By Yasmeen Ahmad, head of advanced analytics and data science, Teradata

As a buzz phrase, big data may be as worn as a five-pound note in a bar on New Year’s Eve.

Where it once marked a change in focus, drive and investment, big data is now a term that embraces all data, big or small.

This is certainly as true in retail banking, as in other sectors where new types of data are emerging as banks seek to transform themselves in their struggle with changes in consumer demand, threats from fintech revolutionaries and new payment mechanisms such as Apple Pay.

Indeed, as mobile devices such as smartphones and wristbands are increasingly used to pay for goods and services, banks are entering the world of the Internet of Things (IoT), requiring them to reassess how they solve business challenges using data and analytics.

These new sources of information provide major opportunities for uncovering lucrative insights into customers and their behaviour, even if the big data is more difficult to interrogate.The question to be asked is whether banks are equipped to work new data types where source-complexity and formats hinder consumption, as well as new analytical techniques required to find patterns and trends.

The advance of IoT

It is not a theoretical matter. Consider how IoT is rapidly integrating payment technology. Samsung, for example, is building a scanning and payment mechanism into its Family Hub smart fridges, through which consumers can pay for the items they order using the new Groceries by Mastercard app on a touch panel.

In another example, Fitbit, the fitness tracker,is now integrated with Wellcoin, enabling users to earn and buy rewards with the virtual currency.

As consumers, particularly millennials, have more payment methods at their disposal, such peer-to-peer payment on Facebook or SnapChat, the power shifts in the relationship, putting greater pressure on banks to use their new data to refashion customer relationships. Consumers now have far more choice in how they approach and deal with their finances.

Big shifts in expectations

An example of how relationships are shifting can be found in the chain of coffee shops collaborating with a telecommunications provider. The company uses technology that picks up the proximity of customers through their smartphones and relays offers to them, allowing them to order and pick up their beverages without queuing. As consumers become more accustomed to this kind of service, so it will affect how they expect their banks to treat them.

In addition to customer expectations, the banks will also have to make better use of their data to combat the insurgent threats from Apple Pay and online banking operators. There is a danger for banks that it will be the tech innovators and third parties interfacing with customers who will start to own the consumer interface. Without this direct contact with consumers, banks will find it more difficult to hone their operations and lose opportunities to target individual marketing.

The vital role of IoT data

To combat this, banks in turn will have to adopt the same approaches to device data as manufacturers, maintenance providers and utility companies, where IoT data in the form of sensors is now hugely important. Banks must integrate their IoT data from customers’ smartphones, mobile apps and other devices that come online with all of the insights they generate today from more traditional channels.

The insights from IoT can be used to enhance the banks existing understanding of their customers’ needs and habits, extracted from effective analysis of every interaction via website, phone or branch.

Making it work

IoT data stands out because of its granularity, yielding immediate results. Yet while cheaper storage methods have enabled the collection of large volumes of data, this in itself is insufficient. Banks have notoriously disparate systems and must overcome the compartmentalised nature of much of their data if they are to solve business challenges.

The data has to be queried and integrated using analytics at scale so that the customer journey is linked to a customer – who they are, the products they use and their lifetime value. This is the context that allows a bank to assess the true customer experience.

In manufacturing, for example, a set of sensor readings from a machine is virtually useless if not accompanied by the machine attributes such as its age, warranty, length of service, last maintenance point and so forth. Data integration such as this is the key to unlocking value for banks just as much as it does for electricity generators or motor manufacturers.

IoT data is on the rise for the banks to tap into and drive value from, to the benefit of many aspects of their business, provided it is carefully managed so that analysts have the flexibility to integrate and continue uncovering hugely precious insights.