Adfin: How to Automate Revenue Collection with AI
- Marc Griffith
- May 12
- 4 min read
Summary Adfin has raised €15.3 million to extend a platform that combines proprietary payment infrastructure and agentic AI to reduce invoice delays. The solution claims to bring on-time payments to 91% and serves over 1,500 companies; the capital will fund product, hires, and international expansion. Key takeaways
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Automating revenue collection is at the heart of Adfin's strategy: the London-based fintech has just closed a €15.3 million round to take its platform beyond mere collection, toward end-to-end cash flow management. With the new capital, Adfin aims to expand the product, hire engineers and sales staff, and launch international expansion.
Overview of the fundraising and goals
Founded in 2024 by Tom Pope and Ciprian Diaconasu, Adfin positions itself as a platform designed specifically for invoice payments, combining proprietary payment infrastructure with agentic AI. The company aims to make the collection process faster, traceable, and secure, always keeping humans in control.
Adfin aims to transform critical financial workflows: it automates repetitive tasks and suggests optimal actions to improve collection times and liquidity management.
How to automate revenue collection in practice
The platform evaluates every invoice and decides, using agentic AI logic, the best communication and payment action for that customer, leveraging multiple channels and accounting integrations. By automating these activities, Adfin contends that businesses recover liquidity faster and reduce operating costs tied to debt management.
Automating Revenue Collection: Infrastructure and AI
Adfin says it has built both the underlying financial infrastructure and the governing agentic workflows, combining control, auditability, and traceability. Owning both levels enables automated decisions that are safer and easier to audit by the finance function.
Automating Revenue Collection: Observed Results
According to the company, its solutions have led to a late payment rate of 9% among Adfin's customers, compared with a UK SME average of 63%. Lowering late payments improves working capital and the operational resilience of client businesses.
Adfin's approach is not just automation: it is a model that blends infrastructure and decision intelligence to tackle corporate cash flow bottlenecks.
Funding and growth strategy
The €15.3 million Series A was led by Index Ventures, with participation from Visionaries Club and new investors such as Stéphane Kurgan and Andrey Khusid. The capital will strengthen the product toward end-to-end cash flow management and support key hires in engineering and sales.
Adfin serves over 1,500 companies in the United Kingdom, including accounting firms, law practices, and professional services and care businesses; the focus is on scale and internationalization. The company intends to use domestic market results as a lever to enter new countries with similar capital optimization needs.
Critical Debate: Opportunities, Risks, and Limitations (in-depth analysis)
The Adfin model highlights a tension typical of fintechs that automate sensitive financial functions: on one hand, automation can unlock capital and reduce operational friction for thousands of SMEs; on the other, there is a risk that poorly calibrated automated decisions could worsen delicate business relationships or trigger legal disputes over collections. For founders, the key question is: how to balance decision intelligence with human oversight to preserve long-term customer relationships?
Pros: the end-to-end approach promises immediate efficiency and measurable metrics, such as reduced payment delays; this is particularly relevant for businesses with thin margins or seasonal cash flows. Cons: reliance on agentic AI requires high-quality data, robust governance, and transparency of decision rules to avoid bias or unwanted escalations. Implementing clear policies and operational feedback loops is essential to maintain controls and trust.
From a regulatory standpoint, solutions that orchestrate payments and communications must comply with anti-fraud, data protection, and, in some markets, payment execution requirements. This can slow international expansion or require partnerships with local operators. A prudent strategy includes local proofs of concept, integrations with banking partners, and a scalable compliance plan.
Finally, there is a competitive perspective: many companies offer enhanced credit management or factoring tools, but few combine payment infrastructure and agentic AI in a native way. This positions Adfin in a potentially defensible niche, provided it maintains performance and transparency in automated decisions.
Practical implications for founders and CFOs
For leaders of startups or SMBs, adopting solutions like Adfin's can translate into an immediate improvement in operating cash flow and less time spent reconciling and chasing invoices. A pilot assessment on a segment of customers or a portfolio of at-risk invoices is the most prudent way to test real impact.
Operational tips: define financial KPIs based on days sales outstanding (DSO), automation errors, and impact on customer relations; plan a manual rollback for sensitive cases; and integrate the solution with the existing accounting system. Measuring before and after adoption is the only way to quantify value and justify the investment.
A Step Forward in Money Movement
Adfin offers a clear vision: treating money movement not as back-office tasks but as a strategic growth lever that can free resources and reduce operational risk. If the reported performances hold on scale, the cashflow solutions market will see a new generation of products focused on intelligent automation of payments.
Tom Pope summarizes the company's ambition: automate the workflows that drive payments and enable finance teams to focus on value-added decisions. For founders, the lesson is clear: money movement is not admin, and an optimized process is a competitive lever.
