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Big Data 29 May 2020

BBVA's data wrapping - what does it mean?

A recent article by MIT Sloan Management Review highlighted the innovations in data wrapping that companies like BBVA and PepsiCo are pushing into the markets.

But what is data-wrapping, why is BBVA using it, and what benefits does it bring to the bank’s customers and shareholders?

In simple terms, data wrapping involves adding more data-driven insight to the products and services you offer customers to, as the MIT report states: “delight customers and increase profitability.”

That quote from MIT also neatly sums up the reasons for doing it for customers and shareholders too. Firstly, to give a better user experience to your customers and clients, by helping them better understand the product they have with you, or the service they contract from you, through data-driven explanations.

Secondly, though, because the more you can do for a customer or clients, the more they are likely to take further products or services from you – or to recommend you to others – which in turn increases profits, delivering better returns for shareholders, from individual investors through to big pension funds.

It was this value-add that data can impart which BBVA Chairman Carlos Torres Vila outlined as far back as 2017. He noted how by applying intelligence to data, it is possible to generate the type of value added recommendations that can help the company earn its customers’ trust, thus closing the circle.

So what does this look like in practice? Well again, MIT gives an example using the Financial Health tools embedded in BBVA’s mobile app. The MIT report – called Why Smart Companies Are Giving Customers More Data and which can be read in full here – states: “In 2016, Spanish banking group BBVA offered to its Spain-based customers a personal finance management app.”

“One of the app’s tools used machine learning algorithms to sort customer transactions into common budgeting categories such as rent, food, and entertainment, and then it displayed a customer’s expenditures broken down as a simple chart.”

“BBVA promoted the categorizer on its digital banking website as a way for customers to better manage their personal budgets. In just a year and a half, the tool became the most utilized feature on the BBVA website, second only to funds transfer.”

This data-driven insight is part of BBVA’s commitment to providing its customers with the tools they need to make their money go as far as possible.

“Data and Analytics are crucial in order to give our customers personalized experiences that are really meaningful for them”

In February this year, the bank’s Chairman Carlos Torres Vila, emphasised the centrality of this to the bank’s future when he announced BBVA’s six new strategic priorities. At the heart of these were commitments to work hard to improve peoples financial health, and to help people transition to a more sustainable future.

The tools themselves are an output of BBVA’s focus on using the data it collects on behalf of its customers in a smarter way. This is enabled through two elements. Firstly, the bank’s algorithms are able to better assess what people are spending money on in terms of categories individually – and show customers that data-set a succinct, easily understandable, and easily actionable way.

But secondly, it also allows for socio-demographic comparisons too – comparing spending with other people who are similar in terms of age, sex, earnings and postal codes. This allows customers to better understand if they use their money in markedly different ways to others, which can help change less financially-healthy behaviour.

Commenting, BBVA’s Client Solutions Head of Advanced Analytics and Data, Elena Alfaro, said: “Data and Analytics are crucial in order to give our customers personalized experiences that are really meaningful for them”.

“The insights we can build from the data we see can, and do, make a real difference to how people save for their futures, how they invest wisely, how they reduce expenditure or how they change their spending habits to help them achieve an ambition or a goal.

“This is equally true of business customers, who can better predict their money flows, price products better, manage supply lines, just to name a few things.

“It is the reason BBVA led the banking world’s push to employ data scientists and created sophisticated expertise like our AI factory as well as our distributed Data Science teams among countries and functions. And it is a service that is only just getting underway – how we will use this expertise to support better financial health in the future will be astounding.”

For PepsiCo, the report notes how the company launched a suite of data analytics capabilities – called Pep Worx – designed to support retailers make more profitable sales.

The report adds: “PepsiCo has used Pep Worx to help transform the nature of its retail customer relationships from transactional to collaborative by creating a “three-audience win” whereby sales or marketing activities simultaneously deliver value for the shopper, the retailer, and PepsiCo.”

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