Fintech debt funding is available, but access to capital increasingly depends on the quality of the underlying funding case.
KPMG reported that global fintech investment increased from $95.5 billion in 2024 to $116 billion in 2025. However, deal volume fell from 5,533 to 4,719 transactions, its lowest annual level since 2017.
More capital was deployed across fewer deals, pointing towards larger transactions and a more selective investment environment.
Although these figures cover the wider fintech investment market rather than debt alone, the underlying message is relevant to founders and CFOs approaching lenders: a strong market narrative is not enough.
The company needs to demonstrate why its revenue is durable, what the funding will achieve and how the resulting cash flow will support repayment.
This is where competitive moat becomes part of the credit story.
Fintech Moats in an AI World explores how defensibility, customer embeddedness and AI investment connect to revenue quality and fundability.
Debt providers do not participate fully in the equity upside if an AI investment transforms the business.
Their priority is whether the company can meet its interest and principal obligations under both the base case and a reasonable downside scenario.
This means lenders are likely to focus on areas such as:
As Fuse has also highlighted in its analysis of private debt selectivity in the UK and Europe, capital remains available, but lenders are placing greater weight on financial visibility, resilience and credible repayment pathways.
A large addressable market does not guarantee debt serviceability.
Lenders need to understand why customers should remain and why forecast revenue should continue after the capital has been deployed.
A fintech that is deeply integrated into billing, reconciliation or risk workflows may be able to demonstrate stronger revenue visibility than one dependent on a small number of easily replicated features.
Relevant evidence may include:
The credit question is not simply whether customers value the product today. It is whether they are likely to continue paying for it throughout the life of the facility.
“Investing in AI” is too broad to function as a compelling use of funds.
A lender needs to understand what the investment will change.
For example:
The distinction between peripheral and core AI is useful when presenting this case.
|
Area |
Peripheral AI |
Core AI |
|
Primary purpose |
Improve internal efficiency |
Strengthen the core product or infrastructure |
|
Typical applications |
Customer support, reporting, administration and document processing |
Underwriting, fraud intelligence, orchestration and proprietary decision-making |
|
Expected benefit |
Lower costs and increased productivity |
Better customer outcomes and deeper differentiation |
|
Time to value |
Often shorter |
May require a longer implementation period |
|
Cash-flow impact |
Can improve margins and near-term serviceability |
May strengthen revenue, retention and long-term value |
|
Defensibility |
Often reproducible by competitors |
Stronger where linked to proprietary data or workflows |
Peripheral AI can improve the funding case where its savings are identifiable and measurable.
Core AI may create a stronger long-term moat, but the business must explain the investment required, the implementation period and the commercial benefit.
A well-developed fintech debt funding case may combine both: near-term efficiency gains that support cash flow alongside longer-term investment that makes the business harder to replace.
A lender ultimately needs to connect the use of funds to the company’s ability to service and repay the facility.
Founders and CFOs should show four things:
The forecast should distinguish between identifiable cost savings and anticipated revenue growth.
Cost reductions may be easier to evidence when they relate to known headcount requirements, third-party costs or processing expenses.
Revenue improvements require a clear commercial mechanism. Evidence could include customer demand, contracted pipeline, improved conversion, increased transaction capacity or stronger retention.
Before approaching lenders, the leadership team should be able to connect three parts of the narrative.
Explain why customers stay, what competitors cannot easily reproduce and where the product sits within customer operations.
Support the explanation with retention, cohort performance, contract length, transaction activity and concentration data.
Show how the facility will fund integrations, infrastructure, data capability, regulatory expansion or a proven commercial model.
Avoid presenting the debt primarily as a general runway extension unless the route from additional runway to measurable value is clear.
Connect the strategic investment to revenue visibility, margins and cash generation.
The strongest story allows a lender to follow the logic from capital deployment to operational improvement and then to repayment.
Fuse Capital’s work with fintech and financial-technology businesses provides examples of funding aligned to specific commercial objectives:
The structures and circumstances differ. The common thread is that the funding requirement could be connected to a defined strategy, operating model and credible growth outcome.
Before starting a process, ask:
Debt can support AI investment, product development, acquisitions, expansion and working capital where the business has sufficient revenue visibility and the structure matches its cash-generation profile.
It should reinforce the moat rather than weaken the business through excessive repayment pressure or restrictive terms.
Our view is that funders do not need to believe every part of an ambitious AI vision. They need to understand the commercial pathway behind it.
A credible fintech debt funding case translates technology investment into measurable changes in retention, margins, revenue visibility or risk.
That provides a stronger basis for assessing facility size, structure, covenants and repayment.
Watch Fintech Moats in an AI World: What AI Commoditises and What Remains Defensible for the full discussion with Martin Koderisch and Kayode Sulola.
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Fuse Capital Group advises growth-stage businesses on debt funding across the private credit market.
Businesses considering funding for AI investment, infrastructure, expansion, acquisitions or working capital can explore our private credit advisory approach or speak with the Fuse Capital team.
Potentially. Debt may be appropriate where the company has sufficient revenue visibility, a defined use of funds and a credible ability to meet repayment obligations. Suitability depends on the company and proposed structure.
Lenders commonly assess recurring or transaction revenue, retention, customer concentration, margins, cash generation, historical performance, funding purpose and debt-serviceability.
A defensible market position can support retention and revenue visibility. This may give lenders greater confidence that cash flow will remain available to service the facility.
The business should prepare historical financial information, forecasts, customer and retention data, concentration analysis, a clear use-of-funds plan and an explanation of how the investment will support repayment.