New thinking on the value of Big Data for the financial services industry
Over the past few years, Big Data has had quite a run as a tech industry buzzword. But one problem with tech buzzwords is that the focus gets too myopic – as if one thing is the answer to everything. A sure sign of maturity is when the buzzword seeps into the background and people start to think more deeply about how it fits into the larger picture. This is what’s happening with Big Data. And for the financial services industry (FSI), this is a good thing.
At SAP we talk a lot about the digital economy – which has quite a bit to do with things like cloud, mobile, social media, analytics, the Internet of Things, and much more. Rather than something separate and out on its own, Big Data is now being seen as something that fits into all these aspects of the digital economy – and many organizations are beginning to see their data as a core corporate asset, like any other asset on the balance sheet. This is true across multiple sectors within FSI – including banking, insurance, and capital markets.
Retail banking: chasing the omnichannel dream
Take, for example, the dream of omnichannel in retail banking. Omnichannel refers to delivering a consistent and self-reinforcing positive customer experience across all customer touch points. This could be in-person, over the phone, online, through mobile devices, through social media, and more
The point is that banks should understand exactly who they’re interacting with at all times – and act accordingly. Let’s say you’ve been with a bank for a decade, you’ve never bounced a check, you have a mortgage with them, and you’ve brought several family members in as well. Shouldn’t you be up for some preferential treatment from time to time? Yes, that would be nice. But it turns out that banks find it hard to deliver this preferential treatment because they can’t quite see who you are.
Omnichannel, in other words, is a Big Data challenge. The holy grail of 360-degree customer visibility is attainable only when you realize the inherent value of your data by putting it at the fingertips of your workers – across all silos of operations in real time.
Doing this requires coordinated thinking rather than one-off approaches where individual business units pursue Big Data initiatives on their own. If you’re a bank, you need a corporate-level strategy for how you’re going to use Big Data to compete more effectively in the digital economy.
Insurance: now for something completely different?
The same is true in insurance. While omnichannel in particular isn’t quite as important in the insurance sector, the idea of thinking strategically about Big Data is. This is because newer companies (such as Google, Amazon, or MoneySupermarket) are stealing market share by using data to their advantage.
If you’re a traditional player and you want to survive, you need to catch up soon. But again, it’s not about implementing some Big Data tools here and there. Instead, it’s a question of how you can take all of the data and compute power available today to fundamentally rethink your business.
Here’s just one example: Let’s say you’re the insurer of manufacturing equipment and you partnered with an OEM to monitor equipment in real time. This would change things dramatically. Suddenly, you’re in the business of syncing up with smart devices, tracking high volumes of real-time data, and alerting customers of potential equipment failures. This isn’t really insurance coverage at all – but that’s exactly the point. In a digital economy, manufacturers may prioritize operational uptime over traditional insurance coverage – and insurers may want to put their data to work in a way that positions them to meet this need – or cede market share to those who will.
Capital markets: room for improvement with convergence
If there is one area of FSI where the value of Big Data has been consistently realized, it has been in the capital markets sector. On the one hand, this sector includes high-frequency traders who use mind-boggling algorithms to gain the slightest market advantage by executing millions of transactions instantaneously. On the other hand, it includes information providers like Moody’s or S&P where the issue isn’t market speed but the ability to troll through mountains of historical data to effectively analyze a company’s credit standing. If you’re in either of these camps, you know that Big Data is an old story indeed.
But perhaps there’s room for improvement here as well. In-memory computing, for example, now makes the convergence of these two worlds possible. Whereas in the past you had to choose between speed and depth of analysis, now you can do both. Now you can have granular and detailed data in real time – and simultaneously go back in time to merge this data with the historical record to make better, faster decisions. This can help companies comply with regulations better in real time, gain insight into the value of a particular trading pattern, or detect market signals faster than competitors.
But let’s not forget that a big part of capital markets is wealth management – and here is where Big Data can have even more impact. In recent years, the wealth management business has moved from advice and commissions to a fee-based structure where companies charge per transaction as customers can get all the advice and information they need on their own. This has started to erode revenue growth. To recapture that revenue, many companies are going after the “mass affluent” market instead of focusing exclusively on high net-worth customers alone. But the question is: How do you not only serve this market but also predict the value of customers in it? Big Data can help provide relevant answers with fast and deep analysis that can actually automate decision making processes regarding who you ultimately do business with.
The road to value starts with strategy
Just to reiterate – in case you missed it: The way to maximize the value of Big Data is to think strategically at the corporate level about how you’re going to use one of the most vital assets on your corporate balance sheet to help you do what you want to do as a company. What business do you want to be in? Where are your customers taking you? In what ways will you transform your business to take advantage of the digital economy in the future? Thinking at this level is what should come first. What you do with the vast potential and myriad opportunities presented by Big Data will follow.
In the Internet age, people expect to get data fast and cheap. For intel on how this affects the financial services industry, read Banking Must Be Real-Time And Near-Free.