Putting big data to good use
11 February 2015
The asset management sector is yet to get to grips with big data. Transfer agents may be able to help
Image: Shutterstock
The world of data is getting bigger. Almost three million emails are being sent every second, some 50 million Tweets are being published every day, while Google is processing 168 petabytes of data every week.
What does this mean for investors? In KPMG’s most recent ‘Investing in the Future’ report, it asked whether big data, which is understood to be streams of information so large and complex that they are difficult to digest and disseminate, could be used to make better investment decisions.
“We are already seeing new business models emerge in the industry that claim to be able to be able to develop investment strategies, trades and hedging arrangements from the analysis of the content from millions of social media messages,” explained the firm in its report.
“Similarly, other sectors are beginning to be disrupted by new data sources. For example, in the insurance sector, the analysis of policyholders’ spending habits is starting to displace traditional actuarial data as a more appropriate predictor of individuals’ risk (and therefore pricing) profiles.”
“Can this happen in investment markets in an analogous manner? What would investment analysis look like in the face of big data going forward and what could it mean for alternative investment strategies?”
The conclusion drawn by KPMG and others is that the asset management sector in particular is yet to get to grips with big data. Ian Smith, financial services strategy partner at KPMG in the UK, said: “Asset managers still have a long way to go to recognise and exploit big data and data analytics. While IT is already attracting a significant amount of investment, it is not being channelled into the right areas. Many businesses are putting their efforts into trying to unpick the complex legacy of disparate systems and technologies while trying to make sure they provide the right level of control to meet increasingly stringent compliance.”
“There is too little focus on building the architecture to meet the business needs of tomorrow. Platforms will need to be redesigned with the flexibility to support a much more diverse client base and deliver a step change in costs, control and client experience.”
Indeed, regulation is a huge driver in this area, particularly given the continued emphasis from regulators on gaining greater visibility into underlying fund investors, according to Richard Clarke, director at RBC Investor & Treasury Services, with responsibility for shareholder services within product management.
He adds: “This means that more data has to be captured to gain greater clarity as to who the investors are on the register.”
“The challenge is to take that investment to support regulatory requirements and turn it into an opportunity to provide more meaningful information to our clients and derive better returns on our investments.”
A multitude of fund types, more countries of distribution than ever before, and different distribution models, also add to the complexity of global asset management’s big data challenge.
“On the face of it, more complexity in their operating model, driven by cross-border distribution and an expansion in market coverage, alongside greater demands from regulators, are not a good combination of factors driving the cost base of asset managers. Consequently, asset managers that are unsure how to handle big data may look to their transfer agents for more support in this area,” says Clarke.
Clarke explains that transfer agents that process tens of millions of transactions per year are particularly well positioned to understand and help with the task that asset managers are facing. Specifically, turning the data associated with those transactions into meaningful and useful information.
“Asset managers need more flexible interfacing tools that will enable them to receive, store, manipulate, consolidate and interpret big data,” says Clarke. “If we can help integrate transactional data with macroeconomic trends, for example, which asset managers need for their product development teams, transfer agents can begin to support both regulatory compliance or sales management with reporting, and also provide useful intelligence to the product development teams trying to identify sales patterns, which in turn should assist in increasing returns.”
“The more intelligence that a transfer agent can provide in identifying which products are attracting whose attention and how these trends are affecting their distribution strategy, the more valuable we become to the asset manager.”
While some asset managers are deploying their own strategies around leveraging big data internally, gaining a more holistic view will be essential in order to fully appreciate investor behaviour, suggests Clarke. “Transfer agents have the benefit of processing millions of transactions which, if leveraged appropriately should give valuable insights into the key trends of investor behaviour.”
“Leveraging big data is not new and the tech commerce sector (unsurprisingly) is significantly further ahead than any financial company. When you consider Amazon obtained a patent called ‘Anticipatory Shipping’ over a year ago, which is the process of dispatching an item in anticipation that their customer will order the product, it gives you some clue just how far along the path they are.”
“It is unlikely that the asset manager sector will catch up, and in many ways even take the same path, however, one would expect the potential of leveraging the innovation in big data will be realised sooner rather than later.”
What does this mean for investors? In KPMG’s most recent ‘Investing in the Future’ report, it asked whether big data, which is understood to be streams of information so large and complex that they are difficult to digest and disseminate, could be used to make better investment decisions.
“We are already seeing new business models emerge in the industry that claim to be able to be able to develop investment strategies, trades and hedging arrangements from the analysis of the content from millions of social media messages,” explained the firm in its report.
“Similarly, other sectors are beginning to be disrupted by new data sources. For example, in the insurance sector, the analysis of policyholders’ spending habits is starting to displace traditional actuarial data as a more appropriate predictor of individuals’ risk (and therefore pricing) profiles.”
“Can this happen in investment markets in an analogous manner? What would investment analysis look like in the face of big data going forward and what could it mean for alternative investment strategies?”
The conclusion drawn by KPMG and others is that the asset management sector in particular is yet to get to grips with big data. Ian Smith, financial services strategy partner at KPMG in the UK, said: “Asset managers still have a long way to go to recognise and exploit big data and data analytics. While IT is already attracting a significant amount of investment, it is not being channelled into the right areas. Many businesses are putting their efforts into trying to unpick the complex legacy of disparate systems and technologies while trying to make sure they provide the right level of control to meet increasingly stringent compliance.”
“There is too little focus on building the architecture to meet the business needs of tomorrow. Platforms will need to be redesigned with the flexibility to support a much more diverse client base and deliver a step change in costs, control and client experience.”
Indeed, regulation is a huge driver in this area, particularly given the continued emphasis from regulators on gaining greater visibility into underlying fund investors, according to Richard Clarke, director at RBC Investor & Treasury Services, with responsibility for shareholder services within product management.
He adds: “This means that more data has to be captured to gain greater clarity as to who the investors are on the register.”
“The challenge is to take that investment to support regulatory requirements and turn it into an opportunity to provide more meaningful information to our clients and derive better returns on our investments.”
A multitude of fund types, more countries of distribution than ever before, and different distribution models, also add to the complexity of global asset management’s big data challenge.
“On the face of it, more complexity in their operating model, driven by cross-border distribution and an expansion in market coverage, alongside greater demands from regulators, are not a good combination of factors driving the cost base of asset managers. Consequently, asset managers that are unsure how to handle big data may look to their transfer agents for more support in this area,” says Clarke.
Clarke explains that transfer agents that process tens of millions of transactions per year are particularly well positioned to understand and help with the task that asset managers are facing. Specifically, turning the data associated with those transactions into meaningful and useful information.
“Asset managers need more flexible interfacing tools that will enable them to receive, store, manipulate, consolidate and interpret big data,” says Clarke. “If we can help integrate transactional data with macroeconomic trends, for example, which asset managers need for their product development teams, transfer agents can begin to support both regulatory compliance or sales management with reporting, and also provide useful intelligence to the product development teams trying to identify sales patterns, which in turn should assist in increasing returns.”
“The more intelligence that a transfer agent can provide in identifying which products are attracting whose attention and how these trends are affecting their distribution strategy, the more valuable we become to the asset manager.”
While some asset managers are deploying their own strategies around leveraging big data internally, gaining a more holistic view will be essential in order to fully appreciate investor behaviour, suggests Clarke. “Transfer agents have the benefit of processing millions of transactions which, if leveraged appropriately should give valuable insights into the key trends of investor behaviour.”
“Leveraging big data is not new and the tech commerce sector (unsurprisingly) is significantly further ahead than any financial company. When you consider Amazon obtained a patent called ‘Anticipatory Shipping’ over a year ago, which is the process of dispatching an item in anticipation that their customer will order the product, it gives you some clue just how far along the path they are.”
“It is unlikely that the asset manager sector will catch up, and in many ways even take the same path, however, one would expect the potential of leveraging the innovation in big data will be realised sooner rather than later.”
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