Robo, blockchain and predictive analytics – applications in wealth management

Timothy Neville, Singapore based Managing Director of wealth technology company FNZ, made a presentation to delegates attending the Digital Wealth Forum on the application of Blockchain, predictive analytics and robo advisory within the wealth management sector.

FNZ partners with major financial institutions to enable them to provide multi-channel wealth management services to their clients across direct, intermediated and workplace channels. The company provides a fully outsourced ‘platform-as-a-service’ model, which includes its core wealth management technology platform, tailored to a client’s specific requirements and then supported by full wealth management investment operations services. 

FNZ first started in New Zealand in 2004 and is now headquartered in the UK where it is the market leader.  FNZ has over 1300 employees globally and has delivered wealth platform solutions for financial services companies in Europe, Asia, Australia and New Zealand. 

“In financial services technology today, to be relevant, you really need to provide scale,” Neville explained. “We now have around SGD$400 billion in assets on our systems globally, primarily in Europe, Asia, and Oceania. We have 52 global customers, all predominantly blue chip financial institutions. We are now building out our presence in Asia, which is our current key strategic focus.”

“Our technology helps deliver scale, efficiency and control,” Neville told the delegates. “We achieve scale aggregation through a single technology and operating model. This allows our customers access to the scale based pricing and continuous innovation of a platform they often do not want to build or maintain themselves. On top of this we offer continuous security and data protection, as well as global market connectivity and operations across all asset types.”

He then explained that FNZ also focus on innovation to complement its core wealth platform offerings. “Specifically, FNZ’s recent focus has been on building out its Robo-Advisory, Blockchain and Predictive Analytics capabilities in a wealth management context.”

My friendly Robo

Neville explained that what he termed the ‘Robo-revolution’ has advanced the industrialisation of digital advice across the industry, but from FNZ’s perspective, a large part of the market is not progressing. “A key problem as we see it, is that a lot of Robos have simply sought to automate old financial advisory processes. This may create greater efficiency, but does not really improve the investment proposition or optimise the investment outcome for the end investor. It is exactly in this area that the market is focusing on.” 

But at the front of the Robo in the digital engagement space, this has improved dramatically over the last 5 years. 

Better digital engagement and psychometric modelling means the Robo obtains more and better information. “The more quality information a Robo engine obtains from a customer,” Neville noted, “the greater the likelihood of an investment proposition matching that customer’s preferences or needs.”

Individualising the Robo experience 

Accordingly, the next step is true individualisation of Robo advice, which at the risk of being somewhat technical, occurs through a centralised investment strategy, optimised for individual client goals, combined with an objectively assessed risk profile. “In simple terms,” Neville elucidated, “this means in practice you could have 100,000 customers on your wealth platform, coming through the Robo adviser, all with different investment portfolios that are optimised to each individual. Now that is a very, very different proposition to the traditional wealth management platform service.”

Neville also noted that the Robo requires a seamless connection to the wealth platform. “The seamless connection of the Robo integrated into your execution and settlement platform is what creates the experience for the customer, or the adviser using the Robo as the case may be.”

Neville does not see Robo as a replacement for the financial advisor. “We see Robo as a way that allows the financial advisor to focus on the things that are important to them, which is very much customer engagement and understanding.”

Blockchain – a transactional revolution in the making

Neville moved on to the topic of Blockchain, which is a distributed ledger technology most publicly applied to the creation of cryptocurrencies, especially Bitcoin. 

“It is the underlying technology that I wish to focus on, as distributed ledger technology will start to eliminate the need for centralised authorities. It will start to eliminate the need to certify ownership and clear transactions, and in the wealth industry, that is really significant. It is a cost play, an efficiency play, and a risk management play.”

Neville reported that in the UK, FNZ has established a consortium of the top six asset managers representing 30% of assets under management in the UK market with the aim of transforming market-side transaction processing using Blockchain technology.

“This will be a private Blockchain, not a publicly accessible Blockchain like Bitcoin. Phase 1 of this solution, due in Q4 this year, is to deliver potential T+0 settlement for all mutual funds using this technology, with real-time regulatory reporting. This alone is a revolution in the making - it is transformational and a vision for the future. The next step would then be to create a multi-jurisdictional global asset management shared ledger solution.”

Predicting the future

He then touched on predictive analytics, which is machine learning and statistical modelling applied to data. “Within wealth management it has considerable application, but first requires the necessary data. Neville said, “the institutions and BPO wealth vendors are the only entities with genuine data relating to wealth management customers – with these data sets, predictive modelling that can add value can be developed using the standard trial and error process of arriving at optimal models.” 

FNZ has progressing quickly in this space and Neville provided 2 specific examples.  

FNZ are rolling out an investor attrition predictive model in multiple markets currently.  In other words, attempting to predict the risk that a customer may leave a wealth product, platform or service. Neville outlined the 55 predictors within the FNZ investor attrition model that can be used by customers to indicate if an investor may leave your business. This creates an immediate call to action allowing the institution to intervene on that at-risk customer or group of customers. 

Another example provided was using predictive analytics to produce targeted mutual fund marketing. FNZ has worked on this in Europe and is now rolling out in Asia through their Singapore hub. “We can identify a sub-demographic profile, a group of people that are the most likely to purchase a particular fund based on historical fund purchase profiling.  We then overlay a model of demographics in the region where the fund is being marketed (i.e. Singapore) and then we conduct a matching exercise say across the 28 districts of Singapore. Once the highest concentration districts are identified against the target sub-demographic, an automated marketing campaign can be triggered from our Predictive Analytics platform to Google adwords as an example.”