A recent report by Accenture has releveled that only 12% of the 160 retail and commercial banks they interviewed have fully committed to digital transformation. According to the survey, 50% of banks have made little progress and the remaining 38% are in the midst of their transformations but their digital strategies lack coherence.
While the study found that those banks who had invested most heavily in digital services had generated greater profit, this was largely due to cost savings rather than an increase in revenue. So where is the financial sector going wrong? Do they need to increase their technology budget? Do they need to adopt a more risk-taking approach to innovation and new business models and are the right people driving the transformation?
Digital transformation in banking isn’t just needed, it’s expected. Consumers around the globe now expect their banks to act and interact more like top technology brands. The likes of Amazon and Google have become the gold standard for digital engagement meaning many consumers now have a stronger emotional connection with these brands than they have with banks. So if banks want to keep up, they have to engineer a winning digital experience to build emotional connections, which ultimately, could translate into sticky interactions and more profitable customers.
It sounds like a complete a no-brainer so why are so many banks still yet to get their digital transformation strategies off the ground?
Research suggests, many traditional banks are so focused on keeping the lights on that they fail to execute their innovation goals. Keeping a bank running profitably while satisfying the regulators is no easy task, meaning transformation initiatives often get pushed down the priority list.
In the race to deliver transformation, many banks fall at the first hurdle. Their main competitive advantage – the rich data they possess about every aspect of their customer’s financial needs – is often siloed across multiple legacy systems and managed by different departments. The task of consolidating data and establishing a central hub for business analytics is expensive, time-consuming and diverts valuable resources from run-the-bank activities.
But the challenges don’t end there. Automation is often viewed as an unwelcome concept for decision-makers, especially those who manage large teams and have spent years building up expertise around the bank’s legacy systems and manual processes. They understandably fear they, or their team may be made redundant.
These are only a couple of the challenges being faced by traditional banks and it’s easy to see why they find digital transformation painful. But when they do embrace change, the benefits can be huge.
Banks that adopt a disruptor mindset recognise that machine learning and artificial intelligence are powerful tools. With the right approach, these banks can use the same technologies to both drive transformation initiatives and streamline day-to-day operations, creating a virtuous circle.
For example, analytics-powered automation is not just a tool to eliminate paperwork and reduce headcount. By freeing up time, it can also help employees focus on high-value transformational tasks, revealing new opportunities for product development and highlighting ways to build more customer-centric services.
Analytics are also key to transformation and it’s one of the unique competitive advantages that large, well-established banks have over their new start-up rivals. Armed with millions of customers who trust and value their services, these banks can accumulate a vast amount of incredibly rich data about customer behaviour. And since modern analytics techniques such as deep learning are extremely data-hungry, the banks with the most data will be able to build predictive models that are far more sophisticated and accurate than their competitors. This could prove to be a decisive advantage as AI initiatives begin to take centre stage in transforming customer service.
Recent success stories illustrate the very real rewards that banks can reap from digital transformation:
Nationwide recently launched a project using AI and natural language processing of customer emails. The building society identified the communication methods that produced a positive reaction and those that created frustration. The analysis revealed that 26% of all interactions could be moved to an online process, reducing waiting times for customers while saving time and resources. What started as a proof of concept has now become a companywide initiative to use data analysis to streamline its back-office operations, develop new products and evolve its services.
RBS is combining analysis of big data, including unstructured and textual data, to develop a much clearer picture of complaints so it can deliver a faster resolution for customers. By creating a link between the complaint data and customer interaction data, RBS has been able to identify and address service or process failures.
For example, a customer who isn’t able to cancel a direct debit within 24 hours may be satisfied with the service that an agent delivered but unhappy with the process. By having the relevant data available in a single dashboard, RBS is able to identify the issue and respond with improvements to the process, branch or team.
While some of the traditional financial giants are beginning to unlock the potential of innovation, many are yet to follow. Competition from those keeping pace with digital transformation, as well as the wave of next generation digital disruptors such as Monzo and Revolut are offering new types of services that eat into the most profitable parts of traditional banks value chains – meaning the race to innovate really is on.
To find out how the Development Bank of Singapore transformed their organisation to be named “the best bank in the world” click here.