CIC Watch List · Live in 14 banks & NBFCs

Catch the next ₹100 Cr fraud before your next CIBIL pull.

FinAGG.AI continuously monitors every MSME on your book — GST, banking, MCA, GSTR-2A — and surfaces diversion, fake-invoice and dummy-supplier patterns the bureau cannot see. One score. One queue. Every morning.

Trusted by
HDFC CIC Federal Bank Axis CIU IndusInd RBL +9 more
cic.finagg.ai / monitoring
HDFC CIC · Analyst Console
CIC Monitoring
🔔 Alerts 12 PM
Monitored MSMEs
12
₹20.50 Cr sanctioned
Critical risk
2
Action required
High risk
3
Investigate this run
Open alerts
9
2 in review
Flagged exposure
₹15.95 Cr
78% of book
⏷ Tier : All tiers
⏷ Fraud : All fraud types
⏷ Analyst : All analysts
⟲ Run timeline
↓ Export
BorrowerFameScoreTrendTierFraud flagsSanctionBTOLast run
Rajesh Enterprises
B-1042 · AAACR4521K · Thane, MH
38
↓ 14
Critical
DiversionFake InvoiceDummy
₹1.00 Cr 71%↓ 71pt 2026-04-15
Medichem Pharma Pvt Ltd
B-0987 · AAACM2398L · New Delhi
44
↓ 8
High
HSNFake Invoice
₹2.50 Cr 88%↓ 36pt 2026-04-12
Sunrise Textiles
B-1158 · AAACS9821P · Surat, GJ
51
↓ 6
High
Stock
₹5.00 Cr 96%↓ 9pt 2026-04-18
Vertex Auto Components
B-0912 · AAACV1290Q · Pune, MH
68
↑ 2
Watch ₹1.50 Cr 108%↑ 6pt 2026-04-19
Apex Foods & Spices
B-1320 · AAACA8821H · Ahmedabad, GJ
73
↑ 1
Watch ₹0.90 Cr 112%↑ 3pt 2026-04-22
₹427 Cr
In bad-loan exposure flagged for member banks in 2025
11 days
Average lead-time over CIBIL on the first fraud signal
3.2×
Lift in catch rate vs. quarterly bureau-only review
94%
Analyst-confirmed precision on Critical-tier flags
Fraud signals

Five MSME fraud patterns the bureau will never tell you about.

Bureau scores describe how a borrower has behaved. FameScore describes how a business is actually behaving — right now — by triangulating GSTR-1, GSTR-2A, GSTR-3B, banking flow and MCA filings. Each pattern has its own evidence rail and its own pattern score.

High

Diversion of Funds

Loan disbursal routed to non-business or related-party accounts within days of credit, with no matching invoice on the GST rail.

Pattern score22 / 100
Evidence4
Clean

Stock Position Fraud

Reconciles declared stock against FAME-implied stock from GST plus banking — catches inflated drawing-power claims at source.

Pattern score82 / 100
Evidence0
High

Dummy / Circular Transactions

Recurring high-ticket invoices with zero bank settlement, often to promoter-linked counter-parties identified via MCA.

Pattern score31 / 100
Evidence5
High

Fake Invoice Fraud

Invoices billed to GSTINs that were cancelled or suspended at/after invoice date, or to circular customer-supplier rings.

Pattern score26 / 100
Evidence5
Clean

HSN Code Fraud

Compares declared business nature against the actual HSN purchase mix — surfaces shell entities masquerading as legitimate MSMEs.

Pattern score88 / 100
Evidence0
📈
High

Banking-to-Turnover collapse

BTO crossing 85% means the borrower's bank credits no longer support reported GST sales — typically off-books revenue or fund diversion.

Threshold≥ 85%
Lookback6 runs
How it works

From sanction to surveillance in one onboarding sprint.

FinAGG.AI plugs into your existing core-banking and bureau stack. We don't replace your CIC pull — we layer underwriting-grade behavioural data on top of it, on a daily cadence, and only escalate the borrowers your analysts actually need to look at.

01 — Connect

Plug in your book

Upload sanctioned MSME list with PAN, GSTIN, sanction amount and disbursal account. Day-1 baseline within 4 hours.

02 — Pull

Daily multi-source pulls

GST (1, 2A, 3B), AA banking, MCA filings, e-invoice rail and IRP-NCLT trackers — all consent-fenced and audit-logged.

03 — Score

FameScore + run delta

One 0-100 score per borrower per run, with side-by-side delta against the previous run, and a pattern-level evidence rail.

04 — Act

Triaged alert queue

Critical and High flags flow into your CIU's queue with FameReport PDF, regulator-ready paper trail and SLA timers.

Inside a borrower file

A side-by-side run, not a snapshot.

Every borrower opens to a side-by-side comparison of the current run versus the previous one — across 12 underwriting metrics. The metrics that broke a threshold are highlighted; the rest are quiet. Analysts work the deltas, not the haystack.

  • BTOBanking-to-turnover dropped from 142% → 71% — investigate off-books revenue or fund diversion
  • PARTYNew related-party debit detected: ₹85L RTGS to Kohli Holdings LLP, no GSTR-2A entry
  • CONCTop-5 customer share rose 7.2pt — concentration risk increasing, monitor next run
  • FILEGSTR-3B filed 3 days late — first such delay in last 6 runs
Side-by-side · Run R-6 vs R-5Rajesh Enterprises
Metric Last This Δ
GST sales (TTM)₹9.20 Cr₹6.85 Cr↓ 25.5%
Banking-to-Turnover142%71%↓ 71.0pt
Debt-to-Turnover56%52%↓ 4.0pt
Top-5 customer share54.0%61.2%↑ 7.2pt
GSTR-1 filing delay2 days5 days↑ 3.0d
Inward bounce rate1.4%2.1%↑ 0.7pt
Avg bank balance₹28.00 L₹22.00 L↓ 21.4%
Why a CIC layer

Bureau is rear-view. FAME is real-time.

India's MSME default cycle is 9-14 months ahead of bureau visibility. By the time DPD shows up on a CIBIL or CRIF report, the diversion has already happened, the inventory has already moved, and the GSTR-1 trail has already gone cold. FAME closes that gap.

Bureau-only review
  • ↳ Quarterly cadence, post-default visibility
  • ↳ DPD-based — fraud often paid down before it shows
  • ↳ No view of GST, banking flow, MCA changes
  • ↳ Reactive — analyst opens the file after the loss
  • ↳ Cannot distinguish fraud from genuine stress
FAME CIC Watch List
  • → Daily cadence, 11-day median lead time
  • → Behavioural — diversion, dummy, fake-invoice rails
  • → GST + AA banking + MCA + e-invoice triangulation
  • → Triaged queue with FameReport, SLA, audit log
  • → Separates fraud-tier from genuine-stress-tier
Pilot programme · Q3 onboarding

Run FAME against 50 borrowers from your book this week.

Send us a sanitised borrower list — PAN + GSTIN + sanction. We'll return a baseline FameScore, fraud-pattern map and Critical-tier shortlist within 96 hours. No commitment, no integration.

Book a pilot → Download the one-pager