State Departments

Screen every treasury payment your state made this year

State finance departments, directorates of audit and vigilance cells already hold the data. NIRNAE turns it into a ranked list of entities and transactions worth inspecting.

9
Agents cross-checking the same working ledger
01
Merged ledger built from many departmental files
100%
Findings shown with re-derivable arithmetic

Audit mandates

Where the engine is applied

Each mandate is examined against records the institution already produces — no new reporting is imposed on the field.

Treasury payment review

Full-year payment registers screened for splitting, duplicate bills and same-day sanction-and-payment cases.

Departmental procurement

Vendor clusters sharing an address, bank account or directors, bidding against themselves in the same tender.

Constituency development funds

Works split into small orders, recurring implementing agencies, and vendors located far from the sanctioned work site.

Subsidy and DBT integrity

Beneficiaries recurring across schemes under near-identical particulars, and disbursals to dormant or newly created accounts.

Civil works and PWD bills

Works certified without measurable quantities, and the same bill raised across two financial years.

Vigilance case support

Entity linkage and the payment chain in order, prepared as an audit observation with a recommended verification step.

Records examined

What you send us

Standard exports. A date, an amount and a payee identifier per row is enough to begin; every additional column unlocks further tests.

  • 01Treasury payment registers
  • 02Sanction and work orders
  • 03Contractor and vendor masters
  • 04Beneficiary lists
  • 05Measurement book abstracts
  • 06Scheme-wise expenditure statements

Disclosure

Operating boundary. NIRNAE holds no live access to treasury, PFMS, banking or departmental systems. The department exports the records it wants examined and submits them. The product is in pre-deployment: engagements today are supervised pilots on exported or anonymised datasets, and every finding is an indicator for verification, not a determination. Full answers in the FAQ.

Interested?

Leave a departmental email and we will arrange a briefing on a sample dataset.

Request a briefing