SINGAPORE: If you could be a superhero, which of the following superpowers would you pick: Flying or invisibility? This, I heard recently, is an interview question one of the big technology companies asks potential candidates.
This is a question no doubt designed to test a candidate's ability to think on their feet and demonstrate reasoning. However, with the accelerating pace of technology advancement, navigating the future of business is like choosing superpowers. The emerging superheroes: Blockchain, APIs, cloud, big data, machine learning, the Internet of things (IoT), biometrics all claim to have superpowers that enable you to save the world.
So which one to pick? Where to start? It may be obvious but many seem to get it wrong. Tinkering around with technology because it is the flavour of month is likely to get you nowhere. Which technology to pick should be driven by what business problem you are trying to solve and guided by vision and strategy, but this sentence offers no new guidance.
MAKE BANKING DISAPPEAR
At DBS, we believe that for banking to be joyful, banking needs to disappear from people's lives. When you get out of an Uber taxi, you do not have to worry about payment. In the same way, we want to integrate banking into people's lives.
However, we clearly have a long way to go in our goal to make banking disappear, and it feels like we will need the entire squad of technology superheroes to pull it off. The magic of APIs is going to help us integrate into ecosystems. Biometrics will help solve the authentication challenge. IoT will allow payment between objects, and robots are going to automate operations to drive efficiencies. All these technologies are young and their superpowers are still developing.
However, there is one superhero who is quietly delivering outcomes, and that is Big Data along with his sidekick Analytics, which includes machine learning and artificial intelligence. Between these two, they offer a whole range of superpowers that banks can leverage to better serve consumer needs.
1. SEE INTO THE FUTURE
At DBS, we now use machine learning to predict when a relationship manager is going to resign and potentially take our clients with her.
We can also predict when an ATM is going to mechanically fail; this is important as we have one of the busiest ATM network in the world and we take downtime very seriously. Our audit team can also predict which branch will likely have the next operational issue.
We can also predict branch and ATM queues and even the sales performance of job candidates.
2. ALL SEEING
Machine learning can help monitor the bad guys. At DBS, we use data to detect rogue traders and fraudsters in the procurement and trade areas. We also use machine learning on video files to monitor the IT guys who have access to our production systems.
3. ALL KNOWING
We were an early adopter of IBM Watson, an artificial intelligence platform, and have used it to analyse the vast quantity of research material available to make investment recommendations, with good success.
4. OPERATE ACROSS BORDERS AND LANGUAGES
Last year, we launched a mobile-only bank in India, Digibank. We partnered with a start-up called Kasisto to build a chatbot that answers customer questions. The bot is able to understand the language there and respond to 80 per cent of customer queries on its own.
5. X-RAY VISION
It might not exactly be x-ray vision, but sometimes it seems that way as banks do know a fair amount about their customers. Your bank knows your age, gender, financial standing, address, where you work, and how much you earn. They also know what you spend your money on, where you go on vacation, your favourite restaurants, and what you do in your spare time.
This is the ultimate data superpower and has to be used responsibly. On the flip side, it is a key that can help unlock amazing customer experiences and ultimately make banking disappear.
The superpower metaphor while fun has a serious side to it. It helps address one of the challenges we continue to face on our artificial intelligence journey. People find it difficult to imagine the future and what problems a new technology can solve. People tend to think in increments.
FIVE LESSONS LEARNT
We have only just started but have learnt five lessons from our big data and analytics journey that are worth sharing. First, always start with the question in mind. Unless you are clear about what problem you are trying to solve, you run the risk of running round in circles. Simply wallowing around in the data does not work. We tried it, don’t do it.
Second, start with your own data. We were tempted to supplement our own data with the beguiling world of social and IoT data. However, these are hard to get hold of and work with, and we had so much of our own data that we were not using that we decided to focus internally first. In a couple of cases we have supplemented solutions with external data, but so far this has been the exception.
Third, don't work alone. We worked with IBM, Kasisto and A*STAR, the research arm of the Singapore Government. We started with very limited capability, as talent is hard to come by. But each partner helped us accelerate our learning curve and yield results.
Fourth, design for data. As we learn the potential of machine learning, we are starting to design our products with data in mind. We ask ourselves, "what data should I produce from this product or service that will enhance customer offerings or drive efficiencies?" We then design accordingly.
Finally, grab your mask and cape and just step into the nearest phone box. There are so many untapped opportunities in banking and I suspect in pretty much every other industry. It's time to just plunge into it and save the planet – well, a small part of it anyway.
Paul Cobban is DBS Bank’s chief data and transformation officer.