How can the sexiest job of this century help brokers?

by Calida Smylie20 Mar 2014
Mortgage brokers will soon understand and implement changes found via big data with the help of ‘big data scientists’ hired by lenders keen to make sense of the endless information which disappears unused each day.

“The buzz surrounding the relatively new technology of big data has led to the new job title of data scientist,” said Hays Information Technology senior regional director Peter Noblet.
“This new role has been coined ‘the sexiest job of the 21st century’ by the Harvard Business Review and there is good reason for it.
“As employers create new roles to make better use of sophisticated data models, these roles will appear everywhere from start-ups to the largest firms,” Noblet said.
According to Hays, this new breed of IT professionals – who must have a rare combination of computational, scientific and business analysis skills – will become critical to business success as they can recognise patterns and derive insights from multiple sources of data, letting them make observations and predictions.

Aggregator Vow Financial spokesman Matt Mitchener told Australian Broker the mortgage broker of the future will understand, use and implement changes found via big data.

“The biggest problem in today’s organisations is that there is plenty of data but not enough work done to analyse it to make informed decisions for the future of a business. Generally, we are all caught up working in the business to recognise the importance of trends, bottlenecks, opportunities and threats to our business.”

He said companies such as Vow would look to employ specialists to sort through large parts of data on applications, lodgements, settlements, and product mixes. They would identify bottlenecks within business processes as well as recognise general focus trends.

There is no reason as to why mortgage brokers cannot also use data to improve their processes, reduce costs and boost performance, Mitchener said.

“The big banks have departments and analysts who work through this data for best process and practice to ensure the greatest efficiencies. With big data becoming more readily available to smaller businesses, mortgage brokers may employ a data scientist to pour through data and provide recommendations to an organisation they previously could not see.”

There are plenty of efficiencies to be created in the mortgage industry from a marketing point of view as well, Mitchener said.

“With all of the customer data we have on file, who should we target for various promotions and campaigns for the best ROI? Database segmentation and up-to-date CRMs will be a key focus for any serious broker to implement big data capture and future implementation.”

However, Brett Spencer, director of mortgage services support provider Stargate Group, said while hiring big data scientists is an interesting concept for the mortgage industry, he believes the industry is still too small for this be given any serious consideration.

“The likelihood of brokers hiring data scientists would be zero and I never see that happing due to the spread and average size of the data set that a broker has at their disposal,” he said.

“Larger aggregators and lenders will definitely benefit from using data scientists to mine their database for statistics and modelling, but I would be surprised if most of them are not already doing this.

"Those that aren’t doing this are missing out on a very important aspect of their business management opportunities.”

Spencer said data is the key to managing a business and planning the future and he already sees companies issuing reports based on data sets, which helps others with their planning process.

But while this provides great tangible benefits to the company doing the data mining, it provides very little actual tangible benefit to the industry, he said.

“I don’t see any value for brokers as they are too small to take advantage of using data scientists. They should simply learn how to mine their own data using the tools provided to them in their CRM or loan processing systems.”