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Ever since its launch in November 2022, OpenAI’s text-generating artificial intelligence (AI) chatbot, ChatGPT, has been making headlines as a revolutionary technology. But with business use of AI growing all the time, what makes ChatGPT and other so-called
generative AI tools such good news for commercial lending?
The story so far
Previous incarnations of AI have played a significant part in the increased automation of commercial lending processes . Machine-learning AI tools in particular are highly effective at extracting the right data from credit applications for digital processing
– or making relatively simple lending decisions.
And because these tools are continually mining more data points and learning from human behavior, they become even more accurate and efficient over time.
In a matter of months, generative AI has rapidly gone several steps further. Rather than simply replicating manual processes and human decisions, tools like ChatGPT dig even deeper into available data to create their own textual or visual content.
Suddenly it’s possible to automatically produce an entire, persuasively written dissertation or a disturbingly lifelike deepfake image. That makes generative AI both astonishingly clever and a potentially dangerous way to cheat the system.
Valid concerns
So, while generative AI has the power to revolutionize financial services like commercial lending, it’s also, understandably, unsettling the industry.
First, it introduces major, more sophisticated opportunities for fraud. When generative AI can be used to create initially convincing – but ultimately phony –
pictures of Donald Trump’s arrest, what’s to stop it faking documents to show a commercial lending applicant is more profitable and creditworthy than it is – or that it exists when it actually
doesn’t?
Within financial institutions themselves, the emergence of generative AI tools is sparking other fears. A number of large banks
on Wall Street and
beyond have already banned the internal use of ChatGPT while they assess concerns about data privacy, cybersecurity and access to systems.
Finally, of course, there’s the ever-present worry that AI tools will replace more and more human employees. Generative AI only heightens the anxiety, as it doesn’t just automate repetitive, mindless tasks – it puts creative and cognitive roles at risk,
too.
Rewarding opportunities
But once the industry has addressed these concerns, I think lenders would be missing a trick by ignoring the many potential benefits of generative AI for their processes and even their people.
Positive use cases for generative AI in commercial lending could include:
- Know Your Customer – taking the early identification of problems to the next level
- Credit assessment – determining the creditworthiness of new businesses without a credit history
- Fraud detection – translating unstructured data into meaningful insights and never missing warning signs
- Product generation – digesting thousands of data points about customers to design highly customized facilities and recommend them at the right point in the business cycle
- Commenting on credit applications – giving customers constructive feedback on the reasons for lending decisions
- Financial analysis and forecasting – predicting what could happen to customers or markets in the future
- Report generation – creating more accessible reports and dashboards, tailored to the needs and intellect of the individuals reviewing them
- Model training and validation – supporting stress test scenario generation
- Sentiment analysis – interpreting data on businesses and sectors from news feeds, social media and other online content
- Assisted credit memos – providing all the background information lenders need for human analysis
What about human intelligence?
Like other forms of AI-driven automation, generative AI can remove friction from a wide range of commercial lending processes, by processing vast quantities of data with far greater speed, efficiency and accuracy than a human being ever could. Crucially,
it can also remove human bias and help lenders make totally objective but thoroughly informed decisions.
However, what all AI tools lack is empathy – a quality that’s always served traditional commercial lenders well. Sometimes, when the financials are inconclusive, an instinct, a good gut feeling or a deep understanding of the customer can kick in and lead
to a successful deal.
Ultimately, then, although AI can make a massive, redefining contribution to human decision making, it shouldn’t replace it. Side by side with AI tools, emotional intelligence and human experience still have a major part to play in credit assessment and
loan management.
But change is coming – and coming fast. And if generative AI is to fulfill its potential as a force for good, commercial lenders must quickly find ways for it to work in harmony with their human workforce.
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