Why Banks Still Build What They Should Buy - And What It's Costing Them

For decades, banks have been navigating the crucial decision of whether to build lending platforms in-house or buy an external vendor solution.  

Banks frequently select the “build” option – in the belief this is the best, most cost-effective way to improve operational efficiency, drive differentiation, and improve customer experiences.

But is this true?  

At face value, the approach appears to offer more control, greater customisation, future-proof transformation, and long-term cost savings. But in today’s fast-moving and highly competitive banking environment, that view is potentially a strategically risky one.  

After the global financial crisis, UK lending markets were highly concentrated, with around 90% of SME lending provided by the 4 largest banks. But in the last two years we’ve witnessed the rise challenger banks and alternative lending providers, which now account for 60% of annual gross bank lending to SMEs.

Demand is high - it’s predicted that by 2030 the UK SME sector alone will require finance to the tune of £70 billion+ - but overall loan success rates for businesses applying for bank finance are low in the UK, at less than 50% on average.

It’s therefore more important than ever that banks carefully analyse the build versus buy decision.  After all, it’s one that will prove pivotal in shaping their ability to adapt to competitive market conditions, increased demand and evolving regulatory landscapes; and help manage risk while delivering superior lending experiences.

Why do banks build?

The rationale behind internal lending builds is understandable, and there have been notable successes.

Traditional banks still struggle with legacy tech stacks and have huge reputational concerns and regulatory pressure over data privacy and compliance.  Plus, banks often have big teams of people that can “do the job”.

But too often, this “build” mindset leads banks down a long and costly road, fraught with missed opportunities, and ultimately delivers solutions that are already out of date by the time they’re deployed.

Let’s look at a couple of scenarios:

Bank 1

This tier one bank has successfully built a lending platform internally, leveraging their own skilled tech and compliance teams.  The result is a highly tailored solution that meets its specific needs - integrating with existing legacy software, improving operational efficiency, and enhancing data consistency.

Sounds good right?  But it’s come at a huge time and resource cost, and the bank is still struggling to access as granular level analysis of customer suitability and affordability.  Resource availability and financial investment will remain a concern as the bank works to ensure in-house innovation keeps up with digital challengers, AI-powered fintech’s, and data-driven alternative funding providers.

Bank 2

This fast growth tier two bank doesn’t have huge inhouse resources, so it bought an advanced credit decisioning platform from a leading vendor, when its incumbent in-house system began suffering from escalating investment and prolonged development cycles. The switch to a “buy” approach empowered cross-functional lending decisioning via advanced API integrations, data orchestration, and automated workflows.

The vendor’s expertise, vast range of data sources, application of continuous market-wide learning, focussed product development, and dedicated teams meant the bank was able to quickly deploy a robust and scalable solution and deliver a comprehensive approach that vastly improved the accuracy and efficacy of credit decisioning.

The hidden costs of building in-house

It’s clear from these examples that the true cost of a “build” approach goes beyond just developer hours and investment in compliance teams.

The hidden costs can quickly mount up:

• Time to deployment: what starts as a six-month sprint can easily become an 18-month marathon
• Continuous maintenance: continuous updates, UX enhancements, bug fixes, security patches, regulatory changes, tweaks to the customer journey.  These all consume valuable internal resources, leaving less time to focus on compliance and adding value to customers
• Integration challenges: making legacy and innovation play nicely is no mean feat, but it’s certainly a costly one.
• Innovation lag: the pace of change is brutal.  Keeping up without external support is a huge ask, and a huge investment - after all, when internal teams are fighting fires, they’re in technical debt and aren’t building competitive advantage.

But it gets even worse. Assessing affordability is more challenging than ever. Accurate credit decisioning requires that banks take an increasing number of factors into account when considering a customer’s suitability.  Without access to the right external data sets, banks will only ever have an incomplete picture of customers credit risk exposure, affordability, and liquidity.  This makes it tough to balance the fair treatment of customers and the experience they receive, with risk mitigation across their lending portfolio, and their ability to meet stringent compliance requirements.

The exposure both in terms of both cost and risk management losses are huge. Take this example from Experian for instance:

In this example, the prospective customer’s business turnover was equal to around £30m according to the annual accounts, which were confirmed with Current Account Turnover (CATO) data. However, Credit Account Sharing Information (CAIS) also showed that the company was servicing over £90m of active debt – all on either three or four-year repayment terms. This sum was understated in the company’s reported liabilities.

These insights revealed that the customer’s debt-to-income ratio was over 300% – a particularly worrying figure considering that the average term of the debt was around three years. Finally, the Debt Service Ratio was over 100%, meaning that all the company’s revenues were required just to support the existing debt repayment obligations

This case demonstrates the critical need for a full picture of affordability, and why access to the broadest range of data and insights into multi-lender exposure can prevent significant losses based on fair, timely, accurate affordability assessments.  It also highlights why in-house lending builds are especially complex.

So, why buy?

The landscape has changed; in fact, it’s constantly in flux. Vendor platforms are not just faster and more cost effective to deploy; they’ve got evolution baked in.

Here are just a few of the benefits of a “buy” approach:

• Access to live, external data sources: financial data orchestration, consolidating intelligence from across the banking ecosystem can enable banks to gain a fuller of a customer’s liquidity, debt exposure, and cash positions.  Total visibility for more advanced decision making
• Eliminate fragmented internal data limits: Banks often struggle with incomplete visibility across different lending products and customer accounts and end up working in silos. By eliminating this siloed approach and replacing it with API-powered connected insight, banks can spot cross-sell opportunities and improve experiences at every stage of the customer lifecycle.  
• Advanced monitoring: With timely insights and alerts into customer behaviour and changes to risk profile, banks can respond to liquidity issues or borrowing spikes before they escalate - helping balance risk and the delivery of proactive support

When banks buy the right solution, you're not trading control for convenience. You’re investing in speed, differentiation, compliance and scalability, and most importantly customer experience.  

A change of mindset is required. Banks that continue to build what they should buy aren’t just over-investing — they’re falling behind. The smartest players are shifting from builders to integrators, from owners to orchestrators.

The “buy” decision just got a whole lot easier…

Introducing nCino ProBanker powered by FullCircl.

ProBanker delivers real time access to restricted commercial credit data for a total market view of customer risk and opportunity across multiple financial institutions. This advanced ready-to-deploy solution supports smarter lending decisions, stronger customer relationships, and faster time to funding.

ProBanker draws on an exceptionally rich dataset of around 18 million commercial credit accounts’ credit history from 180+ commercial credit contributors (CAIS and CATO), as well as Commercial Credit Data Sharing (CCDS) data of approximately 10 million records from the CMA9 banks.

It can assist your bank to:

• Access a multi-bank, total market view of a customer’s credit exposure
• Track affordability and liquidity in near real-time
• Strengthen portfolio health by identifying early warning signs of financial distress
• Accelerate time to funding
• Improve customer outcomes through proactive engagement and personalised outreach

Contact us to find out more about this market-first lending solution.