Answer: In two words – kind of.
Commercial lending technology has, of course, taken significant strides in recent years thanks to the rise of AI. Consequently, commercial lending technology is no longer restricted to email, spreadsheets and documents. Instead, the current landscape includes a spectrum of tools designed to enhance the speed, accuracy and accessibility of commercial lending.
AI-powered lending tools can automate key processes (such as data entry, data validation, customer service via chatbots, etc.) and introduce extra capabilities (e.g. instant credit decisioning, personalised loan solutions, AI-powered digital contracts and more).
So, what’s the issue? There are a few ongoing gripes about the state of commercial lending technology, potentially holding it back from achieving its full potential. We’re thinking of a utopian view of commercial lending technology where:
At the moment, this ‘view’ is simply not happening. Though there are no hard statistics about technology in commercial lending spaces, currently, only 75% of firms in financial services are using AI, and it’s likely a similar statistic exists in the lending sector.
In this article, we’ll address three factors potentially holding back commercial lending technology and explore how the industry could resolve them.
‘We can automate parts of processes, not automate entire processes. So where we can do those bits that help, that can reduce risk or drive efficiency’.
~ Adam Crockford, Senior Manager Automation, Novuna Business Finance
With technology developing so fast, it can be difficult to pinpoint what is automatable and what isn’t. A hyper-automative approach – where businesses pool resources into automating as many processes as possible – may ultimately prove an (admirably) ambitious goal.
In actuality, Adam Crockford is correct – whole processes in commercial lending generally cannot be automated or, at the very least, automated using just one technology.
Using commercial lending technology to address inefficiencies in a business borne of parts of processes may initially deliver a foundation requiring substantial improvement. Rome wasn’t built in a day, after all.
Commercial lenders could build an AI strategy that starts by automating parts of processes like:
Of course, necessary integration is one of the main issues with adopting even lightweight automation.
Promoting employees to use ChatGPT for basic analysis does not require integration. However, integrating AI into complex lending tech stacks may necessitate a technologically advanced approach that some firms do not feel prepared for. Case in point: Outdated IT architecture can make even simple API integrations seem like they are not worth the expense or time.
Concerns around the feasibility of integration directly relate to the talent shortage in IT. The talent shortage is holding back commercial lending technology insofar as:
However, the right tools will not need a whole IT department. Rather, the best solutions will mask complex technology with the most user-friendly design possible. But, integration and accessibility may not be the only concerns for commercial lenders. You can always overcome complex integration issues but not a lack of compliance.
Ultimately, adoption is one of the most helpful ways to develop industry-specific technology. By onboarding new clients and collecting their feedback, fintech companies in the lending space can not only survive but refine their offerings.
Reasons for not exploring new technologies are manifold, including concerns about the expense, ease of use, changes to workplace culture and so forth. But one particular issue – maintaining security and compliance – stands out. A paper by CPA noted that security and privacy were the main concerns (yet the cost was not, indicating that financial services professionals are aware of technology’s economic potential).
However, businesses can assuage the concerns around security and privacy by working with a technology vendor with rigorous technological security. Consider whether the vendor:
If the vendor has worked with banks, their banking clients will likely have assessed the vendor's security certificates and protocols thoroughly.
DF Capital is a relatively young UK bank specialising in asset finance. Completing ‘four eye checks’ for the invoice data they input into their systems slowed them down.
However, they overcame potential uptake issues by investing time and resources into a Proof of Concept (PoC), proving the model’s accuracy. They also resolved issues with compliance by ensuring that the provider was ISO27001 compliant, providing best-in-class practices for data security.
After confirming that the experiment was successful, they deployed the solution. The solution saves them time by 95% compared to manual extraction, which has allowed them to meet their sustainability and customer goals.
As a commercial lending technology provider, we can attest that commercial lending technology is improving by leaps and bounds. However, there is a long way to go, and improvements cannot occur until commercial lenders fully embrace AI technology’s potential.
Commercial lending has always presented a challenge to technology developers. Why? It requires both accuracy and speed. The resulting technology needs to be powerful without compromising usability and compliance.
When commercial lenders and fintechs work together, the results can be fruitful. Maybe 2025 will be the year where education, motivation and technical capabilities meet in the middle, removing all barriers to technological success.
Interested in trying Evolution AI’s multiple award-winning technology for free? Book a demo or email hello@evolution.ai for more information.
Stay up to date with our takes by following Evolution AI on LinkedIn.
