Success With AI in Banking Hinges on the Human Factor

Artificial intelligence has the potential to transform customer experiences and establish entirely new business models in banking. To achieve the highest level of results, there needs to be a collaboration between humans and machines that will require training and a reassessment of the future of work in banking.

There is little argument that digital technologies and artificial intelligence (AI) are transforming every industry, including banking. These changes are impacting the way back offices operate, how services are delivered, as well as the revenue and cost structure of banking. For most organizations, the desire to modernize with digital technology and AI is a balance between wanting to reduce costs/increase revenue and wanting to improve consumer satisfaction.

But, the benefits of this transformation are different than the traditional paradigm of automation, where machines improve process efficiencies and lower costs. There is evidence that when AI is combined with human logic, creativity and capabilities, both humans and machines will achieve much more.

According to Accenture, “Between 2018 and 2022, banks that invest in AI and human-machine collaboration at the same rate as top-performing businesses could boost their revenue by an average of 34% and their employment levels by 14%.” This perspective was shared by banking executives who were surveyed by Accenture. Three out of four of the senior banking executives believe the industry will be completely transformed by intelligent technologies, and 67% of executives expect AI will result in a net gain in jobs within their bank in the next three years.

“As AI becomes more nuanced, its role in banks is moving beyond automation to elevating human capabilities,” said Alan McIntyre, a senior managing director at Accenture and head of the company’s Banking practice. “To benefit from the potential of AI, banks need to implement ‘applied intelligence’ – combining technology and human ingenuity – across all areas of their core business,” added McIntyre.

Roadblocks to AI and Human Collaboration

Despite the belief in the benefits of AI, the application of AI across the industry has lagged expectations. Much of the use of intelligent technologies has represented iterative advancements in areas already accustomed to machine learning (fraud, risk compliance and efficiency areas of the bank), as opposed to generating positive disruption in areas that impact consumer experiences.

The one reason why banking operations aren’t relying on AI isn’t because of the unwillingness to adapt to change. Rather, the industry lacks the right talent to drive that change.

There is a significant disconnect between the recognition of a need and an appropriate response. The Accenture research found that while executives believe that most of their employees are not ready to work with AI, only 3% of executives are planning to increase investments in retraining workers in the next three years. This is unfortunate since employees indicate that they are not only impatient to thrive in an intelligent enterprise that can disrupt markets and improve their working experience; they are also eager to acquire the new skills required to make this happen.

“Banks’ lack of commitment to upskilling and reskilling employees to learn how to collaborate with intelligent technologies will significantly hinder their ability to deploy and benefit from them,” McIntyre explained.

Senior executives also indicated a perception that their employees are resistant to the introduction of artificial intelligence. In reality, most employees believe that AI will have a positive impact, making them more interesting (61%) and creating new opportunities (67%). Employees are also confident that they will be able to work with AI (88%) and understand the importance of developing new skills (75%).

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AI Impact on Jobs Goes Beyond Numbers

The impact of AI on banking jobs goes beyond simply gains and losses. Most understand that the most significant impact of AI won’t be on job counts, but rather on the types of jobs impacted. In the Accenture research, 40% of the banking executives surveyed said that AI will transform the workplace. A similar number said traditional job descriptions have become obsolete as machines take on routine tasks and as people move to project-based work.

With regards to more complex roles, 27% of banking executives reported that they’ve extensively redesigned jobs, indicating the impact of technology across organizations. In addition, 62% of senior bankers said the proportion of roles requiring people to collaborate with AI will rise in the next three years.

Reimagining the Future of Work

“While there is no doubt that getting human-machine collaboration right is critical to achieving their goals, few banks have adopted a systematic approach to unlocking the value that lies at the intersection of people and intelligent machines,” according to the Accenture research. While it is clear that training is needed, a biggest barrier may be the lack of clarity around the skills that should be prioritized. The research indicates that the key is to move the focus from ‘jobs’ to the ‘nature of the work’ itself before preparing workers with the necessary skills.

The will require an assessment of tasks performed (as opposed to jobs), creating new roles that leverage AI, and mapping the skills available to the new roles. The gaps can be addressed through training or sourcing. In this process, banks should focus more on how the work can best be done than on the roles and responsibilities that make up the work.

The Power of AI and Human Collaboration

Banking executives recognize the power of AI and humans to collaborate to create new customer experiences and business models. As a result, many banks are moving from the prototype stage of development to larger-scale applications. This said, banks must resist the pressure to capture only short-term market advantage.

According to Paul Daugherty and Jim Wilson, authors of the book ‘Human + Machine: Reimagining Work in the Age of AI’, “The opportunity for newly skilled individuals to collaborate with increasingly intelligent machines and software will accelerate the shift from an assembly line approach to a more fluid ‘assemblage’ of teams and technology, capable of higher levels of creativity and innovation.”

The growth prospects of the AI revolution are not limited to immediate outcomes, but the need to move forward is immediate. The speed of the digital revolution is unprecedented. According to Gartner, deep learning and machine learning – two key emerging AI technologies – will reach mainstream adoption within two to five years. If organizations want to benefit from these opportunities, there is a need to take action … now.

A key part of this strategy will be to reimagine the future of work in banking, and to start moving toward a state of advanced AI collaboration. Or, as stated in the research report, move toward a model of humans helping AI to help humans.

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