed, and pricing gaps, where an old rate stayed in the system after a revision. Freight and packaging overruns, unclaimed supplier credits and unbilled scrap follow close behind.
Is this a one-time review or an ongoing check?
It can be either. Most businesses start with a review of the last twelve months to see what is there and what it is worth, then keep the checks running so new leakage is caught within days rather than at the next year-end.
Does it change anything in our ERP by itself?
No. The system finds and reports. Every case goes to the person who owns it with the supporting documents, and a human decides whether to raise the invoice, correct the rate or claim the credit. Nothing is posted without approval.
How much data do you need to start?
Usually twelve months of sales, purchase, inventory and freight records, plus your price lists, contracts and standard costs. If some of that sits in spreadsheets rather than the ERP, that is normal and we work with it.

Find Out What Your Business Is Leaking

Book a free consultation. We will look at the documents you already hold and show you where a leakage review would start and what it would check.

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No commitment. A practical first look at your own transaction data.

AI Governance & Security Features

What Is Inside an AI Governance Framework

The output is a working set of controls, not a policy document that sits in a drawer. Here is what we define, how we build it in, and what you walk away with.

Core Features

Controls that live in how AI runs

Access and Approvals

Who can do what, and what needs a check

We tie access to roles, so each person and tool can only reach the data and actions they should, and we set human approval on the actions that carry risk.

  • Role-based access to tools and data.
  • Approval steps on risky actions.
  • Clear rules for what AI may do alone.
Access and approval controls for AI
Data Protection

Sensitive data stays controlled and private

We define what data AI can access, how it is protected in use, and who can see the output, so sensitive information does not leak through an AI tool.

  • Limits on the data AI can access.
  • Protection for sensitive information.
  • Access rules on the results too.
Data protection for AI
Audit and Compliance

A record of everything, ready for review

Every AI action is logged and monitored, so you can see what happened and prove it, and the whole setup is lined up with your policies and the rules you follow.

  • A full audit trail of AI actions.
  • Live monitoring of what is running.
  • Compliance with your policies and rules.
Audit trail and monitoring for AI
What You Get

Everything the framework delivers

🔑

Access rules

Role-based access to AI tools and the data they can touch.

✅

Approval workflows

Human checks on the actions that carry risk.

🔒

Data controls

Protection and privacy rules for the data AI uses.

📜

Audit trail

A record of every AI action, ready for review.

📊

Monitoring

A live view of what AI is running and how it behaves.

⚖

Compliance view

How AI use lines up with your policies and rules.