Much has been spoken about the transformative impact of emerging technologies such as artificial intelligence and blockchain, none more so than in the financial services industry. Robo-advisors are taking the place of humans, chatbots are being deployed to check balances and digital-only institutions are rocking the centuries-old banking status quo.
Underpinning many of these disruptive technologies in finance is AI – with the current momentum surrounding AI in finance centered on the customer. Talking to CBR about the momentum behind AI in the year ahead, Oracle’s Vikram Gupta said:
“Artificial intelligence is expanding day by day and I can see more and more use cases coming out, so it is all a question of creating the right model, and trying to decipher the data as you go along.”
Unsurprisingly, banks and financial organisations are tapping AI in order to improve customer experience and interaction – similar to other industries like retail and B2C.
“The focus is on the customer and how to improve the customer experience, that remains a large focus area, but there are other areas that I am seeing gaining more momentum, such as using machine learning to figure out how to improve operational efficiency within the bank,” the Vice President of Oracle Financial Services told CBR.
Machine learning, another favoured buzzword with its roots firmly in AI, could be leveraged to create next-gen customer experiences in finance, as well as improving operational efficiency in banking and finance.
“Machine learning is now trying to pick up patterns, and then starts suggesting products for certain types of customers. So we achieve a focus whether it’s on customer retention, cross-product, or what the next best product offer is, or how to improve the entire experience,” said Mr Gupta.
Predicting customer behaviour could prove a goldmine for finance, but Mr Gupta is not selling machine learning as a new technological revelation in finance:
“From a banking perspective, what we are trying to look at is what are the type of customers that will be default, what is the pattern that you see for customer retention; we are trying to use models to predict customer behaviour.
“It is not a new phenomenon, we have built some models for customers, and we are working with some customers on proof of concept (POC). If you get into the realm of machine learning it is all about what is the best model you can create and how the data gets populated over the period of time, and then what is the answer you derive out of this model.”
While banking and finance are trying to get to grips with machine learning, they are also being rocked on another side, with yet another favoured buzzword looking to shake the entire industry to its core. This may sound dramatic, but blockchain could prove revolutionary if done correctly.
“What we have done for a bank is we actually went and implemented a use case, and we believe that the blockchain is much better from an intra-bank perspective, where the bank can host their own hyperledger or blockchain technology.”
Outlining another use case, Mr Gupta said:
“if you have a client in London who is buying goods from Hong Kong and he opens a letter of credit, but also wants to book the loan in New York – instead of doing all of this manually, you can create a buyer’s credit, and the system will automatically send out all of the messages, to New York, as well as releasing the money to the seller in Hong Kong.”
The Oracle VP gave a timeline of around one to two years for blockchain to really hit it big in finance and, when coupled with the 12 months ahead for AI, could point to the financial services industry being on the cusp of a total transformation. Time will tell if the tech buzzwords break the centuries-old banking industry and start delivering on their promises.