Using AI to Strike the Right Balance Between Innovation and Risk

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Ben Weismer
Director, Product Innovation
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Pace of innovation calls for strong collaboration between humans… and between humans and machines.

Since the dawn of the information age, humans have filled the gaps between what technology can do and what the enterprise needs. Now, in the era of artificial intelligence (AI), machines are doing more of the gap-filling work than ever before.

A significant gap many growth-oriented organizations are confronting today is the one opened by the rapid pace of innovation. Leaders charged with predicting and solving for “what’s next” are under immense pressure to ideate and get solutions to market quickly. In the financial sector, that pressure often gets transferred to enterprise risk managers who must swiftly evaluate a universe of potential threats, and ultimately, give the green light to launch an innovation. 

The gap exposed by time-consuming, manual risk assessment and the enterprise’s desire to compete and grow presents a massive opportunity for AI augmentation of human capabilities. Luckily for both innovators and their risk colleagues, AI-based risk assessment is democratizing rapidly, opening up new possibilities for fast (and safe) go-to-market initiatives. 

Augmenting, not replacing, risk professionals

Human experience is an essential component to assessing risk. In fact, I’ve heard more than one risk manager say their discipline is more of an art than a science. That’s part of what can make it somewhat difficult to imagine leaning on machines to evaluate risk. 

But consider this. On their own, people can’t possibly know every risk in every corner of the world, nor can we adequately predict the likelihood that risk will live out in our particular neck of the woods. The year 2020 brought that message home loud and clear. But, with the help of machines, we can get much closer to knowing what challenges are likely around the bend and the probability that they will impact us negatively. 

Already, AI and machines learning (ML) are collaborating with humans in the financial services risk assessment discipline. Learning technologies process much more information, much more quickly, than traditional risk scoring methods that rely on human processing to function.

AI risk assessment already in play

Take lending, for example. Decisions around a consumer’s creditworthiness is increasingly based on alternative data, such as social media behaviors or utility and rent payment histories. It’s one of several ways the traditional financial system is working to bring underserved consumers into the fold. On its own, the content a person likes on Facebook or the regularity of a mobile phone payment is not enough to determine loan approval, pricing or terms. But, when blended with lots of other unstructured data such as natural language, images and speech – and then run through an algorithm that predicts the likelihood of default – the data becomes much more meaningful.

The same is true in fraud detection and prevention. AI detects and stops fraud in real-time by pulling data from a variety of sources, including national crime databases, biometric data stores and behavioral data collections. Human analysts stay in the loop, course-correcting and “training” the AI tool so it can spot a false positive on its own the next time.

Fundamentally, AI and ML are allowing risk management professionals to stop losses more proactively, rather than manage risks inherent to operations.

Of course, there are limitations to AI and ML. Today’s AI solutions are learning from algorithms most often developed by humans. When turned into disparate bits and bytes of data, poor judgement or lack of sensitivity can take on a life of its own. Lending professionals, in particular, will need to carefully monitor for bias as they implement different learning technologies into their day-to-day decisioning and risk assessment.

Innovators hone threat management skills thanks to risk colleagues

Humans love taking risks. The same thrill we get from paragliding along a glacier or deep-sea diving in shark infested waters is experienced by many of us in business who love the adrenaline rush of trying new things. We don’t do so recklessly. In fact, we have honed our risk management skills by working alongside our risk colleagues. 

That said, our human evaluation of risk is just as imperfect as any other human pursuit. It’s my belief that eventually, AI and ML will empower us to take risks at a richer and more meaningful level because we will have the added confidence that our decisions are powered by the best technology has to offer. 

Risk professionals bear a big portion of the brunt when it comes to weighing the risks and rewards of technology innovation. If you’re an innovator, make it a point to thank a risk professional this week. Without their carefully honed practice and purpose-driven discipline, we wouldn’t have the freedom to develop solutions for the millions seeking to live financially healthier lives.