By Simon Moss, CEO of Symphony AyasdiAI
During the Great Recession, enterprise technology businesses did relatively well, including those that served a banking and funds sector that took a direct hit.
Banks and funds that survived cut costs to balance their books as demand cratered, but CIOs felt they couldn’t scrimp on software subscriptions lest they fall behind in increasingly competitive markets where survival meant claiming more of a shrinking pie.
Some in the enterprise tech industry think that dynamic will happen again. Despite recent positive earnings from big tech companies, they’re almost certainly wrong. Now it’s the other way around.
The world is in the midst of what is shaping up to be potentially the worst economic crisis in a generation. It might not feel like it yet because almost everyone has been in a state of denial called lockdown. Sooner or later, though, we’ll open our eyes and see who’s not wearing a swimsuit now that the tide has gone out.
To wit, as Gavin Baker at Atreides Management has written, companies under duress are taking a second look at existing software contracts. Companies spend half their IT budgets on software. A responsible leader can’t keep it off the chopping block.
A false sense of security has lulled many tech and AI firms into thinking they can get away with marketing their technology in the abstract, leaving it to the customer to figure out the best use case. That approach might have worked in a world where customers had the time and money to indulge in exploration.
Customers are nervous. They’ve got more challenges at a time when revenue is a question mark. Our task is to listen and respond with real, easily understandable and, perhaps most importantly, immediate solutions that directly address their needs this week.
Customers today don’t want to know how or why a technology works. They want to know how soon they will see that it is making a measurable difference. For instance, let’s take a look at banks right now.
Banks Swimming In Uncharted Waters
The government’s $4 trillion of stimulus spending in the face of the pandemic is a bonanza for fraudsters. The politicians want to flood the zone with cash overnight. Bankers, however, are on the hook for sifting applicants to figure out who deserves the money and who is seeking to exploit the overwhelmed system for ill-gotten gain.
Thieves have plenty of stolen identities in their little black books. Shell companies abound. Under pressure to shovel out the loans quickly to forestall economic oblivion but wary of regulators eager to blame them for the pitfalls of the government’s haste, the bankers must figure out how to identify good customers from bad.
The moment seems perfect for AI. But humility is a better first response. Most machine learning today is fighting yesterday’s fraudsters. It might catch the amateurs. The professionals, meanwhile, have already been camping in their victims’ networks using sophisticated tools that represent a new generation of graft that’s likely more sweeping than those we’ve stopped in the past.
Commercial banks don’t want more layers of protection that consume their attention, either. They’re already flooded with calls and facing staffing shortages while dealing with swamped government agencies and poorly designed, malfunctioning websites.
The objective, non-biased, hypothesis-free analyses afforded by the right kind of artificial intelligence has a better shot at making banks’ challenges simpler. Auditable machine learning could, for example, provide regulators with not just what fraudsters were uncovered, but why and how.
But do bankers want to hear about topologies and the difference between supervised and unsupervised machine learning? Certainly not. They’re racing too fast for a lecture. They can’t waste time asking if they can really integrate new software into their workflows.
As bankers face a crisis in oversight, generational changes are also afoot. Millennials in particular are poised to begin inheriting trillions in the coming decades. Many of them feel little or no affinity with traditional banks. They expect far more tech-oriented options. To satisfy them, banks are going to need to cut costs in their old systems in order to develop new platforms.
We estimate those cost cuts will comprise around 40 per cent of current spending on technology. Those changes come in addition to the coronavirus pandemic and its aftereffects.
The frothy market for software led to high valuations in recent years. Inexpensive debt helped, too. Look around now. Once-confident AI companies that are having a hard time convincing investors and customers of the value of their product in the new environment. Now customers are facing monumental risks while seeking to lower overhead. That’s a tough climate for the less-than-fit.
AI companies who can quickly demonstrate to jittery chief risk officers and chief financial officers that they can filter out the cheaters, chiselers and scam artists quickly and decisively will not only survive but prosper. That’s the prize we’re chasing. It won’t just come to us.
Simon Moss is CEO of Symphony AyasdiAI, an artificial intelligence software company serving financial services and other industries.