Short version: KIS Finance had a 4.96 rating across 280+ reviews, but reputation did not stop three deals from collapsing in a single quarter. Those failures exposed a nasty truth - our "standard formula" for facility sizing was costing us money and time. It took three failed deals to stop trusting spreadsheets with blind faith and start sizing facilities to the reality of each borrower. This case study walks through the problem, the non-glamorous approach we adopted, the step-by-step rollout, the hard numbers we produced, and the concrete lessons you can apply tomorrow.
How a high-performing lender discovered its biggest blind spot
KIS Finance is a mid-market lender specialising in working capital facilities and short-term term loans for UK SMEs. We were proud of our customer scores and a steady pipeline. The underwriting playbook was simple and fast: a rules-based sizing model that multiplied trailing 12-month EBITDA or monthly revenue by a factor, adjusted for industry sector and credit score. That gave consistent outputs, made sales calls short, and helped operations hit SLAs.
Then three deals fell apart within 90 days of funding. Cumulatively they represented £620k of approved facilities, projected year-one revenue of £78k, and potential cross-sell value we expected to build. Two defaulted due to seasonal cashflow swings the model had ignored. One was structurally undercapitalised because of client invoice concentration and a supplier payment lag we had not stress-tested. The headline pain was lost revenue and increased provisions. The reputational pain was worse - the two SME owners called us out on social media, and one review dented our rating thread. That week we stopped defending the model and asked whether facility sizing should ever be treated as a standard formula.
Why the standard facility formula kept breaking deals
We dissected the three failures and found repeatable patterns. The formula assumed steady margins, stable receivables, and predictable payment timing. Real business rarely behaves that way. Key failings included:
- Seasonality: Two businesses had 40-60% revenue concentration in a three-month window. The model used annualised numbers and missed the pre-season working capital squeeze. Concentration risk: One client had 65% of receivables tied to a single buyer who pushed payment terms beyond standard terms during the quarter - a risk the formula discounted too lightly. Cash conversion mismatch: Suppliers required payment on 14-day terms while customers paid on 60-day terms. The formula assumed netting. It did not stress the timing gap. Behavioural and operational quirks: One business habitually delayed invoicing at month end to manage tax timing. Our model used invoice run rate without validating billing discipline.
Put simply, the formula measured size without measuring shape. It gave a single-point estimate with no idea of downside scenarios. That made us efficient when clients behaved like 'average' businesses but exposed the portfolio when they did not.
Designing case-by-case facility sizing: practical principles we adopted
We replaced the reliance on a single multiplier with a structured assessment that produces a pricing and sizing envelope based on observable and stress-tested metrics. The new approach follows seven principles:
- Assess cashflow timing, not just volumes - map receivables, payables, inventory and payroll monthly for 12 months. Stress the operation with realistic down-side scenarios - delayed receipts, lost top customer, price compression. Measure concentration and create dynamic haircuts - larger haircuts for single-buyer exposures. Size to cover peak net working capital needs, not average needs - peak-to-trough is the real risk. Include behavioural overlays - invoicing discipline, supplier leverage, management credibility. Fix a margin of safety that scales with volatility - more volatile businesses get proportionally larger buffers. Make sizing transparent to the borrower - explain the stress tests and what would change the facility size.
Operationally we built an eight-point analysis template that goes beyond credit score and turnover: monthly cash profile, customer concentration, supplier terms, inventory days, payroll timing, contracted revenue, capital expenditure needs, and contingent liabilities. Each factor feeds into an adjusted facility envelope through predefined formulas and scenario outcomes. The aim was not to add bureaucracy but to make a defensible sizing decision for each case.
Rolling out case-by-case sizing: an 8-week implementation roadmap
We implemented this across origination, underwriting, and account management with a fast, pragmatic plan. Here is the condensed timeline we used and what each week delivered:
Week Key activity Owner Output 1 Define assessment template and stress scenarios Head of Credit 8-point template, three downside scenarios 2 Build modeller - 12-month cashflow view and sizing engine Finance & Data Team Working Excel model and documentation 3 Train origination and underwriting teams on new questions Training Lead Two 90-minute sessions, quick reference guide 4 Pilot on five live applications - compare old vs new sizing Credit Ops Pilot results, tweaks to the model 5 Governance - clear uplift/discount bands and escalation rules Risk Committee Approval matrix and covenant triggers 6 Rollout to the whole origination team Head of Sales Go-live, FAQ for sales 7 Monitor first 30 post-implementation deals Portfolio Analytics Weekly exception reports 8 Refine model and codify best-practice notes Head of Credit Version 1.1 of template and handbook
Important implementation notes: we did not try to automate everything before testing. The early stage used a disciplined spreadsheet and clear decision rules so teams could learn the new questions and consequences. We required sales to get the monthly cash profile and two months of supplier and customer ageing before pricing. That raised friction but reduced surprises post-funding.
From three failed deals to measurable improvement in 6 months
Results are what stop debates. Within six months we saw clear, measurable changes in performance:
- Approval hit rate: rose from 38% under the formula to 72% under the case-by-case process for deals that made it to full credit review. That meant fewer low-quality approvals clogging the portfolio. Average facility size: grew from an average of £150k to £210k for approved cases where sizing previously constrained the loan. We were more confident to size larger where stress tests showed capacity to pay. Default and delinquency: 12-month vintage comparison showed defaults fall from 6.5% to 3.9% - a 40% reduction in default rate on recently underwritten deals. Provision releases improved cashflow by £120k in the first year. Time to close: initial cycle time increased by seven working days during pilot while teams learned, then settled back to a 3-day increase on average. The extra time paid off in a lower remediation workload. Client feedback: transparency in sizing improved collection cooperation. Borrowers appreciated seeing stress-test outputs and what to avoid. Our TrustPilot-style rating stayed strong at 4.96 across 280+ reviews with more positive comments about clarity and fairness.
Financially, the net effect was a mix of higher average ticket and lower loss provisioning. Across the first 12 months, the portfolio produced an incremental £450k in net interest and fee income relative to a counterfactual where the old formula stayed in place, after accounting for the modest increase in origination costs.
3 critical lessons we would have told ourselves before the third failure
You will get this wrong a few times. That is the point - learn fast and hard. The key lessons we took away:
Size to the worst reasonable month, not the average month. Businesses live through troughs. Planning for an average month is planning to fail when the trough arrives. Ask for the right inputs up front. If you do not have a monthly cash profile, do not size. A year of bank statements and ageing schedules are non-negotiable. Make sizing decisions explainable. If you cannot justify the haircut or buffer to a borrower in plain terms, you will fail to manage behaviour or get cooperation when covenant breaches happen.How your business can replicate this case-by-case sizing approach
If you manage credit or run a lending product, you can start using this method tomorrow with three practical moves:
Create a one-page monthly cashflow template and make it mandatory on all full applications. No exceptions. Define three downside scenarios (mild, moderate, severe) and a clear rule for scaling the margin of safety with volatility. For example: volatility <10% = 10% buffer; 10-25% = 20% buffer; >25% = 35% buffer. Use a pilot of 20 deals and measure approval rate, time to close, and 90-day arrears. Expect the first month to slow and the next two months to speed up as teams learn.Self-assessment: Is your current sizing process putting you at risk?
Answer these five quick questions. Give yourself 2 points for every yes, 0 for no.
Score guide:
- 8-10 points: You are in good shape. Keep tightening your stress scenarios. 4-6 points: Some strong practices, but you have gaps that could bite in a downturn. 0-2 points: Your process is relying on luck. Start with the one-page cashflow template immediately.
Quick interactive quiz - one minute scenario
Scenario: A textile wholesaler shows annual revenue of £2.4m, but 50% of that revenue is concentrated in November to January. They have a single large buyer representing 45% of receivables and supplier terms of 14 days. Their EBITDA margin is 9%.
Question: Which immediate sizing action would you take?
Apply the standard multiplier to annual revenue and approve the full amount. Size to peak working capital need during November-January, reduce for buyer concentration with a 25% haircut, and require a 30-day reserve account for the peak season. Reject due to buyer concentration alone.Correct answer: 2. You must size for the peak seasonal month, apply a meaningful haircut for single-buyer risk, and use a structural control such as a reserve to manage the predictable seasonal strain. Rejecting outright might be too blunt if the business can be structurally supported.
Final note - stop treating sizing like a checkbox
The three failed deals were painful but https://www.propertyinvestortoday.co.uk/article/2025/08/6-best-development-finance-brokers-in-2025/ useful. They forced us to treat facility sizing as a decision, not a box to tick. The result was fewer surprises, better client relationships, and materially improved portfolio performance. If you run a lending product and still trust a single multiplier to protect you, you are banking on borrowers always behaving like averages. They do not. Build a process that maps cashflow timing, stresses the business, and scales the buffer to volatility. Do that and you will make fewer reactive fixes and more confident approvals.
If you want our one-page cashflow template, the eight-point assessment sheet, and the stress-test workbook we used in the pilot, tell me the size of your typical facilities and I will adapt the documents to your product in a follow-up.