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Model Validation & Evidence

Proven on 2,466 real invoices

What This Means for a Bank

FatooraFi's scoring model can identify 58% of invoices as low-risk (Bands A+B) with only 8% late rate — versus 88% late rate for high-risk (Band E). This 21.4x separation lets you fast-track the good invoices, price risk accurately for the middle, and decline or hold the worst — instead of treating every SME the same.

58%
Fast-Track Eligible
Band A+B invoices with <10% late rate
21.4x
Risk Separation
Band E late rate vs Band A late rate
5
Policy Tiers
Fast-track → Review → Hold → Decline
Why it matters: Without segmentation, you either reject too many good SMEs (losing revenue) or approve too many risky ones (taking losses). This model gives you the tool to do both — grow volume while managing risk.

2. Risk Band Stratification

BandRisk Leveln (test)LateLate RatePolicy
ALow Risk340144.1%Fast-track
BModerate862225.6%Fast-track
CFair773950.6%Review
DElevated815163.0%Enhanced review
EHigh Risk15613787.8%Decline/Hold
21.4x separation (Band E / Band A late rate)
Higher separation = better discrimination between good and bad invoices

3. Annual Value Calculator

Enter your portfolio parameters to estimate annual value from improved risk triage.

Scenario Analysis
ScenarioLoss ReductionVolume UpliftLoss SavingsProfit UpliftTotal/Year
Conservative4%1%SAR 3.2MSAR 1.5MSAR 4.7M
Base8%1.6%SAR 6.4MSAR 2.4MSAR 8.8M
Upside12%2.5%SAR 9.6MSAR 3.8MSAR 13.3M
Pilot will measure actual improvement on your portfolio.
Base Case Annual Value
SAR 8.8M/year

Your Portfolio Parameters

SAR 1BSAR 100B
Annual invoice financing / SME receivables volume (not total banking assets)
0.5%5%
Use your definition: write-offs, DPD 90+, or charged-off exposure
20%80%
Fee rate minus funding cost minus ops cost
0.5%3%

Improvement Assumptions (Inputs)

4% (conservative)12% (upside)
% reduction in losses from improved triage. Pilot will measure this.
1% (conservative)2.5% (upside)
Current Baseline Losses
SAR 80.0M/year
(2% write-off × 40% LGD × SAR 10B volume)
Where do these inputs come from?
Annual Financed Volume: SME receivables / invoice finance exposure from your finance team
Write-off Rate: Bank's internal DPD 90+ rate, write-off ratio, or charged-off exposure %
LGD: Existing loss-given-default assumptions from credit risk team
Net Margin: Fee rate – funding cost – ops cost (from treasury/product)
Improvement %: Estimated from model lift; calibrated on bank data during pilot
Formulas
Loss Savings = Volume × Write-off% × LGD × Improvement%
Profit Uplift = Volume × Uplift% × Net Margin
Implementation path: Proof of Value (90 days) → Production Integration (60–90 days)
📊
Pilot validates these assumptions on your portfolio
A 90-day proof-of-concept measures actual loss reduction and volume uplift against your historical data. Results calibrate these inputs to your specific portfolio characteristics.

4. What Drives Predictions

Customer Avg Settle TimeFatooraFi
64.5%
Invoice Amount
16.5%
Disputed Flag
13.3%
Paperless (Electronic)FatooraFi
3.1%
Country/Region
2.6%

68% of predictive power comes from FatooraFi-unique signals (buyer payment history, invoice verification). These are operationalized through ZATCA integration and not readily available to banks today.

Ready for a Pilot?

Validate these results on your own portfolio with a 90-day proof of concept.