Financial services as an industry has continually had low levels of consumer trust. Although at a five-year high, the 2019 Edelman Trust Barometer puts the current level of consumer trust in financial services in the UK at just 51%.

When we cast an eye over the state of marketing success over the past few years, according to Binet & Field, in their seminal work “Effectiveness in Context – A Manual for Brand Building”, the financial services sector has embraced all of the destructive trends:

  • A focus on short-term growth;
  • An over-reliance on sales activation campaigns vs. brand building initiatives;
  • Reduction in investment;
  • A preference for loyalty marketing.

All of these destructive trends may have played a part in the continual low level of consumer trust, and the inclination towards loyalty marketing rather than driving new customer acquisition through brand building activity will have weakened marketing’s contribution to the top line growth of many organisations.

If close to half of the population don’t trust your industry, and a new customer acquisition marketing strategy is the way to experience the most growth, then choosing to invest in technology that allows your brand to deliver the tools, features, products, and services that customers desire, must be your number one priority.

But how can financial services brands digitise and remain human?

The rise and influence of FinTechs

The birth of a large number of FinTechs over the past ten years, with their ethos of digital innovation and market disruption, and their use of technology, automation, and artificial intelligence, has made the wider financial services industry wake up, prompting older businesses to take digital action.

Consumers are often drawn to FinTech services because their propositions are simple and more convenient, their products and services are laser-focused on a specific customer need, and the customer experience is more personalised.

This personalisation approach has had a ripple effect across the whole financial services industry, as consumers have come to expect these characteristics in all financial products and services in retail banking, wealth management, and insurance.

WeSwap, the people-powered travel money platform, as an example, has focused on the power of community and innovative technology in order to spearhead its growth and increase the number of customers.

The platform, that helps travellers budget, swap currency, save, borrow and spend smart, has a product roadmap covering transfer of funds, getting the best exchange rates, asking the community how much money to take to a specific country, and ordering cash while abroad. Each element is focused on responding to a potential customer need in the moment.

More established financial services brands, for whatever reasons, have been relatively slow to jump on the bandwagon of using technology in clever ways to deliver new and improved, personalised products and services, and – if the below example of what consumers want from their bank, and what their bank actually gives them, is anything to go by – there is still a long way to go.

What consumers want from their banks, and what they are getting 
Source: GfK, “Bots, Banks, and Brands"

Why customer data could hold all the answers

If we look outside the financial services industry to what other brands are doing in other sectors, we see a growing pattern of organisations harvesting user data and preferences to create new products and services that drive delight, satisfaction, and long-term loyalty.

A neat example of this is Spotify’s Discover Weekly feature, where 30 new tracks the user hasn’t listened to before are served up every Monday.

How does Spotify work out what tracks will pique every individual’s interest? Well, based on the music a user listens to, Spotify assigns them a taste profile. Spotify scans millions of playlists, building connections between tracks, and matches those to individual taste profiles.

The end result is an experience for the individual of constant discovery and, more often than not, music satisfaction.

How Spotify's Discover Weelly works 
How the Discover Weekly machine works (inspired by Sonnad, Quartz, & Girardin BBVA)

This is all achieved with machine learning technology.

Whilst we might be more familiar with the application of machine learning technology in the media and retail ecommerce sectors, we will increasingly see its use in the world of financial services – from analysis of the evolution of savings patterns to determine which investment products are more appropriate to recommend, to providing recommendations of where to eat whilst on holiday, based on spending behaviour blended with third-party ratings.

Machine learning techniques can be incorporated into digital financial services products and services in a myriad of ways.

And Accenture’s Financial Services Customer Survey 2018 actually showed that a growing number of customers are willing to receive advice and services in a way that is completely computer-generated.

Accenture reasons financial services customers give for being willing to receive computergenerated 
Source: Accenture UK Financial Services Customer Survey 2018

To decide whether or how machine learning could be right for your brands or help to achieve your business and marketing objectives, it can be useful to ask yourself a few questions to help frame your thinking:

  • What are we trying to minimise or maximise with this product or feature that provides tangible benefits to the customer? – for example, for a money transfer feature, auto-suggesting friends to send money to could help reduce the time taken for the user.
  • What customer data is actually available to us, and can we first do what we want without machine learning? – for example, do we have access to the customer’s location data, or their spending data, and can we set up personalisation rules accordingly? Do we have the tools, platform, and technology to do this?
  • What should the speed of customer data collection and presentation to customers be? – for example, Spotify’s Discover Weekly only sends out recommendations once a week, whereas an app like Yelp that can notify you with good restaurants nearby that match your tastes, must be able to adapt in real time based on where the customer is right now.
  • What kind of feedback can customers provide, in an unconscious and natural way, to improve the performance of the machine learning model? – for example, the facial recognition feature in iOS photos app allows the user to easily correct its grouping of photos with an individual in it.

Slowly but surely, financial services companies are starting to wake up and use technology to better deliver their services, from mortgage brokers continually tracking if their customers can get a better rate with another provider, to wealth management platforms automatically re-balancing portfolios.

These kinds of service offering are no longer at the cutting edge of technology advancement in today’s world, but they are indicative of the broader trend within the industry to provide finance customers with real value – in a way that is human, albeit powered by technology.

For the financial services sector, the potential to create digital products and services that are self-reinforcing in terms of the experience they deliver, by utilising the data generated by customers, is huge.

Financial Services marketing needs to get personal

Accenture’s Financial Services Customer Survey 2018 found that the majority of consumers are more than happy to share their personal data in return for deeper personalisation and more relevant products from their financial services provider.

Accenture percentage of financial services customers wanting personalisation 
Source: Accenture UK Financial Services Customer Survey 2018

This has also been our experience.

We are often approached by financial services firms looking to enhance the online customer experience, build customer journeys and content to match each stage of the journey, and use new platforms and technology – such as Sitecore – to deliver a personalised experience to each and every customer.

These companies realise that they need the chatbots, the machine learning tools, and the mobile apps, which meet customer need in the moment – but that they also need to consider the long-term user journey and how a customer’s need will change through a person’s lifetime, that they must create products and services to match, so they need the right platform in place to deliver against this.

Financial services brands need to develop a deeper knowledge and comprehension of people’s financial needs, and take advantage of data and technology innovations to create products, services, and customer experiences that amaze, dazzle, and delight.

The brands that focus on engaging and delighting all generations of customers in the micro-moments where decisions are made, and service delivered, will be the ones who win.

Put simply, the choice between continuing with business as usual and staying with the same website platform, or investing in technology to deliver customer data-led personalised experiences, could mean the difference between death and survival.

Technology – if focused on delivering against customer wishes and customer needs – can absolutely make financial services more human.

Want to talk?

With vast experience in the financial services sector, helping to drive differentiated and personalised digital experiences for brands including Seven Investment Management (7IM), M&G Investments, and Nationwide Building Society, everything we do starts with your customers and their needs.

Whether you need a new website platform to automate marketing, and personalise content and the customer experience, or you’re looking to take advantage of the latest machine learning technology to deliver new digital products and services, we can help.

To talk to us about how technology and personalisation can make your brand more human, just get in touch.