Using big data to boost human relationships

Sleek software systems allowing instant reporting and responsive client interaction have received much recent attention. But just as important is the data that runs on them. Indeed a state-of-the-art system can prove counter-productive and expensive without clean and accurate data beneath. The ability to contort data to reveal strategic insights and deliver tangible benefits to relationship managers now presents banks with a key strategic advantage.

The new focus centres on how to best use data rather than seeing it as something static and worthless. Client demand, as well as relationship mangers’ desire to consolidate information into a “single client view”, have added to regulatory requirements and technological advances to further fuel demand for comprehensive data frameworks within private banks.

Nowhere is this quest for data integrity and usability more clearly demonstrated than at the “front end”, where the speed, frequency and quality of information given to clients makes all the difference. If a bank can use data to empower the relationship manager as well as giving the client information to become empowered, a closer relationship can be developed between the two. 

“Digital technology and use of underlying data will complement human interaction between the client and relationship manager,” comments Holger Spielberg, head of innovation, Digital Private Bank at Credit Suisse. “At the same time, that human interaction will be enabled and empowered by strategic insights gleaned from mining data. This will lead to efficiency of business and generate client service.”

Now that rapid technological advancement and economically viable algorithms have given wealth managers the ability to react to compliance, creating strategic advantage is the next logical step, he says.

Indeed for relationship managers, the threat of the ‘robo-adviser’ concept means human interaction needs to offer much more than previously. Access to tax and investment profiles, and leveraging a rules and risk-based decision-making process to service an information rich and self-service orientated investment community has become a pretty standard service. 

“We are looking to give relationship managers the power to better serve clients,” says Mr Spielberg. “We can mine the data to find out how many products and services are relevant to customers and where the product affinities lie. Where are the gaps, and what is the untapped potential? Effectively we are giving the relationship manager something concrete to go on.”

This approach involves delving deep into existing data to create new opportunities, explains Vincent Kilcoyne, capital markets industry lead at SAS. “The wealth manager needs to have a multi-level play to know what to offer to whom and when,” he says. 

“The data is mined to identify a small cluster of people who have similar attributes and are interested in a particular asset class. That cluster can then be offered access to specialist research in a timely fashion. The secret lies in being able to identify both the cluster and the research and putting the two together quickly.”

This process adds to the quality of the relationship by personalising it. It builds trust and ultimately retains clients, explains Joe Norburn, head of digital at Coutts. “The better the data, the more we can equip our advisers with insight. The various data sets would previously have been drawn from multiple systems making visibility hard,” he says. “We have relocated all this data in our online channels and it’s all pulled together to give a thorough overview.”

This personalisation of structured data can also be supplemented by other contextual data that can be drawn from conversations, notes and third party data, including public information. By adding this to data already held, banks can gain further insight and context and can give their advisers a more rounded position from which to start any conversation with the client.

Client centric

The other side of this change in private banking mindset is becoming more client centric. This is not simply about being able to know what data is relevant and making it available, but doing it in a way that clients want and in real time. 

Credit Suisse is currently in the middle of this overhaul, explains Mr Spielberg. “Our process is about reshaping the private banking experience around digital. We are committed to making significant investments in expanding our client-facing technology globally to enhance clients’ access to portfolio analytics, research and market data, plus collaboration and transaction services.”

This project began in Asia with the launch of a global digital private banking platform in March this year, giving clients flexible access to comprehensive and personalised information about their accounts, market insights and intelligence. The platform is designed to facilitate multiple channels of connectivity and collaboration for clients with their relationship manager and Credit Suisse.

The value in this lies not just in the digital offering. To make sure the platform offered tailored research and investment ideas, the bank looked at underlying data and analysed how clients make decisions in relation to their finances instead of categorising them by assets under management or source of wealth. 

Coutts too has made strides in this area, according to Mr Norburn. “The idea is to humanise digital interactions by being more accurate about who we put any given research in front of. This makes research more immersive because we have been more selective about making it available only where we know it is of interest.”

Flexibility

Being able to mine data in a way that is flexible allows for this identification of individuals’ interest. Looking at data from several different angles means wealth managers can reveal not only something that they do not know, but how that relates to something that they do know – combining the two makes for an actionable insight.

“The traditional way of having a mosaic to segment the client base pretty much stops identification of smaller clusters as a mosaic’s edges are pre-defined,” explains Mr Kilcoyne at SAS. “Rather than analysing along predefined lines, the idea is to be able to follow a trail of data breadcrumbs that leads to an event and then looking to see if that trail has been replicated elsewhere. This can help us understand churn or changes in investment patterns and to act upon it.”

Data giving the bank the ability to reveal patterns, connections and trends, which are so far unknown, allows the banks to put real strategic insight and decision making into place, he says.

An example of this is recording conversations, allowing banks such as Coutts to mine those conversations, revealing the same comments are coming up again and again. 

This sort of unstructured data can be added to other data to drive business decisions if, for example, no one likes a particular product or the time lag between a conversation and an action is deemed too long. 

“It is about making data useful. Getting the foundations right so that we can add new data onto old is so important,” says Mr Norburn.

Indeed there is often a clear tipping point to invest heavily in data and for private banks it is all about enabling the adviser to not be good or better but to be the best. Banks are now realising how powerful the combination of various data points around the customer relationship management (CRM) system can be. 

Adding contextual and unstructured data to that serves to raise the value even more and gives a predictive and actionable result based on facts. Having the very best CRM system gives actionable results that are scalable and timely. 

Data governance key to unlocking possibilities

Good data governance is the underlining piece of the software and data puzzle. For Coutts it has been central to its successful “re-platforming” almost four years ago. Without having good governance around the underlying data, any efforts surrounding software of data analytics are pretty much negated, according to Joe Norburn, head of digital.

“One of our key drivers has been getting to the Holy Grail of a single golden copy of data and a single client view. Re-platforming forced us to look at the data and cleanse and correct and verify it before we could proceed with the migration to the new platform. It was a massive undertaking and the result is that our data is now the cleanest and most accurate it has ever been,” he says.

Following this, there is now a strong single framework and methodology for capturing and processing data within a single repository. It is, according to Mr Norburn, “strictly enforced”.

Credit Suisse too has made similar moves, explains  Holger Spielberg, head of innovation at Credit Suisse’s Digital Private Bank. “Data wise, we are seeking to future proof our institution – we are de-siloing data and installing a good data governance at group level. This has involved reshaping unstructured external data and mixing it with structured data we already hold.”

He also points out that good data governance goes hand in hand with the wealth management world, where sensitive data is intrinsic to the proposition. Indeed to make the most of the massive opportunity to glean strategic insight from something previously not considered to be an asset, data governance is key. Without this, de-siloing data and adding to it in contextual, unstructured or structured form becomes exceedingly hard and the end result unreliable. 

To take this a step forward the banks now also need the skills of data scientists to reveal to them trends and clusters and the “unknown unknown” as well as what to do about it.  Although there has been lots of talk in this area, banks are only now committing to the whole data idea and actively seeking to use their data as an active and valuable asset. How effectively they do this depends entirely on the resource and depth they are prepared to put in.