Insights

A Smarter Foundation for SME Lending: Why Banks Need a New Operating Model

Written by Team Bourn | Jul 24, 2025 9:11:42 AM

SME lending doesn’t need a better UI - it needs a new foundation.

Banks have spent years digitising SME lending - scanning PDFs, bolting on tools, dressing up old systems. It hasn’t worked. Lending is still too slow, too manual, too expensive to scale.

Overdrafts once made up 30% of SME finance. Today, they’re just 5%. Not because demand disappeared, but because the economics did. High overheads, slow decisions, and fragmented systems have made it nearly impossible to serve SMEs efficiently, especially below £100K.

What’s needed isn’t another layer of tech on top. It’s a new foundation.

Enter agentic lending - a model where intelligent software agents take on the heavy lifting across the credit lifecycle. From onboarding to underwriting, risk monitoring to servicing - it all happens in real time.

And it’s quickly changing how banks and lenders think about operations: cutting cost-to-serve, unlocking smaller tickets, and reducing reliance on human-led workflows.

The old model is holding back growth

Traditional lenders are weighed down by:

  • Legacy systems with limited flexibility
  • Siloed risk, credit, and ops teams
  • Manual, high-cost servicing
  • Expensive underwriting models
  • Decisioning frameworks built around quarterly risk reviews

It’s a high-cost, high-friction model - and it’s killing margin.

The cost to originate, underwrite, monitor, and service smaller facilities has become too high to justify. Every £100K facility requires the same human effort as a £1M one, with none of the return. It’s left a huge segment of the market underserved, and a big source of potential revenue untapped.

A New Operating Model for SME Lending

Agentic lending doesn’t tweak around the edges, it rethinks the entire credit lifecycle.

Instead of relying on people and batch processes, agentic systems use intelligent software agents to handle onboarding, underwriting, monitoring, and servicing - continuously, and in real time.

For lenders, that means less manual effort, faster decisions, lower operating costs, and greater control over credit performance.

We’re not talking about bots that plug into legacy workflows. We’re talking about a new infrastructure where AI agents act as specialised digital counterparts to your team:

 

  • Risk agents that scan accounting, banking, and ERP data to monitor exposure and surface early warning signs
  • Ops agents that reconcile payments, track utilisation, and trigger alerts automatically
  • Underwriting agents that adjust limits based on live receivables data
  • Customer agents that guide SMEs through onboarding and funding in minutes, not weeks

It’s a model designed to scale - with better margins, cleaner portfolios, and a dramatically lower cost to serve.

Rebalancing the Cost of Lending

Traditional SME lending is resource-heavy. Most lenders spend 30–40% of their cost base on people - underwriters, credit analysts, risk committees - while software typically accounts for less than 5%.

That imbalance makes it hard to profitably serve smaller businesses - especially on facilities below £250K.

Agentic lending changes the equation. Intelligent systems take on repetitive, high-volume tasks like assessing data, flagging risks, reconciling payments, so your teams can focus on exceptions and value-add decisions.

That means:

  • More time spent on revenue generating activities
  • Lower cost to serve
  • Faster decisions
  • Expanded SME eligibility
  • Better unit economies on smaller tickets (even on sub £250K)

 

Why Most AI Projects Fail

Banks and lenders have been piloting AI for years - document automation, chatbots, scoring tools. But most of these efforts stall before they scale.

McKinsey reports that the majority of generative AI pilots in financial services fail to reach production, not due to the tech itself, but because of weak infrastructure and poor governance.

You can’t just bolt AI onto legacy systems. Without real-time data, system-wide visibility, and compliance built-in from day one, AI becomes just a surface level tool like Chat GPT - not a new operating model.

 

Data is the Difference

The smartest lenders aren’t relying on any single data source. They’re combining real-time feeds, structured documents, and intelligent analytics to transform how credit is assessed and managed.

Live connections to client systems and payments feeds provide a continuous view of financial health. Business documents like contracts, invoices, and statements are no longer static PDFs, but structured inputs that can be parsed and analysed instantly.

When these signals are brought together and analysed in real time, they unlock a new level of automation and precision across the credit lifecycle, from onboarding to monitoring to collections.

This isn’t about one system replacing another. It’s about building an operating model where data flows freely, insights are surfaced automatically, and decisions happen faster - with greater accuracy and less manual effort.

Why Lenders Are Partnering with Bourn

Forward-thinking lenders are already moving beyond pilots and bolt-on tools - and building toward a new, scalable operating model.

With Bourn, they’re unlocking a smarter approach to SME lending:

  • Deploying intelligent agents to handle onboarding, underwriting, risk monitoring, and servicing
  • Integrating live data from ERP systems, bank feeds, and documents - all structured, all real-time
  • Automating low-margin processes to reduce cost-to-serve and improve return on assets
  • Launching new working capital propositions without adding operational burden

Bourn provides the infrastructure. Lenders stay in control and go to market faster.

The result? A more agile lending model, better economics on smaller tickets, and a clear path to revenue growth - without the traditional cost.

Learn more at bourn.ai.