We speak with Alexandra Mousavizadeh, co-founder and CEO of Evident, about how banks are leveraging artificial intelligence (AI) and why it is important for them to invest into this technology. Mousavizadeh also shares how banks are already using AI and the challenges that stand in the way of further adoption.
What is the role of banks in global AI investments?
Banks make investments into early-stage AI companies for many reasons, including access to innovation and AI implementation accelerators, gaining market intelligence, forming strategic partnerships with startups, improving their competitive positioning, or fueling the pipeline for future acquisitions.
Investment in AI companies by the major banks is growing, at 15% CAGR from 2017 to 2022. It’s U.S. banks driving this activity, with five U.S. banks – led by Wells Fargo and Goldman Sachs – accounting for almost 50% of all AI investment deals during this period.
Around 70% of AI investments are strategic in nature, designed to support the banks’ core missions or functions. The rest of these investments essentially involve client cash being invested through the banks’ Venture Capital or Private Equity vehicles – and many of the companies being supported have AI applications with limited immediate or obvious impact on banking.
Why is the adoption of AI critical for banks?
Put simply, the banks that embrace AI and successfully place it at the center of their ongoing digital transformation efforts will be the breakout winners in the industry. Those that don’t double down on AI will be left behind.
In many ways, the big banking institutions are well placed to take full advantage of the AI revolution. After all, they have a treasure trove of valuable customer data at their fingertips, as well as strong internal processes to ensure that AI implementation does not go awry – the advantage of operating for years within a heavily regulated industry.
However, on the flipside, the banks face significant competitive challenges from Big Tech, fintech and the neobanks, all of which have been outflanking the establishment in recent times. Legacy banks may cease to exist altogether if they fail to meet the challenge of AI-driven digital transformation.
This explains why, despite the layoffs being seen across most departments, the big banks are massively stepping up their AI hiring. In some institutions, this is the only area of the business in which headcount is increasing.
It’s also why they’re making a huge effort to highlight their progress on AI adoption, and our data shows that investors and shareholders are noticing. The banks which demonstrate their AI strategies and leadership are starting to see improved stock price performance, dominating industry conversations and crowding out the competition.
What are some top ways banks are already leveraging AI?
Across the entire industry, banks are actively using AI across a wide range of processes. For example, they are using it for fraud prevention and anti-money laundering, to smooth customer identification and authentication processes for customer service, and to provide personalized recommendations to customers. In leading banks, AI is now being leveraged in every nook and cranny of the business.
Risk mitigation is a particularly interesting space for AI innovation. Unlike the global financial crisis of 2008, we now have powerful AI technologies capable of identifying early warning signs of financial distress within banks or myriad other risks that could lead to a collapse. The leading banks are now looking at how they can use AI across their portfolio to improve decision-making and clarify the full extent of any potential losses well before they occur.
What are some challenges that stand in the way of banks fully adopting the technology?
The banking leaders who truly get AI knows that the technology has the potential to fundamentally reimagine what it means to be a bank.
These leaders are looking to embrace AI on an organization-wide level, becoming AI-first banks, essentially, which requires a massive internal reorientation and a change in the organization’s collective mindset. There will inevitably be mistakes made along the way, particularly when implementing more complex AI use cases, and while shareholders want to see the banks embrace AI, they also want to see clear ROI across these different use cases.
It’s going to be a difficult balancing act, navigating towards an AI-first future while ensuring a near-term return on the AI investments being made. What’s more, the hype surrounding ChatGPT has created the misconception amongst less tech-savvy stakeholders that because Generative AI interfaces are now more accessible and intuitive, commercial AI deployment is itself easier, cheaper and less risky – none of which is accurate.
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