QuickFund Online — Detailed Monthly Financial Projections – Year 1

The following tables provide granular monthly projections for Year 1, demonstrating the revenue ramp-up from the beta launch in Month 6 through to full operations by Month 12. These projections reflect the phased launch strategy, with limited beta operations in Months 6–7…

QuickFund Online (Pty) Ltd Business Plan › Detailed Monthly Financial Projections – Year 1

Section 15 · Business Plan

Detailed Monthly Financial Projections – Year 1

The following tables provide granular monthly projections for Year 1, demonstrating the revenue ramp-up from the beta launch in Month 6 through to full operations by Month 12. These projections reflect the phased launch strategy, with limited beta operations in Months 6–7…

15.1 Monthly Revenue Build-Up (Year 1)

The following tables provide granular monthly projections for Year 1, demonstrating the revenue ramp-up from the beta launch in Month 6 through to full operations by Month 12. These projections reflect the phased launch strategy, with limited beta operations in Months 6–7 and progressive scaling through marketing activation and Western Cape expansion from Month 9.

Months 1 through 5 represent the pre-revenue establishment and development phase. Revenue generation commences in Month 6 with the pilot launch (500 beta customers) and scales through to Month 12.

Revenue Line (R’000) M7 M8 M9 M10 M11 M12
Loans Disbursed (#) 420 680 1,050 1,400 1,750 2,100
Average Loan Size (R) 2,800 2,900 3,000 3,000 3,100 3,100
Interest Income 59 99 158 210 271 326
Initiation Fees 63 102 158 210 263 315
Service Fees 24 39 60 80 100 120
Insurance Commissions 6 10 16 21 26 32
Other Income 5 8 13 17 22 26
Total Monthly Revenue 157 258 405 538 682 819

15.2 Monthly Operating Expenditure (Year 1)

Expense Line (R’000) M7 M8 M9 M10 M11 M12
Salaries & Benefits 332 332 345 345 358 358
Marketing & Advertising 180 200 220 180 160 150
Technology & Cloud 70 70 75 75 80 80
Office & Utilities 45 45 45 48 48 48
Professional Fees 30 25 25 25 30 35
Credit Losses Provision 33 55 88 117 147 176
Other Costs 25 25 28 28 30 30
Total Monthly Expenses 715 752 826 818 853 877
Monthly EBITDA -558 -494 -421 -280 -171 -58

The monthly projections demonstrate a clear trajectory toward operational break-even. The progressive reduction in monthly losses from R558,000 in Month 7 to R58,000 in Month 12 reflects increasing revenue scale, improving operational efficiency, and the benefits of the AI credit scoring engine in managing default rates.

15.3 Monthly Cash Position (Year 1)

The cash position throughout Year 1 is supported by the R20 million capital injection, with the largest cash outflows occurring during the platform development phase (Months 1–6) and initial loan book capitalisation (Months 7–12). The Company maintains a minimum cash buffer of R1.5 million throughout Year 1 to ensure operational resilience.

Cash Position (R’000) M7 M8 M9 M10 M11 M12
Opening Cash 5,200 3,800 2,900 2,200 1,800 2,100
Cash from Operations -558 -494 -421 -280 -171 -58
Loan Book Cash Outflow -1,176 -960 -1,110 -1,050 -1,085 -1,050
Loan Repayments Received 334 554 831 930 1,156 1,308
Financing Activities 0 0 0 0 400 500
Closing Cash 3,800 2,900 2,200 1,800 2,100 2,800

15.4 Loan Portfolio Analysis – Year 1

The following analysis provides a detailed view of the loan portfolio composition and quality metrics throughout Year 1, demonstrating the progressive build-up of the loan book and the effectiveness of the AI credit scoring engine in maintaining portfolio quality:

Portfolio Metric Q1 (M1–3) Q2 (M4–6) Q3 (M7–9) Q4 (M10–12)
New Loans Disbursed 0 500 (beta) 2,150 5,250
Cumulative Loans 0 500 2,650 7,900
Gross Loan Book (R’000) 0 1,400 6,500 12,800
Provision for Bad Debts (%) N/A 12% 10% 9.5%
Net Loan Book (R’000) 0 1,232 5,850 11,584
Average QuickFund Score N/A 520 540 560
Approval Rate N/A 42% 48% 52%
30+ Day Default Rate N/A N/A 11% 9.8%

The improving portfolio quality metrics reflect the AI credit scoring engine’s ability to learn from actual repayment data and progressively refine its predictive accuracy. The average QuickFund Score of approved applicants increases from 520 in Q2 to 560 in Q4, indicating the model is becoming more selective and accurate in identifying creditworthy borrowers.

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