It’s time for banks to lead with insights driven innovation
According to a recent IDC report, the size of the global datasphere will be 175 zettabytes (ZB) in 2025.To put that number into context, 175 ZB is comparable to watching the entire Netflix catalogue more than 489 million times. The tremendous data explosion has helped technology giants like Amazon, Google, and Facebook generate vast revenues and profits. The tech giants have monetized the enormous amounts of information they get from their users – their search habits, the posts they share, the products they buy, or the music they listen to.
These companies are not only among the top 10 most valuable companies in the US for the last three years, they also figure among top 10 in BCG’s most innovative companies 2018.
So how are these companies using data to drive innovation? Google Assistant and Alexa are continuously getting better at understanding what we say because they always keep learning. When we accept Google Assistant’s suggestion, it’s a feedback that it got it right. And when we surf away from Amazon’s product recommendation, it’s another feedback that we didn’t like the suggestion. Waymo – Google’s self-driving cars are getting better through the analysis of billions of data points collected as the self-driving cars roam the street. This feedback data is incredibly valuable because it is the raw material that feeds into machine learning tools; it’s the very resource that fuels data-driven innovation. And the more you have, the better you get.
So while the opinions may be divided as to whether data is the new oil or not – it is evident that data is rapidly becoming the essential raw ingredient to power future innovation. But if innovation is increasingly being driven by data, the tech giants stand to benefit the most as they are the ones that have access to the most data. This would in-turn help these firms get more customers, get more data and do further innovation. There’s a growing threat of these tech giants becoming a concentrated group of mammoth data-driven innovators leaving smaller competitors and start-ups languishing. And red flags are already being raised about this to ensure that markets stay dynamic and competitive. While the technology may be new, monopolies and anti-trust situations are not new for example the US Government took action against both Standard Oil and AT&T. Both were broken up into multiple entities because they had attained near-complete dominance of their markets. Today’s tech giants enjoy similar levels of market dominance, so each of these companies could, perhaps be called monopolies. However, to win on anti-trust grounds, the government must show that the company’s market dominance is harming consumers in some way – by either artificially raising prices or stifling innovation. That is a difficult argument to make when Facebook and Google’s consumer products are free, and Amazon’s dominance is due in large part to a combination of low prices and free shipping to its millions of Prime members. Plus, all three companies are among the most innovative on Earth.
It is a serious concern for the banking industry too as these tech giants have already started eating into banks’ revenues and margins. As per a recent report from Bain, Amazon could rapidly grow banking services to more than 70 million US consumer relationships over the next five years or so—the same as Wells Fargo, the third-largest bank in the US. Another survey has indicated that two-thirds of Amazon Prime customers are willing to try a free online bank account offered by Amazon. Even among people who don’t use Amazon for e-commerce purchases today, 37% would try.
So what can the banks do?
Banks would do well to up their game in order to counter the threat posed by these tech giants – they will have to overcome not just scale and network effects but also the data-driven feedback effects.
Banks should consider capitalizing on their strengths – leveraging the assets they already have and tech giants don’t – deep understanding of regulations, longevity in banking business and the reputation of being trustworthy and reliable. They could look at combining those assets with advanced digital capabilities in order to outmanoeuvre the tech giants.
The recent backlash against the way big tech monetizes customers’ data for their profitability and instances of failing to keep the customer data secure and safe, may help the banks. Being seen as more responsible may earn banks the right to do more with the treasure trove of customers’ data that they hold. If banks can leverage the data to help their customers save, meet their needs better, and reduce their stress – then they will trust banks with more data and the cycle continues.
Banks have access to a wealth of customer data, including detailed demographics, website analytics and records of online and offline transactions. Banks could grab the opportunity to make most of this advantage and put customers first – meeting their needs in innovative ways by leveraging this data rather than pushing products. By applying deep understanding, reasoning and learning in real time they can uncover new patterns and make unlikely connections for new, actionable insights. In this way they can become more involved in their customers’ lives, extract insights into how its customers’ lives are changing—whether it’s time for a new car, college tuition or a different kind of account—and then use those insights to craft highly targeted cross-selling offers that hit the mark. Utilizing the behavioural data they can advise individual clients on appropriate credit and savings products, based on their goals and habits. The ability to make contextual decisions and deliver personalised experience using real-time data could well be the key to counter the challenge. This would make the customer feel empowered and in control of the experience, deciding when and how they will interact with their bank.
To drive such contextual decisions and personalisation at scale, it is essential to have the ability to both access and process large amounts of disparate data—including customer, transaction, and where allowed third-party data—on an ongoing and repeatable basis. However, harnessing data from internal and external sources and developing the necessary machine-learning algorithms to drive the right customer-level interactions are beyond most organizations’ current capabilities.
Banks could stand to gain by boosting their ability to extract value from their data assets by building proprietary data sets, securing permission from customers to collect and use their data, and entering partnerships to acquire complementary data assets. In addition, they could build or acquire the tools, talent, and processes to extract insights from this data to drive personalized interactions. Legacy infrastructure and business processes might not be all bad, but where they don’t support rapid innovation and the full use of data in real-time, they certainly represent a barrier. Banks would therefore do well to free themselves by choosing the right set of AI powered technologies that can help them leverage the real-time data and also seamlessly interact with the banks’ ecosystem partners. Banks could then overlay these new technology capabilities with their unique advantage of having vast experience and expertise of their bankers which is their ‘’secret sauce”.
While doing all this will make the Banks better prepared to keep the tech giants at bay, the key to their future potentially lies in a fundamental change – unlocking a mind-set of continuous innovation. A mind-set that leverages their strengths and enables them to organize around how customers experience their business, rather than the internally oriented approach to organizing around products, channels and functions. Banks have long played a tremendously important role in the development of our world and with these changes they can continue, indeed enhance that role.