J.P. Morgan urges super funds towards big data

J.P. Morgan’s securities services division has urged its Australian superannuation clients to embrace big data technologies to avoid losing members as the industry faces fresh reforms.

Although Australian employees have been able to choose their superannuation funds since 2005, most remain in their employers’ default funds.

J.P. Morgan Worldwide Securities Services (WSS) client management head Bryan Gray said Australia had a large, disengaged population of superannuation fund members.

“Eighty percent of people are sitting in default funds or will roll into MySuper funds very shortly,” he said, referring to the Government-mandated default product to be introduced next July.

“What happens is as soon as those members wake up and become engaged, all of a sudden they start disappearing to self-managed superannuation funds.

“What our funds are tackling at the moment is how do you identify the point at which those individuals are going to start thinking about a self-managed superannuation fund.”

J.P. Morgan WSS holds more than $400 billion of financial assets for 100 superannuation and investment funds in Australia, including AustralianSuper, First Super, Vanguard and Schroders.

Gray said the company was advising Australian clients to analyse their data stores to identify trends and any changes in individual members’ behaviours.

He suggested running sentiment analysis on customer relationship management data, as well as identifying “people who have never logged on to your website in their life and all of a sudden are logging on”, who could be at high risk of switching funds.

Gray acknowledged that J.P. Morgan WSS was not involved in applying big data analytics to superannuation fund member data but looked to share the wider organisation’s expertise with its clients.

J.P. Morgan had more than 260,000 employees across the globe and a firm-wide engineering and architecture group tasked with exploring and delivering new technologies.

WSS global funds services CTO Bill Conyea said the firm sought to apply big data technologies to three categories: increasing revenue; retention and loss mitigation; and improving efficiency.

In the US, J.P. Morgan Retirement Plan Services used data mining techniques and behavioural science to target communications to individual members.

The US group sent targeted messages to certain people approaching retirement age, for example, encouraging them to put more money into their retirement funds.

Those communications would include targeted imagery, such as luxury goods for certain demographics, and sent through the most appropriate medium, be it print or digital.

Conyea said the firm had also developed algorithms in the past four years to scan its source code – whether homegrown or vendor-developed – to determine its quality.

The analysis informed a firm-wide “index” that ranked the quality of code produced by various lines of business.

“We’re putting almost our entire code base into several tools to take a look at style of coding and improve the quality of our source code,” he said.

“Instead of doing code reviews, which could be labour-intensive, we’ve got some early warning systems around [blocks].”

Sharing financial data for self-managed super funds

Earlier this year, J.P. Morgan WSS unveiled a two-year, $30 million project to improve the provision of data to institutional investors.

The division’s head of e-solutions services William Fraser said last week that its data feeds powered clients’ investment front offices, performance and risk systems.

J.P. Morgan WSS transmitted data in xml or flat file formats to 26 clients currently, up from about six clients 18 months ago.

Gray expected the financial data services to allow superannuation funds to offer more customised investment options, allowing members to effectively manage their own retirement funds.

J.P. Morgan WSS highlighted self-managed super funds as a particular threat to its clients, with the tax office reporting a 31 percent growth in number of self-managed funds in the four years to 2011.