How to strike oil in data exploration

The digital bank of the future will immediately recognise who you are, no matter how you’ve chosen to interact with it. It will understand what problem you are trying to solve but also how that fits into your overall financial position and ambitions.

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It will automatically add value to the transaction – maybe via detailed information around a purchase or recommending how you may do something differently to your advantage. 

"Growing awareness around privacy breaches and data security will drive greater regulatory scrutiny - and that can be expensive.” 

Fundamentally, it will be trustworthy in protecting your data and in its interactions with you.

That bank doesn’t yet exist but understanding the critical building blocks is vital to the strategies being undertaken today to get there. And it’s something banks globally are grappling with.

The mistake is to think these strategies are about technology. Technology is necessary but far from sufficient. What is essential is fully understanding what customers want – which is where disciplines like ‘human-centred design’ come into play. And then delivering it.

Underlying both these fundamentals elements is data. The buzz phrase of the moment is ‘data is the new oil’. It’s quite a good line but for the sake of a nice line it oversimplifies the challenge.

Organisations like banks have plenty of data – they don’t have to wildcat to strike oil – but what they lack is the ability to turn it into valuable final products for customers. They lack refining capacity perhaps.

That’s because the data itself may be highly impure, it may be locked in reserves which are expensive to tap, key pieces of production infrastructure may not link up well. There’s a host of challenges.


As highly regarded financial services commentator Chris Skinner noted recently in a column on British startup bank Monzo, “a big bank with legacy architecture can only tell customers what they’ve spent”.

“Their back-office systems are pure transactional ledgers of past payments,” he wrote. “There is no intelligence, forecasting, predictive analytics or machine learning about customer behaviours, because the data is all fragmented across multiple, legacy, product-focused, silo-structured systems.”

“This is the big banks soft underbelly and a weakness that the young start-ups are clearly focused upon exploiting.”

It’s certainly true a data-enriched experience is something many fintechs see as an advantage; and it’s certainly true traditional financial institutions face a challenge with legacy systems and data.

The real question though is how quickly those traditional banks are reacting.

It’s also important to recognise traditional banks do have some strong advantages from incumbency, notably scale, security and resources.

Banks have large data reserves because they have relatively large customer bases while customer acquisition is expensive. Even if their reputations may have suffered in recent years, their security is still trusted.

Growing awareness around privacy breaches and data security will drive greater regulatory scrutiny and that can be expensive. For many startups, it may be too expensive.

As consultancy Total Expert wrote in a report for American Banker called The Risks and Rewards of Big Data in Financial Services, “to fully leverage your organisation’s data, you first have to understand the regulations concerning the collection and use of data”.

“Then put into place the right policies and procedures to protect this data,” the firm added.  “From the top of the company all the way down to every individual who is going to be working with it.”


The challenge is around aggregating and using data to satisfy customers while protecting it and complying with a growing body of regulation.

Competition though is fierce. As Skinner argues “what happens if there are many intelligent data aggregators out there?”

“Apple knows all of my downloads, music and film preferences; Amazon knows all of my regular buying needs; Google knows what I’m thinking before I finish entering my question…”.

“Before you know it, the big banks will just see statements that say Amazon (auto top-up)  £500.00; Monzo (auto top-up) £200.00; Apple (auto top-up) £300.00; TfL (auto top-up) £40.00 - you know that I am buying things on Amazon, doing things on Monzo, downloading things on Apple and travelling on the London Underground; but you have no idea what, why or where I’m buying, doing, downloading or travelling.”

The Boston Consulting Group made the point explicitly in its report Organising for Digital Innovation.

“New products designed for customer journeys in financial services, for example, are meaningless if a company cannot engage customers and access data digitally,” the report reads.

BCG noted in its research big data analytics had climbed from eighth to third in importance as a source of innovation since 2014. Such analytics, according to companies surveyed, were important for identifying new areas for exploration, idea generation, revealing market trends, informing investment decisions and setting portfolio priorities.

Critically however BCG found companies were still struggling with setting priorities. Starting from a blank sheet of paper (or touch screen), startups on the other hand are more targeted in such decisions – but of course that is also in part due to small size and lack of existing data.

Ask a dozen bankers what being digital means and you’ll get a dozen different answers. Sure it will be about making things easier for customers by removing manual interactions, automatically performing some tasks, reducing errors. Beyond that strategies are both critical and uncertain.

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BCG found “the economic benefits are increasing for traditional retail banks that have implemented the most effective digital strategies”.

“Between their more developed digital strategies and (in many cases) regional advantages, the top-performing banks now have cost-income ratios that are 19 per cent better than those of median banks. That differential has been growing for the past two years.”

BCG identified two main approaches to digital transformation: measured and deliberate; and aggressive leapfrogging. The challenge with the former is deliberate transformation is too slow; with the latter that the cultural disruption is too damaging.

“Data from our survey shows that support for a more radical approach to innovation is getting stronger,” the report said. “Moreover, by wide margins, strong innovators are much more likely to pursue disruptive or radical processes and cultures governing innovation projects.”

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But lubricating all this is data – and it that sense it is truly like oil. Banks have plenty of it but not always in a useable form. Fintechs are smart at using it but typically don’t have enough data or customers.

Global shifts towards “open banking” – where customers have more control over their data and can require an existing bank to share it with another institution – will tilt that scale but it remains unclear by how much.

What is clear is banks have to be a lot better at handling and using data to provide customers with valuable information - not just marketing leads for their existing products.

Andrew Cornell is managing editor at bluenotes

The views and opinions expressed in this communication are those of the author and may not necessarily state or reflect those of ANZ.

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