Helena Schwenk, Market Intelligence Manager at Exasol, explains how banks can use data and analytics to capture customer loyalty.
Driving customer loyalty has always been an important initiative for financial institutions, but COVID-19’s profound impact on the world has fundamentally changed how financial services companies now view loyalty. As more and more interactions shift online to virtual channels; customer behaviour changes as economic constraints hit home; approaches to risk change; and digital sales and services accelerate – the value of progressive data strategy and culture is all the more crucial.
As McKinsey’s recent report highlights, as revenue growth and customer relationships come under pressure, banks will need to rethink their revenue drivers, looking for new product launch opportunities, as well as reorienting offerings toward an advisory and protection focus. Advanced analytics can help identify those relevant niches of prudent growth.
However, the high prevalence of data silos and the unprecedented growth in data volumes severely impacts financial institutions’ ability to rise to this challenge efficiently. And with IDC conservatively predicting a 26% CAGR data growth in financial services organisations between 2018-2025, there are no signs that managing data is going to get any easier.
The financial services sector was already extremely data-intense due its the large number of customer touchpoints and the lasting legacy of COVID-19 will see this expand even further. Beating this challenge will require financial institutions to focus on turning their quantity and quality of their data into governed and operationalised data. To gain competitive advantage and win the fight in driving customer loyalty, financial services firms need to eradicate their data silos and start benefiting from real-time business decision making.
Beating this challenge will require financial institutions to focus on turning their quantity and quality of their data into governed and operationalised data.
Adopt a robust data analytics strategy
Defining a data analytics strategy is crucial for financial services organisations to increase customer loyalty and deliver a better customer experience. A solid data strategy holds the key to uncovering invaluable insights that can help improve business operations, new products and services and, crucially, customer lifetime value — allowing organisations to understand and measure loyalty.
In addition, a robust data strategy will help organisations keep a sharper eye on customer retention, using data to actively identify clients at risk of attrition, by using behavioural analytics, and then generating individual customer action plans tailored to each client’s specific needs.
In our survey of senior financial sector decision-makers, 80% confirmed that customer loyalty is a key priority, given that consumer-facing aspects of financial services generate revenue and are a critical differentiator. And, according to Bain & Co., increasing customer retention rates by 5% can increase profits by anywhere from 25% to 95%.
Recognise the challenges of customer retention
But increasing customer retention and improving loyalty is not easy. There are ongoing challenges to earn and maintain. For example, 54% of our survey respondents believe that customers have higher expectations of financial services experiences and 42% agree that digital disruptors that support new digital experiences, offerings and alternative business models, are encroaching on their customer base.
At the same time, regulation is a concern too, with 41% saying PSD2 and GDPR are impacting their ability to develop and improve customer loyalty initiatives.
Despite all these challenges, the business impact of poor customer loyalty – such as lost opportunities for customer engagement and advocacy (45%), higher levels of customer churn (45%) and lost revenue-generating opportunities (42%) – is too important to ignore. Given that it costs five times more to acquire a new customer than sell to an existing one — gambling on customer loyalty in today's highly competitive environment is a big risk to take.
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Strive for constant improvement
That said, in a heavily regulated industry with a wave of tech-disruptors, keeping customers happy and loyal is no mean feat. But driving a deeper understanding of customer lifetime value and measuring the loyalty of customers is possible. The good news is that almost all organisations (97%) use predictive analytics as part of their customer insights and loyalty initiatives, with three fifths (62%) using it as a key part. 65% also agree that data analytics enables them to offer personalisation and predict customers’ future behaviour.
Overall use of data analytics is maturing in financial services compared to other industries; 96% of the people we surveyed were very positive about their firm’s data strategy and how it is communicated for the workforce to implement. Although 48% did admit it could be improved.
This consistent need to improve is backed by McKinsey. Its survey of banks saw half saying that while analytics was a strategic theme, it was a struggle to connect the high-level analytics strategy into an orchestrated and targeted selection and prioritisation of use cases.
Revolutionising data analytics
Revolut is one disruptor bank showing the world what a thriving data-driven organisation looks like. By reducing the time it takes to analyse data across its large datasets and several data sources, it has reached incredible levels of granular personalisation for its 13 million global users.
Within a year, the data volumes at Revolut had increased 20-fold and it was an ongoing challenge to maintain approximately 800 dashboards and 100,000 SQL queries across the organisation every day. To suit its demands and its hybrid cloud environment it needed a flexible data analytics platform.
An in-memory data analytics database was the answer. Acting as a central data repository, tasks such as queries and reports can be completed in seconds instead of hours, saving time across multiple business departments. This has meant improved decision-making processes, where query time rates are now 100 times faster than the previous solution according to the company’s data scientists.
Revolut can explore customer demographics, online and mobile transfers, payments data, debit card statements, and transaction and point of sale data. As a result, it’s been able to define tens of thousands of micro-segmentations in its customer base and build ‘next product to purchase’ models that increase sales and customer retention.
The 2 million users of the Revolut app also benefit as the company can now analyse large datasets spanning several sources – driving customer experiences and satisfaction.
Revolut can explore customer demographics, online and mobile transfers, payments data, debit card statements, and transaction and point of sale data.
Every employee has access to the real-time “single source of truth” central repository with an open-source business intelligence (BI) tool and self-service access, not just the data scientists. And critical key performance indicators (KPIs) for every team are based on this data, meaning everyone across the business has an understanding of the company’s goals, industry trends and insights, and are empowered to act upon it.
Predict what your customers want faster
A progressive data strategy that optimises the collection, integration and management of data so that users are empowered to make and take informed actions, is a clear route to creating competitive advantage for financial services organisations.
Whether you’re a longstanding brand or challenger bank, the key to success is the same – you need to provide your services in a timely, simple and satisfying way for customers. Whether you store your data in the cloud, on-premise, or a hybrid, the right analytics database is central to understanding your customers better than ever before. By using data to predict and detect customer trends you will improve their experience and get the payback of increased loyalty, which is even more essential in a post-COVID world.
With the entire industry currently under pressure due to uncertainty, data must lie at the core of every decision any business makes if it wants to succeed. In fact, research from McKinsey tells us organisations that leverage customer behavioural data and insights outperform peers by 85% in sales growth and more than 25% in gross margin. Jil Maassen, lead strategy consultant at Optimizely, offers Finance Monhly her thoughts on how data experimentation can be used to drive financial services forward.
The game-changing nature of data
One of the best examples of risk and reward, based on data science, comes from the world of baseball. Back in 2002, Billy Beane, general manager of the unfancied Oakland Athletics baseball team, spawned an analytical arms race among US sports teams. Working under a limited budget, Beane used obscure stats to identify undervalued players — eventually building a team that routinely beat rivals who had outspent them many times over.
Data analytics turned the game on its head by proving that data is an essential ingredient for making consistently positive decisions. The success of the bestselling book and subsequent Oscar-winning film, Moneyball, based on Beane’s story, took data analytics mainstream. Today, financial services companies are applying a “Moneyball” approach to many different aspects of their business, especially in the field of experimentation.
Data analytics turned the game on its head by proving that data is an essential ingredient for making consistently positive decisions.
We live in testing times
Experimentation departments for the purposes of testing, also known as Innovation Labs, have been growing at a prolific rate in recent years, with financial services seeing the highest rate of growth according to a survey by Capgemini. By the end of 2018, Singapore alone had 28 financial service-related Innovation Labs. Alongside this, research from Optimizely reports that 62% of financial services companies plan to invest in both better technology and skilled workers for data analytics and experimentation.
Areas such as fund management are no strangers to data analytics. But since the fintech disruptors arrived on the financial services scene, legacy banks are now using data in combination with experimentation to evolve other elements of their business and remain competitive. Many have found that this is helping them to address common concerns, including how to improve customer experience and successfully launch products to market. So much so, that our research found that 92% of financial services organisations view experimentation as critical to transforming the digital customer experience. In addition, 90% also consider experimentation key to keeping their business competitive in the future.
Eat, sleep, test, repeat
However, experimentation takes patience. As Billy Beane said when his strategies didn’t deliver right out of the gate: “It's day one of the first week. You can't judge just yet.” He was ultimately vindicated. Like any new initiative, experiments can fail because of cultural “organ rejection.” They require taking short-term risks that don’t always work, all in service of long-term learning. It’s the job of Innovation Labs to take these risks, and often, one for the team, by being prepared to fail.
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The point is, when you're transforming something and making massive change, not everyone is going to understand right away. The best way to convince people that your theory is correct is to show them — not tell them — you're right. Experimentation initiatives in business, and especially in financial services where risks and rewards have high impact and return, allow new ideas to be proven right before they play out in front of a paying public.
Founded in facts and stats, experimentation promotes an ethos that is key in adopting new technologies and utilising data analytics to build roadmaps for the future. As the amount of data companies have access to increases, the ethos of experimentation will only become more important for predicting and changing the future for the better.
Experimentation is about measuring and learning and repeating that process until optimum results are achieved. The final word in this regard should perhaps go to Beane himself; “Hard work may not always result in success. But it will never result in regret.” His story is something that all financial services organisations can learn from.
Below, Danny Phillips, Zscaler's Senior Manager of Systems Engineers, discusses the importance of cloud technology and its implications for older entities in finance.
In the financial sector, bigger has always meant better. In fact, if a financial institution is suitably large, it is deemed so vital that, as the popular terms suggests, it is “too big to fail”. This situation has provided two key benefits for large players in the financial sector: the potential cushioning from government when things go wrong, and a tacit understanding that they’re essentially untouchable when smaller competitors enter the marketplace.
This all held true for some time, and newcomers in the space have generally carved themselves a niche, remained relatively small, and never really threatened the incumbents. As such, it can be argued that complacency has permeated the halls and boardrooms of some of the biggest players in the finance sector.
There are, however, signs of change across the sector. Whilst the financial institutions of old aren’t likely to shutter their doors anytime soon, recent technological innovation is shifting the balance of power considerably. It’s not the only technology playing its part in this equation, but cloud IT is the driving force behind disruptive industry newcomers, providing the agility they need to launch products and services faster, push forward better customer experiences and target new markets more precisely.
Lowering the Barriers to the Finance Sector
There have always been barriers to entry to the financial services sector. Chief amongst them has been the tight regulatory landscape, which ensures that smaller players can’t operate without first having the required licences (PSD2, PCI etc.). Although regulation is a necessity, a potential drawback is that it’s yet another barrier for smaller outfits to traverse.
There are efforts, however, to clear a path for smaller businesses. The success of Open Banking has allowed third parties to develop services around financial institutions, with plans to extend this beyond the retail banking sector and encompass products in the general insurance, cash savings and mortgage markets, under a new model called 'open finance'.
This has opened the door to smaller fintech companies to create a host of consumer-focused products, including money saving and credit-building apps. This has been significant because, when considered in conjunction with cloud, it’s arguably putting larger financial institutions, particularly banks, at a competitive disadvantage.
Cloud IT is the driving force behind disruptive industry newcomers, providing the agility they need to launch products and services faster, push forward better customer experiences and target new markets more precisely.
Cloud-Enabled Agility
Cloud is enabling new businesses to be set up without the burden of the physical infrastructure so intertwined with the older, larger industry players. For new entrants, any part of the business can be picked off the shelf. Salesforce for your CRM system or Workday for your HR, all paid for monthly or quarterly. Computing functionality can be purchased as-a-service and can even be paid for in increments as small as a CPU cycle. All that’s needed to enter a market is a great idea, a laptop, an internet connection and a credit card.
Bringing the conversation back to banking in particular, we’re already seeing the benefits disruptive new players are reaping. The likes of Monzo, Revolut and Starling Bank, are releasing new features and functions nearly every month (often based on customer feedback), enriching the customer experience and generating positive word of mouth. They’re able to do so because of their lean and agile structures, unburdened by a reliance on physical hardware, paperwork or branches. Currently, high-street banks are struggling to compete at this level.
Why the Bigger Financial Institutions Aren’t Embracing Cloud
Imitation is the sincerest form of flattery, so why aren’t larger financial institutions just doing the same as these smaller competitors to ward off the competition before it gets too big? A 2019 research paper from 451 Research revealed that financial services companies are behind other business in deploying cloud as a central part of IT operations. Around 70 per cent said their cloud projects were only at the initial, or trial and testing, stage.
There are a number of reasons why this might be the case, namely legacy IT debt, unfinished upgrades and compliance. Obviously, like any business, financial institutions are under pressure to use what they have already paid for before moving on to the next generation of infrastructure. Established businesses have to plan migrations, with business as usual taking priority.
In my experience, what we see instead is a one foot in, one foot out hybridised attempt at cloud adoption from larger financial institutions. Newer applications will be running in the cloud, but the majority will remain housed within the main datacentre. The end result is virtual machines running in the cloud with permanent connections between the corporate network and the cloud provider. So, when someone wants to access this application remotely, they have to dial back into the office on a VPN to get to the cloud instead of connecting to the cloud directly.
This dilutes the benefits of the cloud, and isn’t really a true step forward.
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Thinking to the Future
If plans to open the financial services sector up to new businesses continue along this trajectory, we’re going to be seeing a far more varied industry landscape than we’re seeing today. If larger institutions are still playing catch-up on cloud, by the time they make it there the conversation will have moved on.
Financial services institutions therefore have a doubly difficult route ahead of them. As well as accepting the sunk costs of now outdated infrastructure and upgrading to a cloud-first mindset, they also have to keep an eye on the future. For my money, what they need to be thinking on is how to leverage 5G for competitive advantage, and how to do so in-step with their smaller competitors.
As the use of 5G becomes more widespread in the 2020s, local area networks (LANs) are set to disappear. We currently look to Wi-Fi to access the internet, but when every PC or mobile phone is equipped with ultrafast 5G, the use of Wi-Fi becomes an outdated notion. The traffic from 5G devices will connect the right people to the right applications—through a digital services exchange—and this will deliver faster, more secure, and more reliable access to apps and services.
The promised low latency, high data capacity and reliability of 5G networks has a host of applications in financial services, and creates a new platform for the delivery of services on mobile. For banking, reliable video conferencing sessions with mortgage brokers, or financial advisors, without having to travel to their nearest branch could be commonplace, rather than a seldom used novelty. Real-time data streams from customers, perhaps in conjunction with a machine learning platform, could aggregate a customer’s behavioural data in real time, enabling contextual financial recommendations.
If larger institutions are still playing catch-up on cloud, by the time they make it there the conversation will have moved on.
5G will not be solely a benefit to a bank’s customers though. Its impact will be felt so broadly that banks need also to think about how their own employees will utilise 5G. It’s highly likely that, as 5G becomes the norm, expectations for quick and hassle-free access to applications will climb. When applications are hosted in the cloud, fast internet access is more important than ever. If a user’s device has faster internet access than the corporate network, those users are likely to continue using their superior mobile access, as opposed accessing the internet via the corporate network. It’s a matter of human nature to take the path of least resistance.
However, security may not be top of mind for these users as they access work applications while away from the corporate headquarters. Protecting an on-premises network infrastructure will become less relevant and financial organisations will have to adapt to secure the “edge” once more: in this case, the individual user on their mobile device. Banks and other financial institutions will have to be able to respond to the effects of evolving user behaviour introduced by 5G.
In many ways, financial institutions are facing an uphill struggle to make back the ground they’ve already lost by dragging their feet on cloud adoption, both in terms of fulfilling the needs and expectations of their customers as well as their staff.
Ultimately, for end consumers, these newer, faster and more convenient financial services are inevitably coming our way. Whether they’re brought to us by one of the big four, by a challenger like Monzo or Starling, or even by Google or Apple, is still to be decided.
