Big data – a vast pool of potentially invaluable information
Businesses – including banks – are constantly bombarded with a colossal amount of information, thanks to the ever-growing influence of the Internet. But how can financial institutions harness this information and start using it for their own purposes? Even finding and identifying the right information can seem like a headache – a bit like finding a stone in a raging torrent.
You need to know how to look and where to look. And then, when you have the information, you need to know how to use it to boost your profitability. This is an important area that Oracle’s been exploring in a recent report, “Responding to change – how are banks using information and pricing strategies to boost profitability?”
The details of this joint Oracle and Efma publication can be found in my previous blog, “Are you making the best use of information?”, which looked at how banks are using their existing customer information.
The potential of big data
However, there is a much wider pool of information that is now available and can provide some fascinating insights into customer behavior. So-called ‘big data’ includes both structured and unstructured data from many different sources – including the many social networks that have sprung up across the Internet in recent years.
Our study showed that much of this information remains untouched and unused by banks – and that relatively
few senior executives have really grasped its potential for transforming the profitability of their organizations. The amount of data being produced continues to increase exponentially – and the gap between this amount and its usage by banks is also continuing to grow. This is partly because the data needs to be properly identified and prepared first, so that it can then be analyzed effectively – and also because the skills and resources required are still scarce. Banks find it hard to keep pace with the volume of data being produced and are unsure how to use it effectively.
Using big data effectively
Our survey therefore looked at how banks are progressing in terms of meeting the challenge of using big data. On the positive side, it showed that most banks are now beginning to understand the importance of big data and the need to put it as a priority in their future planning strategies. Banks have very different approaches in terms of their big data journey. However, the vast majority are still in the planning stages or are only just beginning to find ways of using big data.
This finding was confirmed by in-depth interviews with banks from different geographical regions. For instance, a financial institution in Russia said that the big data journey was still in the very early stages. However, it hopes to develop its capabilities in the future – indeed, big data is high on the agenda for most of the banks in the region.
Two banks (one in the Czech Republic and one in the Middle East) said that they were also starting off on their big data journey – one with the idea of using data from non-banking partners and the other by developing analytical models.
In contrast, a bank in East Asia said that it doesn’t really have time to focus on this topic at the moment – and another bank in Central and Eastern Europe commented that it didn’t have a sufficiently critical mass of information.
We also looked at the types of big data that banks are using and how they are using it. Most seem to be augmenting their existing data with structured data, although there is a greater emphasis on unstructured data in the US. At the moment, big data is mainly being used for ‘quick wins’, such as improving decision-making and
enhancing the customer experience. Other areas – such as using the data to reduce fraud or to improve risk assessments – have been largely overlooked, even though these could lead to impressive returns for the banks.
No gain without pain
Unfortunately, the whole process of collecting, analyzing and using big data is an expensive business. However, it’s one that banks can’t afford to avoid. As a starting point, targeting can be a relatively easy and effective way of leveraging big data.
This might mean exploring customer interactions on channels such as social media in more depth, and using geolocation and other data to make the right offer to the right customer in the right location. For instance, offers can be sent to the customer based upon the retail outlets within their vicinity. This will also help the customer to engage more with the bank, and enhances their perception of the value of the bank’s services.
Ultimately, big data could open up a host of new opportunities for banks. The main question is whether they are both willing and able to take up the challenge. The key to success will lie in each bank’s readiness to invest more time and money in the big data journey. If the willingness is there, this could lead to great rewards in the future.