Banking on data
Chris Evans speaks to data evangelist Ian Matthews at NGDATA about the challenges banks face adapting to the ‘next generation’ of customers
Tell me about NGDATA
We are a European start-up focused on helping consumer-centric industries, particularly banking, with how they interact with customers. This is done through a data platform and offering services to help them move from legacy systems to value-driven analytics.
Do you work with banks of all sizes?
Yes. We’ve seen it’s the medium-sized banks who are doing the most. The smaller challenger banks tend to not have a lot of data and the large banks are slow to move.
We help banks move from just having a branch and minor web presence to providing an integrated customer experience across the internet, phones and apps.
Are banks taking advantage of Big Data to the extent they should be?
Yes and no. Almost every big bank has put in place test programmes and projects around risk or fraud analytics, and even products, using big data analysis and get some good results. But they tend to just put the results in spreadsheets, and are too nervous to plug the products and programmes into their operational systems and offer real-world application.
The few that do allow customers or staff to interact with them suddenly get a lot of value. When IT teams are leading the data analytics, it’s hard to draw value, but when there’s a dedicated smart business team actively involved changes can be made.
Are we seeing this happening?
There’s certainly interest. HSBC is investing in big data and has adopted open banking more than others. They’re trying to become a hub. But generally speaking, the bigger banks are letting the fintech/challenger banks steal their customer relationship interaction. If you’re using budgeting app Yolt or savings apps like Chip on your phone, that’s what you see as your interaction with your bank.
The challengers/fintechs are certainly encouraging saving and giving customers insight into their money, but they’re not necessarily experimenting with innovative ways of using customer banking data to change your life.
But there are some interesting fintechs in the SME space, such as Fluidly, which is using open banking and artificial intelligence (AI) behind the scenes to do cash flow forecasting that you’d traditionally have to get an expensive expert accountant to do.
Fluidly is then automating that at scale so it can give hundreds of businesses a real-time view of their cash flow. The larger banks with their huge sets of data and vast customer interactions could take massive advantage of such B2B applications if they were to properly invest.
According to a YouGov survey 22% of people have not even heard of open banking. What more should be done?
The funny thing is that they don’t realise their apps are already using it. The challenge is enabling it. The problem is the banks didn’t push for open banking, it is something the EU regulators wanted. Until the banks can get a full set of values from it, they’re not going to talk about it much because it encourages you to go to someone else. The smart ones will be those who work out how to drive value for them and the customer, while maintaining the same level of trust. The difficulty is that’s being eroded somewhat by the endless headlines about data breaches and IT downtimes.
Interestingly, the challenger banks are not doing a lot of personalisation with customer data, but they are relentless in their customer focus. They communicate their service offerings all the time.
By contrast, the big banks can make everything personalised to the customer because they’ve got the data, systems and usually the technology in place. But they’re not applying it or communicating their offerings effectively enough.
They could apply the work they do with their high-value wealth management clients to all consumers. They would then feel more engaged in things like AI stock trading programmes or investment advice programmes. These services can be powered by AI with a little tweaking from the experts who teach and guide it.
Do you see that as the future?
This is the year where, if banks get it right with data analytics and AI, they could disrupt the sector completely. They could offer 15 different services and pick the right one to offer the customer at exactly the right time, and even on the right medium.
If I get an email from my bank, I might read it. If I get a text, I’m going to read it pretty sharpish. And if I get a WhatsApp message, I don’t really like that, but other people do. So, getting the communication right and offering the correct product or service is key.
I have been with NatWest since I was 14, so they’ve got many years of data on me – spending habits, insurance, mortgage and so on. But they’re not personalising products and rates to meet my needs. Instead, you’re seeing US banks such as Goldman Sachs offering their own agile digital banks with preferential high-interest savings accounts. Unsurprisingly, they’re proving successful in the UK. If customers see a better rate they’ll go for it.
It’s all about personalisation. There’s the old marketing adage that people only open about 15% of emails, and you’re lucky if you get 5% click-through. If the banks could personalise the online experience, they could potentially get 50-60% click rate. This is what we found with Belgium bank Belfius, who we helped with their customer experience across branch, internet, phone and app.Is it a delicate balance between releasing data through open banking and protecting it through GDPR?
For starters, it’s a case of the banks educating the customers about how they’re going to be using the data. But the other aspect is that challenger banks see data governance as an enabler, so seek permission from customers to do something then immediately act on it. Whereas the incumbent banks see data governance as a form of compliance and security.
Are the challengers actually stealing customers from the big banks?
They are certainly stealing the next generation of customers. The traditional banks have the baby boomers and older generation X who tend to stick with them. But the younger generation X and millennials are getting tempted away by the challenger services. Some might still maintain their core bank and adopt service offerings from the challengers, such as a Revolut card when travelling because it offers preferential rates. But others are happy to change and do all their banking on their mobiles.
I don’t think challenger banks will put the big banks out of business now. But if the latter don’t capture the next generation of high-net-worth (long-term) customers early, it’s going to be hard to pull them out of another bank once they’ve got mortgages and investments there.
Are challengers promoting enough variety?
It’s more about ease of use rather than variety. Their saving rates are not exceptional, but everything can be done at the touch of a button. It’s all about communication and real-time solutions.
When I raise my hand, I want someone on Twitter from the service provider to say, “Yes, Ian, what do you care about?” Once they get more data, they can do more personalising. Not just, “What’s your problem?”, but, “I think you’ve got this problem, here’s the solution”.
How should traditional banks be responding?
They need to gather real-time information, use big data or next-generation technology in the cloud, and engage with their customers. Then set up teams to address problems facing groups of consumers and test solutions rapidly, rather than taking the big bang approach of planning to change their entire banking system within five years. That will have a wide impact, but not change their customer experience in the short term. The smart ones will have mini challenger banks internally. You’ve seen that with CYBG acquiring Virgin and making them their digital bank.
How do you see financial firms interacting with technology in 2019?
One or two will do things like compare the market automatically using open banking or become a one-stop hub for all financial transactions. It’s just a case of whether it’s a challenger or traditional bank that can put all the pieces together and implement it first. As part of this, we’ll see the big banks craving the challenger bank technology so they can be more mobile.
We’ll also see firms offering AI investment decisions, conducting next-generation fraud analytics and looking at next-generation personalisation experience (through things like chat bots).
The challenge is that AI can be right with 99% of decisions, but that 1% could be problematic. If it’s just a case of recommending the wrong product, it’s not too bad. But if they lock the customer’s account down, or misdiagnose something, or target the wrong product and the customer loses money, that’s when it becomes serious. So having the checks and balances as you scale it up is key, as is looking at the cost benefits – risks versus rewards.
In data, getting 90% accuracy takes 10% of the time, the next 9% takes 20% of the time, and the final 1% you could be working on forever. Obviously, you can’t spend all your time cleaning the data and getting it right, you’ll go out of business. But if you don’t do the checks, you can’t make a tough decision that will affect your customer without raising a flag.