While AI is not widely in use by most financial institutions, new research by The Economist Intelligence Unit shows 86% of banks and insurance companies plan to increase AI-related investment into technology by 2025
AI is set to shape the future of the banking and insurance ecosystem, according to a new report commissioned by ThoughtSpot, the leader in search and AI-driven analytics. The report, “The Road Ahead: Artificial Intelligence and the Future of Financial Services,” conducted by The Economist Intelligence Unit (EIU), analyses the sentiments of 200 business executives and C-suite leaders at investment banks, retail banks, and insurance companies in North America, Europe, and Asia Pacific.
The study found that while there is a strong degree of confidence in the benefits of AI, the reality is that the technology is not largely in use: more than half of respondents say AI is not incorporated into their business’s processes and offerings, with only 15% saying the technology is used extensively across the organisation. However, the benefits that have already emerged combined with respondents’ plans to double down on AI investment in the short-term show this technology is slated to drive a massive wave of future growth for the financial services industry.
AI Drives New Growth for Financial Services
Banks and insurance companies perceive AI as critical to unlocking new growth opportunities and reducing costs. Respondents were clear AI will transform their business in a number of ways over the next five years, including spurring new products and services (27%), opening up new markets or industries (25%), and paving the way for innovation (25%). About one-third (29%) of respondents expect between 51% and 75% of their workloads to be supported by AI technologies in five years’ time.
In addition to driving future growth, AI technologies promise significant savings both today and in the future: 37% of respondents report that their organisation has reduced operational costs as a result of AI adoption and use, and another 34% predict that AI will lower their cost base over the next five years. When it comes to other benefits of AI, one-third of respondents each reported a greater use of predictive analytics (34%), increased employee capacity to handle workload volume (33%), and enhanced customer service and satisfaction (32%).
The Path Forward: Upskilling The Frontline Workers
Despite relatively slow adoption rates to date, the promise of AI holds clear with 86% of respondents saying they plan to increase AI-related investments into the technology over the next five years. However, greater AI adoption will ultimately be driven by how much financial services organisations invest into upskilling their workforce. This upskilling across the organisation is required to get real value from democratising insights.
According to the data, the industry is at a halfway point when it comes to upskilling their employees, with 49% of respondents saying training initiatives for employees to better understand AI are currently in place. Another 42% have plans to implement such training.
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“We’re already seeing the massive impact AI is having on financial institutions’ businesses by reducing costs, but more importantly, driving new growth. The rapidly rising AI adoption and training rates are a clear precursor of the AI revolution that is set to unfold over the next five years,” said Sudheesh Nair, CEO of ThoughtSpot. “AI is the new growth engine, and the key to unlocking its potential requires investing in talent. Financial services companies must train and reskill employees to capitalise on the productivity and innovation gains made possible by AI.”
“AI has the potential to truly transform the banking and insurance industries,” said Dr. Katya Kocourek, Managing Editor, Thought Leadership at The Economist Group. “The research shows the strides that are already underway and the path forward that will boost the industry to the next phase of AI adoption. Like any potentially transformational technology, it will not be a path without risks, but the impact on the future of banking and insurance is clear and promises to deliver a world of value.”
Investment Banks, Retail Banks, and APAC Firms Emerge as AI Leaders
Investment banks are deploying a higher volume of new AI applications on average when compared to their retail bank and insurance peers. They are also the most advanced when it comes to the implementation of training programs: 54% say they have already implemented training initiatives, compared with 46% in insurance and 48% in retail banks. Additionally, investment banks are most likely to use machine learning (63%) and image analysis (52%), whereas retail banks are more heavily tapping predictive analytics (71%) and virtual assistants (61%) within their organisations.
The report also found that banks and insurers in the APAC region are trendsetters when it comes to adoption, training and measurement. Sixty-one percent of all APAC respondents reported that half or more of their workload is supported by AI, compared with North America and Europe (both at 41%). Europe’s low usage rate is partly a reporting problem: almost 10% of European respondents either had no metrics to measure AI-application success, or they had not been measured for long enough to report on. By way of contrast, all APAC respondents had functional reporting metrics. 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 37% in Europe.
The APAC and North Americans regions expressed the strongest optimism regarding plans for AI-related investment into technology: 90% of APAC and 89% of North American respondents say they plan to invest over the next five years, compared with 75% of European respondents.
Challenges to Overcome
While the long term outlook for AI in financial services is bright, organisations do have concerns in realising those benefits. The research found 40% of organizations cite risk, specifically security as the greatest area of concern, more so than cost (39%), insufficient infrastructure (29%), and poor data quality (28%).
Only half (52%) are confident about their preparedness to address AI-associated risks like security, and 55% have developed policies, procedures and oversight processes for AI-based automation, highlighting the need to invest in solutions and policies that protect governance and security while mitigating.