Technology’s cool. Whatever you want, technology can connect you to it, from superfood salads to soulmates. Not only has it brought us boundless choice and instant delivery, it’s got a whole lot better at working out what we’re going to like before we even start looking.
The fuel that drives all this wizardry is personal data. Amazon knows everything we’ve bought or even browsed. Facebook knows what we like and who we know. Google goes with us everywhere, and knows everything we’re curious about. These Tech Titans trawl through vast pools of data for clues to what could be the next indispensable service for their users.
Their advantages are simple and powerful: enormous customer reach and brand recognition – Amazon, as of April this year, has more than 100 million paying subscribers to Amazon Prime, or in other words, roughly 2.5 times the customer base of HSBC – and a level of emotional trust that most banking organizations lack.
These large tech firms have invested heavily in engagement technology, having the ability to handle data at scale and use it to generate new services. And they also have access to enormous computing power in the cloud.
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The Power of ‘Big Tech’ Mindset
But, what makes them particularly dangerous for banks, credit unions, investment firms and other financial services providers is their mindset. They’re not scared of deploying new services and they see financial services as another way to facilitate their business model. If Amazon lends a consumer money, they can buy or sell more stuff on Amazon.
They have no reverence for anybody else’s business model and they will casually disrupt without any sense that they should not be on that territory. Equally, they’ve got very little reverence for their own business model – they will iterate it repeatedly to deliver a better service, to grow faster and to own more share of heart – not just mind.
They are also very attractive organizations for the best technology talent wants to work: they offer the biggest canvas for talented developers. And over and above all of that, they have shareholders who are trained to go for growth, not dividends, and who value disruption and new kinds of service imagination, design and delivery.
The Creation of Expanded Insights
There are other ‘data players’ in the Open Banking future that, like banks, are old-economy companies in many ways. These include retailers, energy companies, telcos, wealth managers, pension providers, insurance companies.
The key advantage of these organizations is huge amounts of customer data that could be combined with other data sets to identify unmet and under-served needs. Imagine these needs popping up in the intersections of a Venn diagram. For example, if you bring energy understanding together with banking transaction understanding, you create new insights into that data and the potential for new services built upon that understanding.
The big question marks over them are; 1) have they recognized the opportunity?, 2) do they have the ambition to do anything about it?, and 3) do they have the ability to execute at pace?
New Data Skills Required
”Data scientists dominate this new world, but the truth is they don’t have all the answers… Data is just the raw material that seeds more personal and more human interactions between brands and consumers.”
In the Open Banking future, there is an opportunity for financial institutions to examine ways to use the data they hold to bring benefits to their customers. However, with this opportunity comes risks. The process of identifying opportunities through data, and then designing interventions, are two different disciplines.
It is one thing to be able to tell in advance from the patterns of behavior revealed in a customer’s transactional data that a consumer is in danger of financial distress. It is another thing entirely to have the level of trust and personal engagement that will allow your organization to communicate with the consumer preemptively on a sensitive topic.
Today, Data Scientists dominate this new world, but the truth is they don’t have all the answers. In super-sensitive areas like consumers’ financial lives, where the data reveals everything that is earned and spent, striking the wrong tone or making inappropriate recommendations isn’t just mildly irritating or inconvenient to the customer. It could destroy their relationship with the brand. This is why companies are failing their customers – and themselves – if all they do is deploy squadrons of Data Scientists.
Success demands a different approach. Data is just the raw material that seeds more personal and more human interactions between brands and consumers. Data Scientists can uncover the need, but moving from that discovery to a personalized interaction – one that both meets the need and does so in a way that feels appropriate, human and pleasurable – demands the skills that Data Artists bring to the table.
Moving From Volume of Data to Value of Data
Having a massive volume of data does not automatically correlate to having valuable insights. This transformation from volume to value requires:
- Psychologists. People who understand how individuals relate to one another and their environments
- Semioticians. People who understand how meaning is created and conveyed
- Ethnographers. People who understand how cultures are created and how they morph.
- Ethicists. People who understand what’s OK and what’s not.
To succeed in the Open Banking future, companies must first find their data (many never look at their data, let alone put data to worthwhile use. They must also augment their data with other data sets to provide fresh perspectives on their customers, requiring a new way of thinking as the bank within an ecosystem, not just its own walled garden. And, crucially, they must ‘torture the data’ to reveal unmet and under-served consumer needs.
If you think about it from the perspective of a big tech firm, finding the data is their primary mission. When we view the augmentation phase, bit tech firms have multiple views of the consumer and can onboard other data to provide new views. Finally, these firms have no trouble finding unmet needs with the massive computing power they possess.
Most importantly, these data-driven firms are organizationally willing to listen to what the data tells them. That is because they are dedicated to data analysis and use it to guide their service development. They are also happy to iterate their own business models as often as necessary to deliver a better product or service.
From Data Science to the Art of Insight
Most people agree that without the appropriate data and related insights, the potential of personalization won’t come to fruition. But that requires financial institutions to think about data beyond trying to drive conversation based on statistical correlations.
If banking providers are to succeed in winning consumers’ trust for personalized services that depend on access to their private data, consumers must clearly understand — and enjoy — the value they gain in return for sharing highly personal information.
The question is, can financial institutions hear what the data is telling them about individuals’ needs, and how these individuals relate to one another, their environments and their cultures? Can they hear how people are responding to these needs? Do they understand the messages being sent in response to offers? Moreover, do they know or understand what people will find acceptable?
Once an organization can answer yes to these questions, they can act, knowing that they’ll be doing so with positive intent, and integrity. But, if organizations rely only on data as a science, they’ll struggle to succeed where consumer expectations are increasing.