By Spencer Tuttle, VP EMEA at ThoughtSpot

One way in which financial services companies are constantly gaining competitive advantage is through their readiness to embrace new technologies. The industry has long been an early adopter of technology; the telegraph system was still a novel idea when Western Union began using it for money transfers in the mid-19th century. Online banking emerged in the mid-1990s, half a decade after the internet, and well before most people had an email account. Now, fintech companies are taking on legacy banking incumbents with ambition, converting loyal and long-standing customers to new and innovative ways of managing money.

This revolution in technology has so far covered the connecting of people and the collection of data. As we look ahead to the next frontier, AI looks set to bring the next wave of innovation, as its ability to bring value from that collected data – to people across every department, of every financial organisation – gains momentum.

Investment banks, retail banks and insurers all stand to benefit from its adoption with tangible benefits – many already are. However, we recently commissioned a study in association with The Economist that found that while confidence in AI investments is high, few are actively acting upon and benefitting from the promise of AI in the short term.

Of 200 business executives and C-level respondents working in retail banks, investment banks, and insurance companies across Europe, APAC and North America, 86% said they plan to increase AI-related investments into the technology over the next five years.

Those surveyed were clear that AI will transform their business in a number of ways during that time, including spurring new products and services, opening up new markets or industries, and paving the way for innovation. But, by contrast, only 15% attest to the technology being used extensively across their organisations today.

What’s interesting is that only a very small proportion of that percentage hail from Europe. In contrast, 61% of all APAC respondents reported that half or more of their workload is supported by AI, compared with North America and Europe which both sat at 41%. What the research went on to show is that there are a few factors as to why this is the case.

The lack of business alignment

Firstly, there is a tangible lack of alignment between business outcomes and the application of AI in many financial institutions today. The study revealed that one of the largest perceived barriers to AI adoption is due to a self-reported lack of metrics to measure AI-application success. 10% of European respondents, for example, either had no metrics to measure AI-application success or had not been measuring it for long enough to provide insightful reports. Conversely, all APAC respondents had functional reporting metrics.

In my experience, more often than not this means organisations are not aligning AI with business outcomes. Companies should not be trying to identify new metrics that can measure the success of AI in their business. Instead, businesses should look at the metrics they already leverage to measure a specific use case and measure how the introduction of AI has changed those existing KPIs. After all, AI is only as valuable as it is impactful to the business.

Dave Oliver, head of the nerve centre at RBS, said it best. “I’ve heard people say that we need a special metric to measure the effectiveness of implementing AI, but I think the firms that do this best have no special metrics—it’s simply the measurements used to measure the performance of your firm.”

The lack of training investment

Another primary obstacle to overcome is the perceived challenge of upskilling current staff to become more data literate in order to use AI systems to their full potential. Europe saw this as more of a challenge than any other region, which suggests there is vital training to take place before the benefits of AI can be realised here.

Notably, APAC prioritises reskilling and training initiatives, with 75% of APAC respondents in this region expecting an increased investment in people over the next five years to learn more AI skills and arm them with resources, compared to 59% in North America. Only 37% of firms in Europe plan to do the same, meaning their teams will be woefully behind, even if they increase technology investments.

What most don’t consider is that many AI solutions now provide a dramatically reduced barrier to entry. Employees in financial organisations do not need to become data scientists in extension to their normal roles to reap the benefits of AI. Instead, businesses need to focus on teaching employees how to understand the insights these systems generate, and then effectively apply them to make better decisions.
Getting started can be as simple as a series of short videos, but reskilling teams is an ongoing effort that requires buy-in from both leaders and the talent themselves.

These are no small tasks. If organisations in Europe and elsewhere are able to overcome these initial stumbling blocks, however, the benefits are there to be reaped. Across the study, organisations actively enabling AI confirmed are using the technology to power an entirely new wave of growth, while simultaneously reducing operational costs, increasing employee productivity, and delivering greater customer satisfaction.

Financial institutions in Europe that hope to mirror the success of other markets should be quick to consider these factors and achieve buy-in from their business earlier than their competitors in order to reap the rewards already being shown in their peers. To compete at the speed of thought AI will help to seriously level-up the industry – and best practice examples are already on display in APAC.