David Lynch, managing director and head of technology and operations for Hong Kong and mainland China at DBS Bank (Hong Kong), talks about how new tools and technologies are helping him improve customer experiences at the bank.
What exactly do you do?
My role covers the development and operation of all the technology applications and infrastructure that support our customers and bank employees. In the operations domain, I manage the people who work behind the scenes to support both our consumer and private banking, as well as institutional banking clients.
A key part of my role is championing innovation in the bank and leading our bank-wide efforts to continuously improve the customer experience.
How important is big data to Hong Kong's financial services industry?
The city is positioned extremely well to capitalise on the rise of big data, with its rich maths-based talent base. Alongside the shift to human-centred design and the rise of smartphones and tablets, big data and machine intelligence are the forces that will drive the next wave of financial service innovation.
These things combined will lead to the creation of more personalised experiences, faster processing times, better investment decisions, reduced risk of fraud and exciting changes to the way customers interface with their bank.
In what ways is artificial intelligence (AI) used by the financial services sector in Hong Kong?
Banks use simple forms of AI today, like in payment processing, where pattern recognition and learning algorithms improve efficiency. In fraud prevention, AI is used to identify irregular payment or behavioural patterns.
We have seen AI applied to logistical challenges, like determining the right amount of cash to hold in ATMs, and adapting to changes automatically. There are also cases of banks in parts of the world using simple chat-bots to handle customer-service inquires. It's a rapidly growing field where banks must be an expert.
How are big data and AI related in their financial services applications?
Data is growing at such an unimaginable pace that the term "big data" has become popular to characterise not only the volume, but the approach companies take to interpret and analyse it. The volume of data makes it almost impossible for conventional tools to process and make sense of it all.
This has given rise to a new wave of computing, where processing tasks can be distributed across vast arrays of infrastructure. New analytics tools are emerging fast, allowing people to enhance their ability to manage and interpret information. But there are limits to what people can do. In addition to simple AI applications, smarter "neural" and "cognitive" capabilities are necessary to augment what people can do to apply all this information.
What kind of person should work in information analytics?
There's a surging demand for data scientists and analysts, and people with skills in any field that has depth in numerical literacy. I think many organisations think data is just numbers, but there's an entire void of talent able to analyse and interpret human signals - emotion, sentiment and feelings. As an industry, we need more psychologists and people with arts or humanities degrees.
Looking into the future, perhaps the most valued people are those who can connect all this data to real business and customer applications.
How do you see the use of big data and AI evolving in financial services?
The application of AI and use of big data analytics in banking will increase rapidly. Machines will progressively replace the routine jobs we have today. Those people will be re-skilled as analysts, experience designers and scientists.
Customer-facing jobs will be easier and more data-driven, but the need for a human touch will never go away and may become more important. There will be a real competitive advantage in having the most intelligent information capabilities supporting your products.
