How traditional high street banks must harness the power of big data to remain competitive
At the core of the challenge for banks is understanding their customer better and using the information effectively across the business, writes Thomas Mathews.
On my last count, individuals can engage with traditional high street banks through at least five different channels and I’m sure that I have missed a few. This has been an exceptionally positive development for the consumer as it has given them greater control and flexibility to bank how they wish.
This increase in control has also extended to the provider that they use, as it has become possible for consumers to switch banks in a matter of days and at the push of a button.
The result is that banks are under more pressure than ever before to ensure a consistency of service and to deal with poor experiences in an effective way, as well as expanding their offerings across the available channels to meet needs and expectations.
Promisingly, the industry is adapting to meet this challenge. However, they can do more and go further. In particular, banks are missing the additional commercial opportunities that these changes present.
So where can they improve?
Creating intelligent operations
The first challenge for banks is to try to understand which specific service(s) each customer uses, as well as how and why they do it. To do this, banks have begun investing in ‘big data’ tools to better understand their customers’ habits and preferences, especially through social media trends. For example, our know-your-customer (KYC) data management services centralises the management of data to a common standard, for more than 600 financial services firms.
By effectively capturing and analysing data in real-time, banks are able to improve their decision making processes and offerings by identifying patterns and opportunities for addressing customer issues and needs. However, they are currently being let down through the siloed nature of their businesses.
In many cases, banks’ business units are working in silos and information is not shared effectively. In addition, traditional retail banks have legacy IT systems and processes that are inflexible and unable to effectively respond. These banks need to reassess their operational structures to ensure that operations are intelligent and meet their needs. The key to address this is to leverage the “engagement” layer that sits between process and core technology applications. Systems of engagement can automate and improve processes, increase visibility with actionable reporting and real-time decisions, and generate better collaborations between teams.
The C-suite should engage effectively with issues and help breakdown organisational silos to bring together the right combination of stakeholders, data analysts, and information specialists to ensure a closed loop customer service experience approach.
Using big data and analytics to inform marketing strategies
Rather than just meet expectations, banks can use their insights to cross-sell and ensure their marketing strategies are targeted.
Big data is critical to this. It enables the banks to target existing and new customers with tailored, relevant products to cross-sell their services. For example, if a customer has a query about a banking service, they can be put in touch with the right point of contact instantly whether in-branch, over the phone or online.
Advanced analytics can build models to test hypotheses and provide a simulation of proposed business models and strategies. The result can not only produce better products and services but can create entirely new offerings for customers.
Improve the complaints handling process
In addition to this, many banks continue to struggle with the ability to capture unstructured and structured data around complaints. If a complaints handling protocol is not set up efficiently, unstructured data from in-branch visits and phone calls can slip through the net, causing issues to escalate and damage the bank’s reputation, therefore resulting in potential losses in customers.
Intelligent operational tools can help banks to establish efficient systems of data capture and remove silos, ensuring that there is internal alignment for analytics across different channels. Through the use of interactive voice response (IVR), the data can be measured to understand the root cause of the complaint and the customers’ needs. The root-cause is then fed back to the whole complaints handling team, resulting in a positive impact on the customer experience.
Big data technologies have evolved rapidly over the past few years, reaching critical mass only around 2011, and gaining increasing traction since then. Retail banks will continue to adopt big data technologies as an essential future investment so that they are able to stay one step ahead of their competitors, helping to retain their existing customer base and attract new ones.