By Simon, Sector Director, Business Process Solutions, DST
Big Data’s Expanding Role in Business
Big Data is more than just a buzzword. It is the result of the business world’s realisation that useful information is available almost everywhere, and that capturing and understanding as much of that data as possible will help companies improve how they do business. This is particularly true of the financial services sector, which has some of the most complicated customer relationships in the UK and handles vast amounts of data everyday, stemming from a wide range of sources, both inside and outside of the industry.
Across the financial services sector, there is an aspiration for a better understanding and use of the information available. This aspiration doesn’t usually manifest itself as a simple desire to improve a company’s relationship with data, but often as a frustration around an inability to secure effective Management Information (MI) or to treat customers as individuals in order to generate the most productive business relationships. Although the ambition is clear, many companies remain stuck at the first stage of this process; able to capture raw data from across the business, but not to convert it into a form that can be easily mined for specific trends, communicate the information effectively between different departments, or make use of it operationally. This is the biggest challenge for firms in today’s financial services industry, moving from a basic level of data expertise to an optimal approach that delivers a high level of return for the business.
Big data on a small scale
Simon Penny
Insurance Sector: Practical Big Data Examples
On a practical level, a good example of how maturing the relationship with data can deliver results can be found in the insurance industry. A small number of insurers are making great progress in building data profiles that are attached to individual customers and comprise the full history of interactions with that customer. These profiles are able to dynamically balance the value of the customer against the value of an individual deal, giving operators a specific margin in which to negotiate, whilst never losing sight of the company’s best interests. The more sophisticated of these systems can even differentiate between competitors, allowing more flexibility in competitive bids against some firms than others, depending on the current business strategy. This next-level use of data has clear advantages both in terms of straight forward profit margins, but also as a tool with which to gain competitive advantage. Across the industry, it is estimated that only 15-20% of firms are handling data effectively, with only one in twenty doing it optimally.
The ability to treat customers as individuals extends not only to the field of negotiations around a specific transaction, but across the whole customer relationship – from marketing to customer services. Ultimately, everyone wants to be treated as an individual and companies will have far greater success if they are able to exploit this. Data is helpful in two ways here: firstly, automatically collecting data on the types of communication that a customer interacts with and responds to can quickly establish an individual best practice approach for that customer. Additionally, a truly data centric company will take opportunities to offer prompts to customers as they use online or mobile account management interfaces. These prompts will provide minor details that will allow the company to keep its interactions in a style and format that suits both parties best.
Understanding the Rising Importance of Data
Why is data becoming so important?
The advantages of using data have become very clear over the past few years, and correspondingly, the enthusiasm of companies to capture these advantages has also grown. Although financial services as an industry is a little behind the curve compared to industries like retail, change is coming. Those who don’t climb aboard the data bandwagon soon will find that it may be too late. Technological changes on this scale, in an industry dominated by a web of legacy systems, will not happen over night, but the journey must begin somewhere, and many companies have already passed several important checkpoints.
New Pressures from Competition and Regulation
Furthermore, there is an external catalyst which is already generating incentives for the industry to speed up its adoption of data analysis. Financial services is facing serious competition from other sectors which are keen to expand into the sector. For example, cash rich companies with a strong customer loyalty base from the retail sector are already making headway. Initially this has been with white-labelled products and services, but as Tesco has already shown, the appetite to bring those products in-house is strong. Whilst some within the financial services sector would dismiss the threat from supermarkets, a report from research consultancy Rostrum Research last year showed that half of those surveyed trusted retailers more, or as much as banks when it comes to financial products. At the same time data experts like Google are building huge cash reserves that would allow them to hit the ground running if they turn their attentions to the financial sector. The understanding of customer behaviour and data that these companies boast should be a major concern for the old banks still being restrained by legacy systems.
A focus on change
Since the creation of the FCA just over a year ago, the pressure on companies to develop their data skills for the purposes of compliance and reporting has also grown quickly, offering yet another strong incentive for change. Without doubt, the time is right for all companies in the industry to think seriously about their use of information.
The Future of Financial Services and Big Data
The current generation of banks will need to become sharper, more customer focused and more dynamic to not only lead, but survive the future of the industry. It is entering a phase of rapid evolution, and any firm that rests on its laurels may be left behind.
