Barely a day goes by without the launch of a new report extolling the potential benefits of Artificial Intelligence in the banking industry, in cost reduction, operational efficiency, improved customer experience and, ultimately, bottom line growth. Indeed, analysts predict that AI will deliver a 22% reduction in operating costs (more than $1 trillion) across the global financial services industry by 2030, as banks look to transform both front and back office functions.
Established banks are recognising the need to respond to huge disruption in the market and to develop more agile operations to compete. Smaller players are looking to AI and automation as a way to scale quickly while keeping costs down, and navigating their way around skills shortages.
For many banks, AI has become something of a holy grail and, in their desperation not to fall behind, the danger is that banks start to invest in AI for all the wrong reasons; to keep up with the Joneses rather than to deliver against specific business objectives. The result of this approach is that organisations are too often jumping in at the deep end, looking to implement AI technologies within their operations, but without the necessary strategies or groundwork in place to reap the full benefits of the technology.
Focus on the outcomes, not the technology
The best way to approach and drive the maximum benefit from AI is, in fact, to try to put AI to one side and start by defining clear objectives and desired outcomes, whether that’s wide scale digital transformation across the organisation or process optimisation within a particular department or service. Once the objective has been defined, then you can work backwards from there, exploring the role that technology, AI included, can play in achieving the outcome.
Similarly, rather than thinking about AI as a new technology that is deployed wholesale across an organisation, banks are better served by thinking of AI as something that builds upon existing technologies and processes, and that they can work toward over time.
Build a strategic roadmap for AI implementation
If we take automation as an example, Robotic Process Automation (RPA) has been widely deployed by all banks for a number of years, to take out cost and streamline processes. But now, by integrating AI into their RPA platforms, banks can begin to move beyond the tactical automation of basic back-office tasks and processes, (in the contact centre, HR function or accounts department), to more complex and strategic initiatives.
Intelligent Automation (IA), which combines RPA with AI functionality, and additional capabilities such as Natural Language Processing, enables banks to automate a far wider range of workplace processes, in a fast, effective, and secure way. This means being able to understand and interpret unstructured data across channels such as email and being able to make intelligent decisions based on historic data.
With AI, digital labour and automation moves from being primarily a cost reduction exercise to becoming a strategic asset to change and optimise the way that banks run their entire operations. And with this shift, the benefits become greater—increased productivity, more robust regulatory compliance, enhanced capacity, more fulfilling work for staff, and more agility and scalability of resource across the entire organisation.
We talk about three waves of adoption. The first wave of RPA deployment is about cost reduction efficiency. But once you add in AI, organisations can progress onto the second wave, where automation and digital labour drive improved business performance, and the third wave, where the technology delivers genuine business transformation.
Indeed, as automation moves beyond high-volume processes, the relationship between human workers and digital labour becomes critical. The success of any AI or intelligent automation programme depends on the knowledge and understanding of staff, and their appreciation of the role that a virtual workforce can play in supporting them.
This is why it’s essential for banks to adopt a measured approach to AI adoption, ensuring that they build the right skills and cultures within the workforce along the way, so that the introduction of AI becomes a natural progression on their digital transformation journey.
Beyond the hype—how AI is really making a difference
With the right approach, where AI and technology deployment is aligned to wider strategic objectives, AI has the potential to radically change how banks operate, both internally and externally.
Already, we are seeing banks that are using AI (for example, chatbots) to deliver a highly optimised customer experiences while providing a level of data-driven service and personalisation to all customers that was previously only available to a select few. Elsewhere, banks are deploying AI as a way to manage an increasingly vast and complex compliance landscape, ensuring consistency and accuracy in the way that all transactions are actioned, monitored, and reported, leading to a higher degree of certainty and reduced risk.
Another area where banks are now using AI to great effect is within fraud detection and prevention. The ability of AI to sift through massive amounts of data, 24 hours a day, and identify patterns is one of its greatest strengths, allowing banks to detect fraud and take appropriate action in real-time.
Select projects that deliver value faster
AI and automation will enable banks to redefine their resourcing models, allowing them to do what they already do in a more cost-effective and efficient way. But, more importantly, as their use of the technology matures over time, AI will be the catalyst for innovation, growth and genuine differentiation in the market. That’s where the real value of AI lies.
Therefore, it’s essential that banks adopt a long-term strategic approach, deploying AI and intelligent automation where they can deliver most value now, but ensuring that they have the skills, culture and governance to navigate the upcoming AI journey in the future.