‘Big data’ is supposedly the latest hype. Financials have a huge amount of data on their clients, and with it a mine of information. Practically all banks and insurers have set up pilots to explore the possibilities, but are these efforts going to provide better products and services for clients?
Because of payments, a bank knows exactly on what a client spends his money, and where. A telecoms operator knows who his clients are calling, and for how long. A search engine keeps track of what’s of interest to a user at this particular moment, and a social network knows who their user’s friends are, and what subjects they like to discuss. Such data is a byproduct of the initial service the company is offering. The idea behind big data is that this information can be put to use in all sorts of ways to reduce cost and to maximize turnover and profit.
Big data is without doubt a hot topic. Because of this, a large number of ambitious data management projects that had been shelved during various crises have been revived. Every self-respecting financial is currently investing in tools and skills to analyze big data and pilots are being set up everywhere. Here are a few examples:
- An insurer is finding out at which locations most car accidents are situated.
- A bank is making thorough data analyses to find cases of fraud, but also to predict and prevent them.
- We also notice an impulse in CRM as a result of big data, in the sense of personalization, providing a more effective ‘next best offer’.
What all these efforts have in common is that they’re targeting further improvement in efficiency, for example by reducing risk or by perfecting marketing efficiency. Particularly in a period of ongoing struggle for cost reduction, it’s logical that this low-hanging fruit gets harvested first. We think that with this focus, companies are missing a great opportunity. After all, the real challenge is to use big data to get to know more about customers, and to use the information to deliver more than expected, create new services, and with it new revenues. Moreover, we think that if you want a better understanding of your clients, analyzing large quantities of data will not suffice. Ultimately, thinking from the customer’s perspective starts with a real passion for people, and with wanting to know what moves them.
A successful banker listens to his customers. Employees are selected on this capacity, and trained. You can only recognise deeper needs and act on them when you’re genuinely interested in people. This doesn’t mean that all big data efforts are useless. On the contrary, the point is to extract new insights from big data that lead to better conversations with customers, and more added value.
Exploring the possibilities of big data
Recently, we talked to a large international bank that has been globally active for more than 50 million clients in more than 30 countries, and who, as one of the few financials who do so, is investing substantially in innovation. This bank’s innovation centers are situated in Silicon Valley and at MIT, one of the top US universities. These innovation centers also explore the possibilities of big data using a tried and tested method: What are the deeper needs of customers, private and corporate? What knowledge lies hidden in the data that relates to those needs? How can we transform that data into new added value for our customers?
As a first exercise, it looked at what the bank could offer based on PIN payments customers do in shops every day. Two examples show us where that could lead us.
Imagine you own a successful chain of clothing stores and you’re considering setting up several new branches. The bank will know exactly where your current clientele resides and where they shop based on PIN payments, and even where look-a-likes are living and shopping. This will enable the bank not only to advise you where to set up new franchises, but where to advertise as well.
Suppose you want to surprise your partner and take them to a hip restaurant with a nice ambience, a good crowd, and somewhere reasonably priced. If you just look at one of innumerable restaurant sites, you may end up in a place with an average age that’s much higher than what you had in mind, and the bill could also be far beyond what you had anticipated. The bank, through all the PIN payments made there, knows exactly what the real age of the average visitor is, and what they actually paid at the end of the evening. This information could be easily passed on to clients through, for example, an app. Better information for clients – new added value.