How banks are using Watson

Despite banks’ simultaneous excitement and fear of artificial intelligence as perhaps one of the most transformative technologies for their business, they’ve been quieter about IBM’s Watson.

Watson is a cognitive technology and super-computer comprising AI that “learns” how to draw conclusions from data, natural language understanding – which allows it to read and understand unstructured data, like social media posts and digital photos – and a search engine that can comb through millions of data points in seconds.

It holds enormous promise in the long term for banks, who hold troves of customer data they’re constantly studying and using to create better customer experiences as well as improve operational efficiencies.

“What a Watson could deliver to banks would be tools to ensure sales people are selling the right things to the right people at the right time,” said Ryan Gilbert, a partner at Propel Ventures. “Wells Fargo probably wouldn’t have an eight financial product sales challenge if it had a Watson,” because Watson wouldn’t have allowed such rules to be set for employees to follow.

In the short term, these kinds of improvements will continue to manifest in digital banking chat bots, digital “personalities” programmed to be able to carry on a conversation with a customer. Banks are currently using other AI solutions for these experiments.

Here is how Watson has been used by banks so far.

Regulatory compliance
In November IBM bought Promontory Financial Group, an extremely influential strategy, risk management and regulatory compliance consulting firm in the financial services industry. In doing so, IBM hired its professionals — ex-regulators and former financial services executives — to teach Watson how to address banks’ compliance issues and ultimately create an AI capability that can sort through all the data banks collect to find problems and create solutions for critical needs around financial risk modeling, surveillance and insider threat, and anti-money laundering and Know Your Customer rules.

This marks the initiation of Watson’s move into banking, Gilbert said. It’s not clear how the Trump administration will move on the supposed unraveling of Dodd-Frank, the financial reform bill put in place after the financial crisis. However it moves, it won’t take away from the importance of regulatory compliance and the emerging so called regtech industry.

“If the administration does untangle a majority of the prior administration’s regulations there’s going to be a huge industry around compliance, a lawyer stream and it’ll be a compliance officer’s nightmare,” Gilbert said. “What better than an AI-powered system to gather data and get it all figured out?”

Empathetic bots
Royal Bank of Scotland is developing a chat bot called Luvo to answer customers’ questions in near-real time. Luvo uses IBM Watson Conversation, a cloud-based cognitive tool, which means computing systems learn as information changes or needs evolve. The service was made available in December to 10% of its banking customers through its web chat service and is still in the testing phase. By answering more basic customer questions, Luvo allows RBS advisers to devote more of their time to customers with more complex inqueries. It responds to customers to the extent that it can; if it’s too complicated then Luvo can pass them onto an adviser.

In the future, RBS plans to employ Watson Alchemy Language capability, which would help Luvo better understand customer sentiment – happiness, sadness, frustration – and change its tone and actions accordingly.

For example, it would be able to sense the difference between a customer needing to replace a lost card versus a stolen card. The latter can be a more emotional experience, and Luvo would probably pass the customer onto a human adviser. If someone simply can’t find a bank card, that’s something Luvo could provide some information about quickly.

 

Military separation advice
USAA customers, many of whom are current and former military members, can ask Watson questions and seek advice on transitioning back to civilian life on the bank’s website.

The Watson Engagement Advisor answers questions related to military separation on topics like job searching, home purchasing, military benefits and more. For example: “Can I be in the reserve and collect veterans compensation benefits?” or “How do I make the most of the Post-9/11 GI Bill?” This requires that Watson comb through volumes of USAA’s business data to feedback answers to member’s inquiries.

Wealth management advice
Australia’s ANZ Group has perhaps been Watson’s highest profile banking user. The bank employed Watson Engagement Advisor for its wealth management offerings. ANZ staff — advisors, product experts, legal and compliance staff and customer service people — feed documents and data to the supercomputer about the bank’s products, including their latest terms and conditions.

The technology is meant to help personnel assist customers with deeper insights and at a faster pace, but also employs the Ask Watson feature — the same used by USAA — to give customers feedback to guide their purchase decisions and troubleshoot their problems.

Personalized banking
Citigroup has a long working history with IBM to bring information technology into financial services but it was just a few years go that it brought Watson into its business to explore ways to advance analyze customer needs, improve customer interactions and process vast amount of financial, economic and client data.

At the time, Citi said using Watson’s content analyzing and learning capabilities would help it deliver more simplified banking services, intuitive branch experiences and personalized banking.

WTF is cognitive banking?

Your next bank might be Skynet, if IBM has any say in it.

Though many companies offer AI solutions for financial institutions, IBM is championing the use of cognitive computing in banking, publicizing the term as a new paradigm.

What is cognitive computing and how does it apply to banking?

Based on machine learning, natural language processing, and human interface technologies, cognitive computing systems can learn as information changes and requirements evolve, and easily interact with users, other devices and other data sources. In contrast to traditional computing models which tabulate and calculate based on preconfigured rules and programs, cognitive systems can handle situations that are dynamic and information rich.

When applied to banking, cognitive computing can offer a wide set of benefits to both banks and customers.

What does a fully cognitive bank look like?

Imagine banking was as simple as a Google search. Instead of surfing multiple pages on your bank’s app, you type or talk to a  single input box: “I lost my card.”  A quick chat with a rep you didn’t even realize was not human and the new card is on its way. Compare this to the current frustration of clicking multiple links to find the right phone number, and one can easily see the benefits.

Banks can also leverage machine learning to predict financial needs and proactively suggest to a customer a personalized loan or to transfer money to a saving accounts ahead of a coming purchase. Leveraging a lifetime of customer data, banks will be able to truly personalize the services they offers each client, at scale. A seamless omni-channel experience, often conversational, can turn banks into a trusted advisor who is available when we need it.

Since a cognitive system learns and improves with every iteration, a virtuous cycle of customer satisfaction is formed.

Are banks adopting the new paradigm?

If you banked in the last week, you probably know the answer.

Generally speaking, banks are still testing the waters when it comes to cognitive banking. In a 2016 survey conducted by IBM, just 11 percent of bank executives reported they have adopted cognitive technology. 58 percent named improving operational efficiency as their most important strategic priority right now, which might explain the low adoption rate. Banks are generally focused on cost reducing activities and do not make needed IT investments.

In the same survey, 49 percent cited [the rather superficial outcome of] operational efficiency as the main benefit of cognitive computing, indicating bankers are a bit aloof to the transformative potential of it.