The impact of machine learning and generative AI on business
November 07, 2023
Ever since its launch in November 2022, OpenAI’s text-generating artificial intelligence (AI) chatbot, ChatGPT, has been making headlines and stoking fears. Science fiction, it seems, is coming true as AI moves a significant step closer to outthinking humans.
AI, of course, has long been part of our everyday lives. Just ask Alexa or Siri. The difference with ChatGPT and other so-called generative AI tools is a massive advancement in cognitive skills.
In the world of work, generative AI changes the game by encroaching – in theory at least – on a wider range of roles. Before, jobs ostensibly at risk from AI had to involve a logical sequence of tasks. Now, more creative, cerebral occupations are no longer so safe.
But is this all just hype? And where do these latest advancements leave the businesses that, until now, have been happy to harness the power of AI?
Learn more about the benefits of AI in this video featuring Harry Stahl, Senior Director, Enterprise Strategy, FIS®.
Making data mean business with ML
Pre-ChatGPT, AI tools have played a significant part in the increased automation of critical processes. For example, data is critical to both analysis and efficiency. But its sheer volume, variety and complexity can also make it difficult to access and apply to core banking and lending processes.
Machine learning (ML) AI tools, in particular, have taken digital transformation to the next level by making far better and faster use of data than other technologies or human beings. AI algorithms get to the heart of this dilemma by bringing new ease and efficiency to data analytics.
In addition, powerful, transparent and auditable ML models can now integrate with any number of data sources to accelerate decision-making and improve the visibility and accuracy of risk monitoring processes.
Stealing jobs — or winning back time?
As models and tools become smarter and more powerful, one of the biggest concerns about AI is its potential to put regular human employees out of a job.
The counterargument is that, as robotic colleagues, AI and ML tools can actually help improve the employee experience by adding six key attributes to businesses’ processes and analytics.
AI works a lot faster than humans. While manual processes slow staff down and frustrate the customer experience, AI will race through routine tasks and free up time for employes to add value with customer-facing work.
The more data you have, the better you can inform your decisions. AI tools can analyze a wide range of data types in a single action and pull the data directly into a dashboard or other application.
AI tools can easily do multiple jobs at once, and they access and integrate disparate data sources on an ongoing basis. They can therefore make connections and pick up on details a human might miss – to predict, for instance, when credit is deteriorating or a customer might need a new product.
Despite the rise of automated technology, many companies still input a lot of data manually, which increases opportunities for error. AI tools have a low error rate, and, just as importantly, they can fill in the cracks in automation that result from disconnected systems – and cause manual mistakes.
After years in a business, experience may tempt you to think you always know best and should rely on your instinct. In theory, AI's dispassionate focus on facts makes for more objective decision-making. But don’t forget that AI models are created by humans and so can potentially both adopt and perpetuate human biases.
6. Continuous improvement
Whether supervised or unsupervised, AI tools can learn – either from human input into their models or through their own observation of the data, the operating environment and their impact on that environment. They can therefore continually refine their processes and decision-making abilities.
By taking administrative tasks off employees’ hands, AI leaves businesses freer to focus on strategy, spend time with their customers and build both relationships and value. But at the same time, it takes superhuman care of the critical processes that underpin your operations.
So, even as headlines suggest that AI might threaten tomorrow’s jobs, AI also has huge potential to make today’s work more rewarding.
Driving deeper, forward-looking insights
As well as turbocharging processes and saving human employees time, AI tools can help businesses build a fuller, more in-depth and more dynamic picture of their customers and prospects.
AI gives businesses the ability to draw on a wider, richer set of data, not only historic financials, but also covenant, transaction and market data, news feeds and social media. It’s these more current data sources that can show how things are for customers – and predict where they could be heading.
The trick is to sift through a mass of constantly changing information, pull out the salient points and alert the right people at the right time so they take the right action.
That’s what AI does best, with greater pace and accuracy than a human ever could.
Changing the game with generative AI
So far, then, so good; AI tools are already proving their ability to not only make day-to-day working lives easier but also forecast future challenges. But 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.
So, while generative AI has the power to revolutionize business, it’s also understandably unsettling many industries.
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 credit applicant is more profitable and creditworthy than it is or that a customer exists when it actually doesn’t?
Within businesses themselves, the emergence of generative AI tools is sparking other fears. For example, 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, generative AI only heightens the anxiety that robotic tools will replace more and more human jobs. According to this argument, it doesn’t just automate repetitive, mindless tasks – it puts higher-powered roles at risk, too.
Enriching businesses with new opportunities
But once the financial services industry has addressed its valid concerns about generative AI, there are many positive use cases for businesses to explore. These 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 or customer journey
- 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
Bringing humans and technology together
There’s much that AI can add to a business, for customers and employees alike. But what all AI tools lack is the human ability to read between the lines, to understand, if not empathize with, the nuances and subtleties of human behavior.
Sometimes, when the financials are inconclusive, an instinct or a deep understanding of the customer can override the numbers and lead to a successful deal.
Ultimately then, AI can make a massive, redefining contribution to human decision making, but it shouldn’t replace it. Side by side with AI tools, emotional intelligence, human experience and human judgment still have a major part to play in business.
But change is coming – and coming fast. And if generative AI is to fulfill its potential as a force for good, businesses must quickly find ways for it to work in harmony with their human workforce.