Banking GRC · Audit Surveillance Platform

See every transaction the moment it matters.

AuditWork is a continuous-monitoring platform that watches your core banking data for the eighteen most damaging transaction patterns — and gives auditors the evidence to act, in working-paper form, the same day.

Aligned with

RBI Master Directions ICAI SA 530 IIA Standards DPDPA 2023 CERT-In

Book a 30-minute walkthrough → See the product

Why AuditWork exists

Internal audit teams in banks face a structural problem: transaction volumes have outgrown the team's ability to review them. The patterns that matter — structuring, NPA back-dating, suspense cycling, window dressing — are detectable in the data. Just not by hand.

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Audit Lag

Issues surface a quarter late, after recovery options have closed.

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Sampling Blind Spots

Random sampling cannot reliably find rare-but-severe patterns like structuring or NPA back-dating.

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Evidence Assembly

Even when a flag is found, building the working paper from scattered CBS reports takes days.

Four modules. Eighteen scenarios. One audit trail.

AuditWork is organised into four surveillance modules. Together they cover the patterns that account for the majority of transaction-level audit findings in Indian banking.

Cash Surveillance

7 scenarios

Unusual deposits and withdrawals — structuring, dormant revival, loan diversion, round-tripping.

Back-Dating Detection

5 scenarios

Postings whose value date does not match the entry date — NPA avoidance, interest smoothing, GL parking.

Reversal Analytics

5 scenarios

Patterns inside reversal entries — maker-checker breaches, suspense cycling, single-user concentration.

Window-Dressing Watch

1 scenario

Period-end inflation followed by reversal — book balances, NPA classification, deposit aggregation.

From CBS extract to working paper, in four steps.

Workflow

Ingest

Upload CBS Master, Transaction, GL and Loan extracts as CSV or Excel. AuditWork auto-maps synonyms across CBS vendors.

Configure

Every threshold is editable on a single rules page. Defaults align with RBI and ICAI guidance. No code required.

Run

One click runs all eighteen scenarios. Each match becomes a finding with rule, evidence, risk rating and recommended audit response.

Export

Multi-sheet Excel working paper — Findings, Scenario Summary, Thresholds Applied, Methodology — ready for the audit file.

What you get out of the box

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18 pre-built detection scenarios

Coverage across cash, back-dating, reversals and window dressing.

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Configurable thresholds

Every parameter exposed on a single page. Adjust to your risk appetite, no code.

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Schema-agnostic ingestion

Auto-maps CBS column names. Works across Finacle, BaNCS, Flexcube and most NBFC core systems.

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Findings register with drill-down

Filter by risk, module, scenario, branch or user. Open any finding for transaction-level evidence.

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Audit-grade working papers

Multi-sheet Excel export — formatted for the audit file, not for analysts.

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Reproducible runs

Seeded execution and threshold-stamping mean a re-run produces identical output.

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Single-file deployment

Runs in the browser. No installation, no database, no IT ticket.

Built on the frameworks regulators read.

AuditWork's detection logic, thresholds and reporting outputs map back to the frameworks that auditors and supervisors already cite — by design, not afterthought.

RBI Master Direction on KYC, 2016 RBI Prudential Norms on IRAC RBI Master Direction on Frauds Prevention of Money Laundering Act, 2002 ICAI SA 530 — Audit Sampling IIA International Standards DPDPA 2023 / CERT-In Directions

Stop sampling. Start surveilling.

AuditWork lets your audit team see every transaction the moment it matters — and gives them the working paper before the next committee meeting.

Book a 30-minute walkthrough →

Module Detail

Every scenario — what it detects and why it matters in the context of Indian banking audit.

Cash Surveillance

7 scenarios

Cash leaves the smallest paper trail and hides the largest risk. AuditWork's cash module reads every cash deposit and withdrawal across your branch network and flags the patterns that auditors and regulators repeatedly find inside fraud, money-laundering and KYC failures.

Dormant account reactivation

A long-inactive account suddenly shows large or repeated cash activity — a common shell for laundering and stale-account fraud.

Structuring / smurfing

Cash deposits broken into amounts just below the reporting threshold by the same customer or to the same account.

Loan diversion

Cash withdrawn within days of a loan disbursement, breaking end-use covenants.

Round-tripping

Funds deposited and withdrawn in a tight window — accounts being used as a conduit, not for genuine banking.

Salary-account misuse

Salary credits routed straight into cash withdrawals on the same day, indicating the account is not held by the actual employee.

New-account cash burst

A newly opened account immediately receiving or releasing large cash — a classic mule-account signal.

PAN-level aggregation

Cash that looks small per account but, aggregated by PAN, crosses regulatory thresholds across multiple accounts.

Back-Dating Detection

5 scenarios

Back-dating is the audit profession's longest-running concern: an entry posted today, but value-dated last month, is almost always concealing something. AuditWork compares posting timestamps with value dates and flags every gap that matters.

Generic back-dating

Postings where the value date is materially earlier than the system entry date — quantified, ranked by amount and gap.

NPA-avoidance back-dating

Repayments back-dated to keep an account inside the standard-asset window under RBI IRAC norms.

Interest-adjustment back-dating

Manual interest entries with prior-period value dates that smooth income recognition across reporting cut-offs.

Customer-charge back-dating

Service charges or penalties dated to a month already closed — a fee-leakage and dispute-handling risk.

GL / suspense back-dating

Journal entries to general-ledger and suspense accounts back-dated to manage period-end balances.

Reversal Analytics

5 scenarios

A reversal entry is normal; a pattern of reversals is a control failure. AuditWork pairs every debit-credit reversal in the data and runs five separate tests to separate genuine corrections from override misuse, suspense cycling and insider activity.

Excessive reversals

Accounts with reversal counts or values that exceed both an absolute threshold and a peer-group baseline.

Maker-checker breach

Reversals where the maker and checker are the same user, or where the checker did not exist in the workflow — a direct SoD failure.

Suspense cycling

Funds that move into a suspense account and reverse out within a short window without external clearance.

Customer-level reversal pattern

Single customers whose accounts show reversal frequencies far above the bank-wide norm.

Bulk reversals by one user

A single maker responsible for a disproportionate share of all reversals — an insider risk indicator.

Window-Dressing Watch

1 scenario

Period-end optics are the oldest trick in banking, and the easiest to detect with the right data lens. AuditWork compares the last few days of a reporting period against the first few days of the next and surfaces every entry whose only purpose appears to have been to flatter a closing balance.

Period-end inflation and reversal

Large credits or deposits booked in the final two business days of a period and reversed within the first few days of the next — the signature pattern of book-balance dressing.