Combining Customer and Market Data – an Experiment that is Soon to be a Reality

Johanan Thomas, Performance Director, Wealth, at Refinitiv, the global provider of financial markets data and infrastructure, gave a fascinating, lively and detailed presentation at the Hubbis Digital Wealth Asia Forum to offer his insights on the technology and data capabilities required to empower advisors to better serve their clients. He highlighted the evolving needs of the investor, and how advisers can rise to the challenge and stay relevant. His main thesis was that combining customer and market data can help drive customer centricity and higher productivity for advisors.

Refinitiv is a global provider of financial markets data and infrastructure. The company was founded in 2018, when the Financial & Risk business was spun out of the Thomson Reuters. It is currently jointly owned by Blackstone Group, which has a 55% stake and Thomson Reuters, which owns 45%. The company has an annual turnover of around USD6 billion, with more than 40,000 customers in 190 countries. It is currently part of a transaction to be acquired by the London Stock Exchange Group, and is pending regulatory and anti-trust clearances with the deal expected to close in second half of 2020.

“Many of you of course will know us by our former name as Thomson Reuters,” Thomas began. “But we rebranded under the Refinitiv name and changed our company motto to ‘data is just the beginning’. I am a data enthusiast myself and throughout my career I have spent time championing the use of data to make decisions, to draw insights and to drive business. But the reality today is that it is increasingly challenging to consume the vast amount of data that is being generated, coming as it does from various sources and housed within different systems.”

The challenge

He added that even if it possible to somehow bring all this information together, one still struggles to know where to start. “Today’s presentation,” he explained, “is not to tell you we have the answer. But we are making progress, and in this talk I would like to take this audience through two sets of data that I think, when brought together, can unleash some real productivity and client centricity.”

The first, he reported, is customer data, owned by various financial institutions and getting increasingly disintermediated by the advent of open banking. The second is market data provided by various financial data vendors, including Refinitiv, which is getting increasingly commoditised, reinvented and repackaged.

Customer data – what is it?

Customer data spans a very wide range of variables and a bank would be very fortunate to have all of it. It reflects some of the customer’s investment behaviour, including of course their investment activity that could be driven by the customer’s risk preferences and risk tolerance, them being a factor of their individual profile and behaviour. “Additionally,” Thomas added, “you could have access to a customer’s financial information, access to their portfolio holdings, their income, the size of their household, the properties that they hold, where they live, and further on you might even have access to their spending history, access to sort of loans they have taken out in different institutions, credit card spending Finally if you have deep enough relationship with your customer, you would also know their interests, hobbies, goals and ambitions.”

That all adds up to a lot of information that an RM has to keep track of just to service this customer. “But what does not help is that all of this information could be sitting across various different platforms within a bank,” he noted.

Market data – the other half of the equation

Thomas explained that to give valuable advice to his client, the RM needs to understand the various asset classes that form an optimal portfolio. Each of these asset classes have different performance and risk metrics that the RM needs to consider. On top of that, the RM needs to layer in recommendations by the in-house research teams or the Chief Investment Officer, to reflect the house views of what products, investment strategies and securities are recommended by the bank.

The RM then needs to layer in additional information set out by the product teams, for example, product risk ratings, product due diligence and what sort of risk disclosures are required before advising on a specific product.

“So,” he noted, “there is a lot of information that an RM needs to keep track of, but none of this will be useful if it is not personalised to that specific client’s needs. Just like Netflix or Spotify which recommend movies or music to each user’s unique tastes and preferences, we are moving into a world where wealth management clients are expecting that level of personalisation and recommendations.” The ultimate aim of the RM then, he concluded, is to provide the right advice to the right client at the right time.

Bringing it all together

With all the different sources of data sitting in different systems, the RM’s job is ever more challenging. “Nearly 60% of the advisors globally are not satisfied with their firm’s technology and data capabilities to generate valuable insight for their clients, while 73% of wealth managers are not happy with their mobile platform and capabilities,” Thomas explained, citing a Refinitiv Webcast and a Forbes Insights/Thomson Reuters survey. 

“All this adds up to a considerable opportunity,” he commented. “Things are not working as well as they should, and data is not being used as well as it could be.”

He then mined down into more detail on the needs of the advisor. First, it would be helpful to bring customer data, account and portfolio data, and market data into one single view. This can then be layered with automation and the use of analytics to identify which market events impact which securities of which customers. “But,” he cautioned, “it will not be helpful if it is not personalised to the client, taking into account all the contextual information that the bank has about this customer like their risk tolerance and financial goals.  The solution must also be responsive and instantaneous, so that if the RM receives an unscheduled call from the client, the RM can access the information at one click, and easily then offer the right and relevant advice.”

Bring on the power of tech

Thomas then said that the ‘power of technology’ can solve these major challenges. He explained that a wish list of features required would include the platform being cloud native, or even better cloud neutral, as that gives banks the opportunity to work with the cloud computing vendor of their choice.

Second on the wish list would probably be to ensure all the analytics capabilities developed are deployed effectively on the platform, and to also ensure that in the future all the data that the platform houses can also benefit from these analytics capabilities as well.

“Then you probably want to add in the market data content, which comes with all the news, commentary, research, fundamental and macroeconomic data, fund and stock information, etc, all coming in through the cloud.”

This means the wealth management firm has then taken care of half of the equation and then needs to add in the other half, customer data. But this might be sitting across different platforms within each financial institution, and each of those platforms may well have been developed by different vendors, all in different code and architecture, none of which communicate with each other.

Enabling connectivity

“To bring all this customer information into the central data platform, you may choose to deploy a customer data layer that can connect each of these systems, standardise the information, aggregate it, and pull in the relevant customer records and push it up to the data platform,” Thomas explained. “Having then merged the customer and market data together, you then have to solve the distribution element. And to do that, you may decide to build some API feeds to your existing front-end, and also offer them to the end-client, via mobile apps into their smartphones.”

He added that the firm could even take it one step further and build entire workflows, so the advisor can spend less time in discovery and search of relevant content and ideas, and instead spend more time in relationship building and providing personalised advice.

He then offered delegates the example of a day in the life of such a banker that might use such as solution, highlighting how smart use of the data and analytics can help the RM manage his clients and his work tasks efficiently. This included knowing all relevant activities he had to undertake for a specific client and being armed with personalised advice and recommendations for the all-important client calls. He explained that even if posed some surprising questions on a topic the RM isn’t particularly close to, all the RM needs to do to avoid being caught off-guard is to open up the relevant tab on the topic and access easily all of the market information, key facts summarised, the most relevant news and latest updates, as well as ready access to research from internal and external sources on the hot topic of the day.

Smart and proactive approach

“Furthermore,” he added, “the system smartly identifies which clients are impacted by certain events, based on their portfolio holdings, and also which of their holdings might be affected by those events. So, the RM can always have a valid conversation with the client, and help them rebalance their positions, if so required.”

All this means, very simply, that the RM is demonstrating, time and again, how relevant they are to their clients. “They are providing targeted, relevant, personalised advice,” he commented, “and is able to be highly responsive. And from the client’s perspective, they are getting advice that is entirely relevant to their specific needs and situation. Which results in life being a lot easier for all parties when customer data and market data can come together.”

Why stop there?

But Thomas had one final twist to his presentation. “Why stop there?” he asked delegates. He proposed, “if that information is available to the RM, why can it not also be pushed to the client to ensure the client can also make informed decisions based on the same information that the RM has access to.”

And that is precisely what Refinitiv is now doing. “We are already in pilot testing for this product and will launch at some point next year, all made possible from the significant investments we have made in machine learning and artificial intelligence, as well as in natural language processing and knowledge graphs. We actually believe that AI and machine learning will be the single biggest enablers for the financial service industry and are excited to be applying those capabilities to your customer data. And remember, data is only the beginning…”