Many of us have put the 2008 financial crisis to the very back of our minds – it is a time we do not want to dwell on. However, it has been at the forefront of banks’ strategies and plans, with more investment put into ensuring regulatory compliance cost-cutting. This means that investment into technology and innovation has taken a back seat.
Banks are now concentrating their efforts on innovation strategies and new technologies that will help them to grow and expand. However, over the past few years, digital-first competitors —the bigtechs of Amazon, Google and Apple — and fintech companies, such as Square and Ally, have risen to disrupt traditional retail banking business models. As a result, the pace of innovation has shifted so that it is no longer controlled within the banking industry itself.
Bigtechs and fintechs have consequently reshaped customer demands by providing superior customer service through their ability to deliver personalised experiences in real time.
As banks fight against the new digital competition, they must invest in improving the customer experience. The benchmark for excellence in customer experience is no longer Bank A versus Bank B; it is whoever has the best app available.
Artificial intelligence in banking: Deliver on customer expectations
In a recent report, Gartner researched how banks intend to drive innovation efforts and found that better customer engagement, together with new products and services, are the top drivers for pursuing innovation within their organisation.
Additionally, according to the World Economic Forum and Deloitte, 76 percent of financial service industry chief experience officers agree that artificial intelligence (AI) is a top priority because it is critical for differentiation.
In retail banking, differentiation begins with client insight. Leveraging AI allows banks to connect and gather all historic and incoming customer data, no matter which channel it comes through, meaning physical locations, such as ATMs, web channels, digital wallets, point of sale activity and mobile devices. Next, it contextualises that information in terms of the customer profile that the bank has created based on its relationship with a customer. Once the activity is contextualised, it can be enriched and acted upon — whether that is through supporting the front line in engaging with customers or digital marketers in analysing the impact of campaigns.
AI allows banks to have actionable, 360-degree insights into customers’ activities. Banks can deliver on customer expectations more effectively and efficiently, upsell and cross-sell in a personalised fashion and predict future needs with AI.
A more personalised customer experience
Banks that don’t embrace AI run the risk of losing both existing and potential customers to competition that offers superior personalised experiences. However, with multiple channels through which to reach customers and the multiple underlying systems associated with specific banking products, it can be difficult for banks to consolidate real-time insights into customers’ activities, behaviours and preferences.
While the data is there, the key is knowing how to gather and leverage that information. Often, the two biggest obstacles that banks face are getting the data from across multiple internal systems, and knowing how to analyse and act on that data to enable the delivery of personalised, contextual messages and curated experiences within a matter of milliseconds.
Some critical aspects to consider when choosing an AI-powered solution include:
- Interaction with all established customer channels. A bank’s AI solution should be designed to monitor and facilitate real-time interaction across all existing channels and with its ecosystem in an agile, secure and scalable fashion. A bank’s call centre personnel should have full insight into a customer’s recent website visits and social media activity. This kind of integrated information sharing is crucial to a customer’s experience — in turn, this is crucial to a bank’s ability to cultivate long-term customer relationships. Customers do not want to have to recount history with their bank; they want their bank to know that history and to build on it to foresee their needs.
- Analysis and optimisation tools that facilitate process improvements. Few banks have the required insight to act in real time, not only when it comes to providing customer service, but also in terms of monitoring back-end systems. A bank should be able to analyse the underlying business processes, in addition to analysing a customer’s experience on existing channels. Doing so will allow banks to determine how effectively their existing processes operate, whether there are any bottlenecks, and then model and implement process optimisations across all of their physical, web, digital and mobile channels to serve customers more effectively and provide a great customer experience.
- Scalability and feature flexibility. As a bank’s customer base and ecosystems grow, an AI solution should be able to keep up and grow with the business instead of requiring new technologies at every stage of customer growth. In addition, any AI platform implemented should not simply be a point solution that only has the capacity to fix one set of problems. Rather, the solution should have the flexibility to address a variety of business challenges that banks may need to address in the future, for example, by maintaining compliance and identifying market fraud.
Many banks are still operating in a more traditional way. However, as a result of the increased adoption of AI technologies, it is now possible for them to join the digital world and remain competitive with some of the biggest digital players in the market.
At the end of the day – AI enables banks to provide a more personalised customer experience. It really is a no-brainer.
Verdict deals analysis methodology
This analysis considers only announced and completed deals from the GlobalData financial deals database and excludes all terminated and rumoured deals. Country and industry are defined according to the headquarters and dominant industry of the target firm. The term ‘acquisition’ refers to both completed deals and those in the bidding stage.
GlobalData tracks real-time data concerning all merger and acquisition, private equity/venture capital and asset transaction activity around the world from thousands of company websites and other reliable sources.
More in-depth reports and analysis on all reported deals are available for subscribers to GlobalData’s deals database.