• Yasmeen Ahmad, Head of Advanced Analytics and Data Science at Teradata


• 26.08.2016 10:00 am
undisclosed

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

This is especially true in retail banking, where new types of data are emerging as banks seek to transform themselves to reflect changes in consumer demand, threats from emerging fintechs and new payment mechanisms such as Apple Pay.

Indeed, as mobile devices such as smartphones and wristbands make more frequent appearances at tills, banks are making their entrance into 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 data they provide 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 take new analytical techniques required to find patterns and trends?

The advance of IoT

Consider how rapidly new payment technology is being integrated into IoT. Samsung, for example, is building a scanning and payment mechanism into its Family Hub smart fridges, which allows users pay for the items they order via the new “Groceries by Mastercard” app on the appliance’s touch panel. Even Fitbit has taken this route, integrating with Wellcoin to enable users to purchase rewards with their virtual currency.

As consumers gain access to more payment methods, such peer-to-peer payment on Facebook or SnapChat, a power shift occurs in the bank-customer relationship, putting greater pressure on financial institutions to use their new data to refashion customer relationships.

Big shifts in expectations

This shift in power can be seen in a popular chain of coffee shops that has collaborated with a telecommunications provider. This company is now using 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 in the retail and hospitality worlds, they will begin to expect banks to follow suit.

In addition to addressing customer expectations, banks will also have to make better use of their data in order to combat the insurgent threats from Apple Pay and online banking operators. Tech innovators and other third-parties communicating with customers threaten to take over the consumer interface. Losing direct contact with customers would present a serious liability to banks, taking away the opportunity to conduct individual marketing and making it more difficult for them to hone their operations.

In order to combat this rising threat, banks must adopt the same approaches to device data as manufacturers, maintenance providers and utility companies, where IoT data in the form of sensors is now crucial. Banks must integrate their IoT data from customers’ smartphones, mobile apps and other devices that come online with all of the insights they currently generate from traditional channels. 

This insights can be used to enhance the bank’s understanding of their customers’ needs and habits, extracted from effective analysis of every interaction made via website, phone or branch.

Making it work

IoT data stands out due to its granularity, which is capable of yielding immediate results. While cheaper storage methods have enabled the collection of large volumes of data, this in itself is not sufficient. Banks have notoriously disparate systems and must overcome the compartmentalised nature of their data before they can solve business challenges.

This data has to be queried and integrated using analytics at scale so that the customer journey is linked to a customer, revealing who they are, which 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’s attributes, such as its age, warranty, length of service and last maintenance point. This level of data integration is crucial for businesses looking to achieve real value – whether that business is an electricity generator, motor manufacturers or financial institution.

With IoT on the rise, banks must tap into and drive value from their data in order gain the precious insights to benefit their business. Without doing so, they risk being left behind and losing out to more agile and technologically-based competitors.