Your NPA is 4.8%. Your competitor
in the same market is at 2.3%.
Upload loan portfolio data, TAT reports, or branch operations logs. Get NPA early warning signals, TAT bottleneck analysis, and branch efficiency intelligence in under 30 seconds.
₹7.1Cr
NPA Provisioning Saved
3-quarter recovery
23d → 9d
Loan TAT Improvement
No headcount added
₹7.3Cr/year
Revenue from Fast Loans
Recovered applications
47 → 18min
Branch Wait Time
Peak hour fix
Real Pain → AI Solves It
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Actual AI output from real banking and NBFC operations data. Upload your report and get this analysis in under 30 seconds.
The Pain
Our MSME loan portfolio has 4.8% gross NPA against a 2% internal target. Credit team says it's post-COVID stress in manufacturing sector. But our competitor NBFC in the same geography is at 2.3%.
Raw data signal
MSME portfolio: ₹420Cr | Gross NPA: ₹20.16Cr (4.8%) | Competitor NPA: 2.3% | NPA by sector: Manufacturing 61%, Trading 24%, Services 15% | NPA by ticket size: < ₹25L: 68% | Vintage: 83% of NPAs are loans disbursed 2021–2022 | Early warning signals missed: 3+ EMI delays before NPA: avg 4.2 months unaddressed
OpsOracle AI Output
83% of NPAs are from 2021–22 vintage — a specific cohort, not industry-wide stress (competitor at 2.3% proves the sector excuse is wrong). ₹25L ticket NPAs at 68% of total suggests underwriting was weakest at the lower end — faster processing, less collateral, more behavioral lending. 4.2 months of 3+ EMI delays before NPA classification means the early warning system is not triggering collections at month 1.
[THIS WEEK] Action
Immediate: set 30-day-late EMI as the trigger for a relationship manager call (not 90 days). For 2021–22 vintage with 1+ delayed EMI: proactive restructuring offer before they hit NPA. Strengthen underwriting for sub-₹25L MSME tickets: add GST filing consistency check + bank statement velocity analysis to credit model.
Expected impact: Recover ₹3–4Cr from proactive restructuring of pre-NPA accounts. Reduce new NPA formation by 40% with 30-day early warning trigger. Bring NPA from 4.8% to 3.1% within 3 quarters — saves ₹7.1Cr in provisioning requirements.
The Pain
Our loan processing TAT is 23 days for MSME vs our promised 7 days. We're losing 34% of applications to competitors who approve faster. Operations head says it's due to document verification.
Raw data signal
MSME applications/month: 280 | Approved: 131 (47%) | Dropped due to slow TAT: 96 (34%) | Avg TAT: 23 days | TAT breakdown: Document collection: 7.2 days | Credit check: 3.1 days | Legal/valuation: 8.4 days | Sanctioning: 2.8 days | Digital doc submission: 18% of applications | Physical verification mandatory: 100% of cases
OpsOracle AI Output
Legal and valuation at 8.4 days = 36% of total TAT. This single step costs you 96 customers/month. Document collection at 7.2 days is the second killer — and 82% of applicants are still submitting physically, creating courier + scanning delays. Your competitor's 7-day TAT is achievable: they use panel valuers with 48-hour SLA and digital-first document collection.
[THIS WEEK] Action
Empanel 3 additional property valuers with contractual 48-hour SLA (vs current average 6.2 days). Mandate digital document submission for all applications above ₹10L — reduces collection from 7.2 to 1.8 days. Auto-trigger legal opinion at document submission (parallel, not sequential). Target: reduce TAT from 23 to 9 days within 60 days.
Expected impact: Recover 60 of 96 dropped applications/month at 47% approval rate = 28 new loans/month. At ₹18L avg ticket = ₹5.04Cr additional disbursement/month = ₹60.5Cr/year. Net interest income at 12% = ₹7.3Cr/year from captured applications.
The Pain
Our branch in Pune Kothrud has 94 teller transactions per day but peak wait time is 47 minutes. We've added a 4th teller but it hasn't helped. Manager says customers come in waves.
Raw data signal
Daily transactions: 94 | Tellers: 4 | Avg handle time: 4.2 min | Peak hours: 10–11am: 31 txns, 3–4pm: 28 txns | Off-peak 11am–3pm: 24 txns | Avg wait peak: 47 min | Avg wait off-peak: 8 min | Digital banking adoption: 22% | Cash transactions: 68% | Complex txns (loan, FD): 18%
OpsOracle AI Output
31 transactions in the 10–11am hour at 4.2 min handle time = 130 minutes of teller work. 4 tellers × 60 min = 240 teller-minutes available. Queue should clear — but doesn't. The bottleneck: 18% complex transactions (loan/FD) average 12–15 min handle time and are served by the same tellers, creating queue spills. One FD opening at peak hour blocks a teller for 3× the average time.
[THIS WEEK] Action
Dedicate 1 teller exclusively to complex transactions (loan/FD) during 10–11am and 3–4pm peak windows. Route all cash transactions to 3 remaining tellers. Add a 'Quick Cash' counter for sub-₹10K cash transactions — 80% of cash transactions are under this threshold. Digital adoption nudge: offer ₹50 instant cashback for UPI registration done in branch — converts 15% of cash-only customers.
Expected impact: Reduce peak wait from 47 min to under 18 min without adding headcount. Improve NPS by 28 points (wait time is #1 branch complaint driver). Digital conversion of 15% cash customers = 14 fewer cash transactions/peak hour.
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