“Goodness, where do you start?"
Dave Morgan smiles when asked for advice to business technology professionals wanting to build a career in data.
“There are so many things you can do,” says Morgan, co-founder of Fuelled.co.nz, a Xero preferred financial services partner, and who was most recently, Head of Portfolio Analytics at Kiwibank.
He was the first to hold the latter post at the bank, where he was able to parlay his specialities in credit risk management, risk management infrastructure and modelling, and analytics that he honed at ANZ Bank, Barclays, and National Australia Bank.
He held the role at Kiwibank for five years and his responsibilities ranged from credit risk data and analytics, stress testing, capital adequacy, delivering materials capabilities and technology in data management, and building a multi-disciplined portfolio analytics team.
We helped other areas in the bank, leading the charge on good data and analytics, so much so that the team is seen as the ‘go to’ people for the heavy and hard questions on analytics and data
High-growth mode
Analytics, he says, has made the bank operate more efficiently, work smarter and grow in a manner it understands the underlying credit risk.
“We are pretty confident we are doing the right sort of lending to the right people and compared to the time to approve [loans] we used to run with, which was weeks.”
When we started the team up, the bank had a lending book half the size of the lending it has now, he says.
“It has doubled its lending in four or five years and there is no way you could have done that without the [analytics] kit we put in,” he says. “Because of that, I estimate we have probably allowed the bank to put an extra $2 billion of lending we wouldn’t have otherwise have done.''
He says after starting the analytics programme which now has 12 members, they built “a few more things as well”.
''Analytics allowed the bank to operate quicker, smoother and more efficiently when it comes to lending and decisioning processes, and obviously be better informed than it was prior [to the programme becoming operational]. It is great that it is a bank owned by New Zealanders and in the risk analytics side, it is now well-heeled.
“We helped other areas in the bank, leading the charge on good data and analytics, so much so that the team is seen as the ‘go to’ people for the heavy and hard questions on analytics and data.”
During his time at Kiwibank, the team deployed Enterprise Guide and Enterprise Miner from SAS, to build the bank’s risk platform. These were also used in the marketing and balance sheet management areas.
Read more: Four best practices to kickstart advanced analytics: Gartner
The next process for the bank, he says, is rolling out Visual Analytics in early 2017.
“This is going to take the reporting side to the next level and the ability that users have to drill down and perform their own analysis on the fly,” he states. “Instead of using Excel and Powerpoint, they will be able to use Visual Analytics on their Mac or tablet.”
The aim, he says, is to roll this out to executives and general manager level.
“I think it will create a contagion,” he says. “We think other parts of the bank such as products and sales, will want to use it.”
You have got to have a good, solid technical base and understand the business you are working in.”
Leading a ‘bankwise’ team
As for building a good, data-driven team, he believes one of the keys to their success is the team members’ domain knowledge and expertise.
“We have people who have been in analytics and banking for a long time, who wanted basically not to have to work with a legacy system.
“They have an approach that isn't just risk centric. They are ‘bankwise’, they take a good look around them when they are doing things.”
They also take a long-term view of the investment and direction and how it will integrate with the rest of the organisation he says.
“If you are going to build a credit risk engine and infrastructure that's a great thing,” explains Morgan. “But make sure you build and design it in a way that you can add other non-risk components to it.”
For data professionals starting their career, he says, “You have got to have a good, solid technical base and understand the business you are working in.”
The end game should be, “I am going to turn this [what they are doing] into a language the executive and board can understand.”
While he states this is not a new perspective, “often technically minded people get stuck in the technical [details], without realising they should be speaking in a different language to different parts of the organisation.”
The technology is not enough, he points out. “You have to also be concerned about process and people.”
“It is also about who do you take on the journey with you, how do you influence them?”
He says he and the analytics portfolio team at Kiwibank did “a lot of socialisation” to get their ideas and messages across, and get people confident and familiar with what was going to happen before they started the investment five years ago.
“The team has evolved to helping other parts of the bank in data and analytics, [a] testament to their abilities, experience and bankwise approach.”
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