The current narrative regarding artificial intelligence is that it’s mostly a cost-cutting technology that will allow banks to replace a segment of employees with highly efficient algorithms, leading to massive job loss. That mindset is wrong.
AI is a transformational technology for financial services — on par with internet banking and mobile check deposits. The death of the bank branch and teller has long been predicted, yet banks continue to invest in the branch of the future, staffed with humans helping customers. AI will fundamentally change how we work, and it will benefit employees, enabling them to focus on personally fulfilling and challenging tasks while cutting out the mundane, repetitive ones.
Banks looking to successfully deploy AI will need to rely on a vibrant workforce that is retrained and refocused to work in tandem with AI. In fact, it won’t be artificial intelligence that will be deployed, but rather “applied intelligence,” with machines and humans tackling responsibilities together.
Most employees will welcome the evolution. Banks, to date, have largely underutilized their employees, spending time and money hiring and training individuals who handle rote functions — reconciling trade information, transferring customer requests from one database to another, maintaining regulatory records and answering phone calls about credit card fees. Even after decades of technological advances, much of the bank workforce is still dedicated to transactional responsibilities today.
AI will take back the rote functionality that occupies too much of bankers’ time, unleashing them to use their inherent creative and dynamic abilities.
An Accenture analysis indicates that by 2022 banks that invest in AI at the same rate as top-performing businesses could boost revenue by an average of 34%. And, contrary to the belief that AI is a job destroyer, those same investments will come with an average 14% rise in employment. This job creation will come primarily from the continued general correlation between the increase in gross domestic product and job creation. By 2035, AI
Bank employees seem to recognize the potential for such benefits. Nearly three-fourths of the 1,300 bank employees we surveyed expect AI to make their jobs simpler, two-thirds forecast it will improve work-life balance and a majority expect it to expand their own career prospects.
Yet between now and that robust AI-bolstered future, there are concerns that AI will destroy jobs. The World Economic Forum projects that 5 million jobs will be lost in the top 15 developed economies within the next 24 months.
But those projections do not paint the full picture. More accurately, AI will displace jobs in some areas while creating an equal amount of new jobs elsewhere. The losses will be largely among the transactional workforce, while the direct gains will be in skilled AI-related positions.
This includes AI “trainers,” those who program and model AI, the “explainers” who determine the context for AI to operate in and “sustainers” who evaluate machine outcomes, performance and promote and demote AI systems
This issue isn’t one of near-term job destruction, but of potential job mismatches. The displaced workforce will need to be retrained and roles will need to be reimagined in coming years. Our recent discussions with more than 1,200 banking leaders indicate that more than 90% expect these shifts and plan to retrain and redeploy their workforce as needed.
The challenge for executives is figuring out the specifics of retooling their organizations to effectively utilize their existing workforce. This involves identifying employees who are the best candidates for self-directed reskilling, teaching new skills to others, promoting deep learning for career improvement and providing the support and autonomy necessary for retraining.
AI can help the financial industry by improving the work employees do. For example, it can make a big difference in call centers — which traditionally struggle to find and keep workers — by handling simple transactions. However, when the system identifies a caller through emotional and language cues who needs a more personal touch, it can route the call to a human. That person’s ability to show empathy, coupled with being empowered to make intelligent decisions, will lead to better customer and employee satisfaction.
Another example is in the audit function. For items such as expense or time-card entries, the typical process has been to the audit team select entries at random and examine them in detail. The team spends time and effort to rectify errors, including figuring out how to claw back money that has already been dispensed.
By implementing a system of robotic process automation applied to all entries, algorithms can flag the inaccuracies before money is paid out. Now, instead of auditing a sample of entries, all entries are examined, enabling the auditors to spend time investigating those items the system has flagged and exercising their judgment — eliminating the mundane and maximizing their skill set.
In fact, we’ve implemented this process internally at Accenture. Employee turnover in our audit department has drastically decreased and we have fewer expense errors — ultimately lowering the overall cost of the audit function. As a result, we’ve increased the number of people employed in our internal audit teams.
This is a model that will eventually extend to all corners of the financial services industry, creating the conditions for more efficient businesses and happier workers.
