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Speaker 1: What does it take to be a top performing chief

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Speaker 1: information officer of one of the country's largest companies.

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Speaker 2: Well, Hamish Rumbold should know. He was last week crowned

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Speaker 2: CIO of the Year at the annual CIO Awards for

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Speaker 2: his leadership over the last five years in the CIO

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Speaker 2: role a Kiwi Bank.

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Speaker 1: He joins us this week to talk about the complex

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Speaker 1: issues facing CIOs, including dealing with escalating cyber threats and

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Speaker 1: making the best use of artificial intelligence.

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Speaker 2: You also has an interesting take on open banking.

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Speaker 3: We're trying to increase competition. I personally think the best

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Speaker 3: thing the government could do is support a common banking

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Speaker 3: platform that you manage most of the underlying operational needs

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Speaker 3: of a bank when any other organization can consider on

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Speaker 3: top of them and launch their own brands and products

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Speaker 3: to market relatively quickly without that overhead.

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Speaker 1: Much more coming up with CIO of the Year, Hamish Rumbold.

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Speaker 2: But first being its results season for many of our

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Speaker 2: big listed companies you've been looking for, particularly at Spark

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Speaker 2: and Korus. Over the last week they've both reported their

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Speaker 2: full year results and good bell weather stocks for the

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Speaker 2: economy at large, but also they heavily underpin tech infrastructure

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Speaker 2: in New Zealand telecommunications. Let's start with Spark. They missed

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Speaker 2: their target for earnings.

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Speaker 1: They missed their guidance, which they had just lowered a

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Speaker 1: few months ago. So right, yeah, by a few dollars.

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Speaker 1: They were just under the low end of their guidance,

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Speaker 1: which is not a great look for a company in general, unfortunately.

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Speaker 2: Yeah, so how is this company doing? In many ways,

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Speaker 2: I sort of admire what Spark has done in recent

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Speaker 2: years investing in advanced technologies. They've got their IoT network,

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Speaker 2: they've got their health tech division. They got curious that

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Speaker 2: the data company, they've sort of invested in AI capability.

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Speaker 2: They have an IT services wing as well, So they

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Speaker 2: are on that sort of transition. They realize that there's

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Speaker 2: only so much growth in selling broadband and mobile in actions.

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Speaker 2: But it's going to take a bit longer, isn't it

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Speaker 2: for that stuff to really deliver meaningful revenue and profit

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Speaker 2: to the company.

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Speaker 1: Yeah. Absolutely, I mean we don't really know the upper

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Speaker 1: end of what that can actually deliver as well. We

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Speaker 1: don't know what kind of competitive pressures they're going to

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Speaker 1: experience as that area grows in the future as well.

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Speaker 1: So yeah, it has a huge potential that in early

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Speaker 1: which could give them a kind of a first mover

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Speaker 1: advantage when it comes to creating these high tech solutions.

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Speaker 1: And to be clear, we're talking about stuff like IoT

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Speaker 1: that can ingest a lot of data and then the

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Speaker 1: ability to analyze and process and gain insights from that

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Speaker 1: data as well things like river water sensors that they've

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Speaker 1: got down in the aven in christ Church that can

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Speaker 1: automatically detect the kind of impurities and the water. Unfortunately,

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Speaker 1: they're kind of being a little bit dragged back by.

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Speaker 1: Like you said, they wanted to diversify away from broadband

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Speaker 1: and mobile and their first way of doing that really

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Speaker 1: was with its services. They were met with a real

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Speaker 1: sudden decline in eighty services though. Yeah, that's been really

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Speaker 1: rough and caused a lot of the pressures on Spark.

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Speaker 2: That business is worth one hundred and sixty five million,

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Speaker 2: so quite quite a chunk of money there, but in

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Speaker 2: decline at the moment, so revenues down there. But high

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Speaker 2: tech services, those things you talked about, Internet of Things,

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Speaker 2: their health tech division and others actually reasonable growth there

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Speaker 2: twenty one percent to seventy nine million dollars that's up,

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Speaker 2: and their data center revenue was up fifty four percent

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Speaker 2: to reach I was surprised at this only thirty seven million,

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Speaker 2: So that's a nascent area at the moment. They've invested

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Speaker 2: quite heavily in data centers, and you know, I sort

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Speaker 2: of look at the data center market and go, everyone

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Speaker 2: is building out capacity here is this a bit of

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Speaker 2: a red flag? There will be lots of data center

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Speaker 2: capacity available, but the analysts are sort of saying there's

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Speaker 2: strong revenue growth potential in both high tech and in

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Speaker 2: data centers, but it is really small sort of amount

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Speaker 2: at the moment in the scheme of things for Spark.

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Speaker 1: Yeah, we also don't really again, like high tech, we

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Speaker 1: don't know what the upper cap is on data centers,

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Speaker 1: like you say, a lot being built, but we also

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Speaker 1: know that consumption is rising massively. But there's still a

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Speaker 1: really big established company and they're looking to cut fifty

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Speaker 1: million in labor costs. Yeah, they also paying a five

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Speaker 1: hundred million dollar total dividend despite their free cash flow

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Speaker 1: only being about three hundred and thirty millions. They're going

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Speaker 1: to need to borrow a little bit more to service that. So, yeah,

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Speaker 1: a tough year for Spark. But at the end of

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Speaker 1: the day. It is a very cyclical kind of company.

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Speaker 1: They do sit in the economy of New Zealand very firmly,

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Speaker 1: and so they'll be up and down with the economy.

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Speaker 2: I would imagine sort of tough position for Jolie Hodson,

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Speaker 2: the chief executive, to be in, where she's under pressure

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Speaker 2: to get the books in order start hitting those targets

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Speaker 2: for growth and revenue and profitability. But you know, the

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Speaker 2: only way to do that at the moment really is

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Speaker 2: cost saving. So eighty million coming out, as you said,

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Speaker 2: fifty million in labor costs they've done. I think the

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Speaker 2: majority of that which has been painful I know from

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Speaker 2: people who've been let go, so they're sort of cutting

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Speaker 2: things to the bone to some extent. The question is

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Speaker 2: will shareholders have enough patience to see these sort of

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Speaker 2: high tech plans through. It's often the way with talcos

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Speaker 2: that they invest in diversifying their revenue, whether it's content

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Speaker 2: plays or it services, then they don't live up to

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Speaker 2: expectations and shareholders say, get back to your bread and butter,

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Speaker 2: off delivering broadband and mobile and that's fundamentally much more

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Speaker 2: boring business and frankly running out of margin in this country.

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Speaker 2: It's sat traded and there's not a lot of room

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Speaker 2: for growth there. So I really admire the vision Jolie

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Speaker 2: and her predecessors had to set up some of these units,

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Speaker 2: but they got to pay their way. They've got to

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Speaker 2: deliver strong growth. And will she still be in the

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Speaker 2: hot seat able to do that, I guess that's the question.

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Speaker 2: Looking briefly at Coorus, they are quite a mature business

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Speaker 2: now over a billion dollars in revenue for the first time,

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Speaker 2: which is pretty cool. And their desire to be an

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Speaker 2: all fiber business by twenty thirty, connecting eighty percent of

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Speaker 2: the country and really moving from being a builder to

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Speaker 2: an operator. Yeah that's right.

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Speaker 1: Yeah. So the new CEO at Chorus, as we know,

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Speaker 1: Mark Away, who's previously of two degrees, and he seems

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Speaker 1: to have come in with a real intention to breathing

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Speaker 1: her life into Chorus. It's been, like you said, a

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Speaker 1: very established company that spent a lot of time and

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Speaker 1: money building out this fiber network across the country, which

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Speaker 1: is fantastic and one of the best fiber networks in

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Speaker 1: the world, as we all know. But that building is

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Speaker 1: slowing down and so now always job I guess really

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Speaker 1: is to start thinking about how can he turn it

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Speaker 1: from a network builder into a really lean, agile network

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Speaker 1: operator that can continue delivering service, can continue to grow

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Speaker 1: market share of fiber, and can return the value that

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Speaker 1: it has, you know, back to investors who put in

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Speaker 1: a lot of money to actually help this network be

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Speaker 1: built out.

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Speaker 2: So they've got a really.

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Speaker 1: Aggressive dividend scheme planned, and he talked about cutting things

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Speaker 1: that don't fit that goal. One of the interesting things

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Speaker 1: that I thought he said was starting to really promote

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Speaker 1: the benefits of fiber again. Fiber has become so normalized

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Speaker 1: that we've kind of maybe forgotten how awesome it actually

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Speaker 1: is and the things that it can do. You know.

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Speaker 1: Talked a little bit about using the network in adjacent

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Speaker 1: ways as well, not to get into the weeds of it,

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Speaker 1: but he sounds like he's got a really strong strategy

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Speaker 1: for the next ten years. Talked about a ten year horizon.

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Speaker 2: Yeah, quite a healthy dividend payer. I think they're predicting

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Speaker 2: in twenty twenty five, they're aiming a dividend guidance of

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Speaker 2: fifty seven point five cents per share, up twenty one

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Speaker 2: percent on this year. So if you've ridden the share

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Speaker 2: price up got it a number of few years ago.

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Speaker 2: That's actually quite a nice little Ernert to keep an

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Speaker 2: eye on that. But just finally looking overseas at really

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Speaker 2: what is the big tech story off the week Telegram

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Speaker 2: founder Pavel d'orov, who's a French national but Russian born,

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Speaker 2: he flew into France on his private jet over the

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Speaker 2: weekend and was promptly arrested, probably quite shocked at that,

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Speaker 2: but he, as we record this, is still in custody

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Speaker 2: in France and they've alleged a whole load of things

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Speaker 2: against him, that he's broken French law when it comes

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Speaker 2: to the sharing or facilitating the spread child exploitation, material, fraud,

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Speaker 2: various sorts of things they're accusing him off. And when

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Speaker 2: I was reading this, I was sort of thinking about

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Speaker 2: Kim dot com, bless him, who is potentially soon on

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Speaker 2: his way finally to the US as part of the

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Speaker 2: extradition going ahead. He'll still probably fight that to the death,

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Speaker 2: but really, Kim, you know, twelve years ago so the

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Speaker 2: government off the US accused him off using a digital

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Speaker 2: platform to facilitate illegal activity. In that case, it was

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Speaker 2: massive copyright infringement, and they alleged that he knew that

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Speaker 2: this was going on, and he knew he was profiting

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Speaker 2: massively from it. So there's lots of parallels to this.

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Speaker 2: Telegram is a messaging service that has nine hundred million

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Speaker 2: users around the world. It has all sorts of stuff

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Speaker 2: going on there that a lot of it is illicit.

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Speaker 2: But to what extent did Pavel d'uov know about this,

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Speaker 2: understand the extent of the fraud, child porn trading, terrorist

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Speaker 2: exchanging messages? And did he actually help facilitate all of

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Speaker 2: this in the interest of making lots of money for

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Speaker 2: himself and the shareholders of Telegram. That's going to be

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Speaker 2: a really interesting one to watch play out.

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Speaker 1: It's such a tough question the extent of like, to

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Speaker 1: what extent the platform owner is responsible for stuff happening

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Speaker 1: on the platform, and you know, is that kind of

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Speaker 1: best effort enough? You know, where we know that YouTube,

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Speaker 1: for example, has been radicalizing people, you know, to cause violence,

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Speaker 1: and so is YouTube directly responsible? Well, they say they're

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Speaker 1: trying really hard to take down a lot of these

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Speaker 1: offending things, and Facebook has potential links to genocide, you know,

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Speaker 1: And so yeah, it becomes a difficult thing of how

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Speaker 1: do we as a global community walk that line between

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Speaker 1: a platform that is just enabling us to do things

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Speaker 1: and we're going to do good things that we're going

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Speaker 1: to do bad things, to negligence that is leading to harms.

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Speaker 1: As the provider of one of these platforms, I don't

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Speaker 1: have any answers to that. I just think it's an

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Speaker 1: interesting question.

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Speaker 2: Yeah, and I think it will very much like in

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Speaker 2: the case of Kim dot Com, it literally came down

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Speaker 2: to when they seized messages mainly from his colleagues talking

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Speaker 2: about knowing what was actually going on on the platform

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Speaker 2: and discussing what Kim actually knew about it, and that

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Speaker 2: formed a big part of the case against Kim dot

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Speaker 2: Com and his co defendants. It sounds as though reading

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Speaker 2: the charges here that there was allegations of a lack

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Speaker 2: of cooperation with authorities in France. So Telegram is not

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Speaker 2: a full end to end encrypted service, unlike WhatsApp and

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Speaker 2: Signal rival messaging platforms. So in theory, a law enforcement

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Speaker 2: agency could subpoena Telegram to Divol's messages that are passed

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Speaker 2: across that platform, and if they refuse to do so,

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Speaker 2: they'll be in trouble with French law US authorities. So

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Speaker 2: that will come into it as well. But you also

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Speaker 2: have the fact that Pavel's been out there basically this

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Speaker 2: year saying, well, we're about to list and this is

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Speaker 2: a really profitable business. He's been talking it up. He said, Oh,

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Speaker 2: it only costs seventy cents a month to maintain a

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Speaker 2: customer on telegram. We only have fifty staff, so we're

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Speaker 2: hugely profitable. You can see that sort of boasting echoes

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Speaker 2: of that from the Kim dot com time as well.

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Speaker 2: But it's also a highly political story as well. He

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Speaker 2: is a Russian national born in Russia, allegedly close to

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Speaker 2: Putin as well. You've got the Ukraine War going on,

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Speaker 2: so to what extent has has been politicized as well

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Speaker 2: that Manuel mccran is making a statement here about a

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Speaker 2: Russian who's too close to at the moment their biggest

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Speaker 2: foe in Europe.

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Speaker 1: Well he says it's not political, or doesn't he? So ye,

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Speaker 1: that says statement, And yeah, I guess it goes back

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Speaker 1: to that question of like, if the French authorities are

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Speaker 1: coming and saying we know that Russia is using telegram

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Speaker 1: to commit war crimes, we want you to give us

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Speaker 1: the details of those messages. And he turns around and says, no,

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Speaker 1: I'm not going to do that, Like, where is that responsibility?

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Speaker 2: Yeah, and this could have implications for other messaging platforms.

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Speaker 2: That's why most of them are doing end to end encryption,

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Speaker 2: you know. The Zuckerberg his whole goal has been let's

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Speaker 2: see this go dark, both for us and for the authorities,

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Speaker 2: so we can legitimately say we don't know what is

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Speaker 2: going on on this network. And it opens up a

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Speaker 2: can of worms in terms of morally what you're facilitating

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Speaker 2: on your network, but it also genuinely allows you to

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Speaker 2: say we don't know, and that is a defense. We've

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Speaker 2: got safe Harbord provisions in the US that allow people

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Speaker 2: to operate and not be prosecuted for facilitating things on

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Speaker 2: their platform as long as they obey the instructions of

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Speaker 2: law enforcement agencies and cooperate when asked to, which you

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Speaker 2: can't do when you're full fully into end encrypted. And

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Speaker 2: there's been efforts to try and break that encryption, which

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Speaker 2: thankfully have been resisted largely to date. But a lot

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Speaker 2: of people around the world who are running messaging apps

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Speaker 2: will be looking at this a little bit nervous, thinking,

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Speaker 2: when am I going to get caught up in this

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Speaker 2: as well. Yeah.

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Speaker 1: Yeah, it's going to be a tough business to be

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Speaker 1: and I think, I mean, it's been a truism for

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Speaker 1: a really long time that online communication is not secure.

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Speaker 1: Like that's if you want to do something Dodgy, fly

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Speaker 1: over to and meet them and have a chat in person.

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Speaker 2: I think that's the analogue.

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Speaker 1: Yeah, I guess that does have other implications for you know,

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Speaker 1: people who are resisting fascist regimes and stuff like that,

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Speaker 1: and they may want to be able to keep in touch.

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Speaker 1: So it's just a big moral morass that we're not

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Speaker 1: going to solve. But yeah, like you say, it will

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Speaker 1: be really interesting to see how it plays out for

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Speaker 1: the Telegram CEO.

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Speaker 2: Yeah, okay. Moving on to our featured guests this week,

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Speaker 2: Hamish Rumbold is our guest on the business of tech.

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Speaker 2: The seasoned IT industry veteran took home the CIO of

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Speaker 2: the Year Award last week. That's run by CIO and

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Speaker 2: CIO Magazine. It's a long running, highly prized accolade for

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Speaker 2: people responsible for running all things tech and digital related

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Speaker 2: in our big companies. It capped off five years at

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Speaker 2: Kiwi Bank, with Rumbold leaving the Bank in June. He's

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Speaker 2: now looking at governance positions and other things which he'll

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Speaker 2: talk about in the interview.

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Speaker 1: Yep. And it's really interesting to hear that he has

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Speaker 1: set a big personal goal for his career. He wants

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Speaker 1: to add ten billion dollars in value to the companies

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Speaker 1: he works for.

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Speaker 2: Yeah, that's I haven't heard anyone put it in those

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Speaker 2: sorts of terms before, but that's pretty cool. And he

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Speaker 2: as he'll explain, he's sort of got partway there in

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Speaker 2: some of the companies that he's worked for, particularly a

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Speaker 2: Kiwi Bank. But the CIO role has really evolved over

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Speaker 2: the last decade as companies have moved to the cloud,

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Speaker 2: cybersecurity has become much more important the whole customer experience.

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Speaker 2: MANTRA is now very much tied into this role as well,

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Speaker 2: so it's more complex than ever. We've seen a lot

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Speaker 2: of projects go off the rails and CIOs have to

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Speaker 2: fall on their sword as a result of that, so

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Speaker 2: a lot of responsibility. It spans the entire business, often

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Speaker 2: hundreds of millions of dollars off investment. So that's why

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Speaker 2: I think we like to keep a close eye on

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Speaker 2: the movers and shakers in the space, and particularly the

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Speaker 2: ones who are being rewarded as as the best at

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Speaker 2: what they do.

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Speaker 1: It's always great to hear what's going on inside the

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Speaker 1: head of these people who are created the digital playing

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Speaker 1: field for these massive companies. So here's your interview Peter

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Speaker 1: with Hamish Rumbold CEO of the Year.

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Speaker 2: Hamish, thanks so much for coming on the Business of Tech.

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Speaker 2: How are you doing?

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Speaker 3: Very good, Peter, thank you. Happy Friday.

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Speaker 2: Yeah, and pretty exciting news. Last week was announced that

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Speaker 2: you were CIO off the Year. This was at the

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Speaker 2: CIO Awards, which is really the big shinderg celebrating chief

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Speaker 2: information officers from around the country, although increasingly they're not

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Speaker 2: really called CIOs anymore, right, I mean you won in

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Speaker 2: your capacity as chief Digital and Technology Officer at Kiwibank.

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Speaker 2: The actual CIO title seems to be sort of morphing

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Speaker 2: into that sort of digital and tech sort of role.

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Speaker 3: I think it is. You know, there's a joke in

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Speaker 3: the industry where CEO stands for career is over. But

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Speaker 3: you know that's not the reason why the lessons are changing.

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Speaker 3: I think it's because, you know, really it's about how

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Speaker 3: do you leverage tech to improve the customer and commercial

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Speaker 3: experience and outcomes, so less about just being a department

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Speaker 3: but actually been an integral part of the organization and

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Speaker 3: achieving the outcomes.

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Speaker 2: So that must have been pretty cool being there. You

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Speaker 2: left Kiwibank in July. That was a big stint you

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Speaker 2: did five years in that role, huge change going on

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Speaker 2: at the bank and in the industry. But yeah, what

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Speaker 2: was it like sort of accepting that among your peers

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Speaker 2: you beat out competition from the likes of Tamaki Health

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Speaker 2: food Stuff, South Island Mercury, some big names there.

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Speaker 3: Yeah, and look, I just want to acknowledge those other

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Speaker 3: finalis because I'm humbled to be on the same list

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Speaker 3: as them, and although I didn't get to see their work,

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Speaker 3: I know they're all fantastic leaders. So yeah, it just

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Speaker 3: to be recognized on that same list as an honor

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Speaker 3: in itself. For me, it's a that I accept on

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Speaker 3: behalf of many and you know, it's a lot of

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Speaker 3: marh that are five hundred of my tech team have

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Speaker 3: been doing over the last five years that have helped

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Speaker 3: us win this and and also you know, the executive

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Speaker 3: and Steve CEO, you know, full support for what we

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Speaker 3: had to had to achieve. So yeah, it's a team award,

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Speaker 3: but I'm very grateful to accept it and it's a

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Speaker 3: great way for me to to wrap up my time

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Speaker 3: at QUB Bank after you know, five five very long

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Speaker 3: and hard years.

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Speaker 2: Yeah.

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Speaker 3: My kids were also very pleased about it as well,

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Speaker 3: because you know, three years running, I missed my daughter's

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Speaker 3: birthday because of certain cyber events, so was she was

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Speaker 3: She was glad to see the some acknowledgment for that.

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Speaker 2: Yeah, and I mean QUI Bank has always had a

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Speaker 2: reputation for being quite innovative, particularly like you know, for instance, Hatch,

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Speaker 2: the shared trading platform, came out of QI Bank has

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Speaker 2: been since been sold to an international company.

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Speaker 1: There.

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Speaker 2: The people from Chers's some of them came out of bank,

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Speaker 2: and you know that's now a powerhouse sort of startup

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Speaker 2: for New Zealand. So it's always had that willingness to

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Speaker 2: try new things. And you know what you were awarded

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Speaker 2: here is another example of that. You teamed up with

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Speaker 2: atomic Io, which is rod Drory's new startup for in

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Speaker 2: app messaging. So you implemented personalized in app messaging for

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Speaker 2: simpler and better customer and team experiences. Tell us about that,

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Speaker 2: because that's really what the judges, I think we're really

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Speaker 2: excited about as part of you winning this award.

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Speaker 3: Yeah, look, I think they were. It was an example

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Speaker 3: of the many features that we that we brought to market.

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Speaker 3: And you know, the actual award was awarded for a

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Speaker 3: leader that demonstrated that they aligned and delivered their technical

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Speaker 3: and digital strategy to to maximize the impact for the organization.

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Speaker 3: So you know, we achieved that in four ways. The

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Speaker 3: first way was to be customer's first choice by being simple,

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Speaker 3: really easy, expert and accessible. And you know, today and

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Speaker 3: q weibank seventy percent of customers actively digital users once

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Speaker 3: a day, interacting with the qbank app more than forty

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Speaker 3: two times a month, and with a customer satisfaction score

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Speaker 3: of over eighty percent. And we've also, you know, we've

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Speaker 3: been to make that customer experience really simple. We've launched

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Speaker 3: new features such as atomic and App Messaging, which is

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Speaker 3: a really clever piece of New Zealand technology that allows

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Speaker 3: you to embed that that personalized messaging into your app

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Speaker 3: really seamlessly. But we've also launched block and unblocked debit card,

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Speaker 3: digital home loan refix. You know, people want to be

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Speaker 3: able to do that on very quickly and self service

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Speaker 3: lump sum repayment on variable loans was a really important

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Speaker 3: feature for people. And of course, you know thinks something

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Speaker 3: that five years ago Qubank was never able to do,

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Speaker 3: which was Apple and Google Pay, which was really a

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Speaker 3: really important milestone.

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Speaker 2: Yeah, it's very happy to see that. You know, that

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Speaker 2: announcement was only a matter of a couple months ago

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Speaker 2: something like that about Google and that pay. So that's great,

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Speaker 2: And you know, there is a lot of change to

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Speaker 2: come in the banking sector. We had last week the

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Speaker 2: Commerce Commission, its recommendations came out around stimulating competition in

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Speaker 2: the banking sector, big focus on open banking there. What's

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Speaker 2: your perspective on what that will really unlock for consumers?

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Speaker 3: Yeah, and look, I just want to really caveate this.

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Speaker 3: This is my own personal views. Obviously I've now left Quybank.

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Speaker 3: These don't represent Qbank's perspectives. But I think since the start, actually,

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Speaker 3: you know, I think there was a piece of research

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Speaker 3: done with consumers about whether they wanted open banking, and

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Speaker 3: a vast majority of them said they don't. And I

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Speaker 3: think there's a there's sort of a perception problem with

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Speaker 3: open banking, which is no one wants their banking to

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Speaker 3: be open, you know, they want it to be safe, secure,

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Speaker 3: and so possibly wrong name, wrong branding and wrong. You know,

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Speaker 3: what are they trying to achieve? And so for me personally,

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Speaker 3: there's not a lot of evidence around the world of

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Speaker 3: open banking or these o pr API has been exposed.

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Speaker 3: It is actually achieving a lot. And the reason for

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Speaker 3: that is is if you if you only have one

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Speaker 3: or two API is exposed, you can't really do a lot.

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Speaker 3: If you're a fintech or with that, it actually you

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Speaker 3: need a suite of APIs and and and a and

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Speaker 3: a big ecosystem at play to be able to for

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Speaker 3: value to be able to be created and actually deliver

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Speaker 3: value for the for the customer and for the for

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Speaker 3: the country. So I think for me, it's it's more

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Speaker 3: important to go back what problem are we trying to solve?

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Speaker 3: You know, if we are trying to make it more

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Speaker 3: simple for customers to get products and for banks to

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Speaker 3: make better decisions for their customers, so good customer outcomes,

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Speaker 3: then actually, you know, that might actually be companies like

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Speaker 3: the I r D providing you know, information back to banks.

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Speaker 3: It might be banks providing information out to other people

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Speaker 3: it might be zero opening up their APIs. You know,

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Speaker 3: it's not necessarily about always banks out. It could be

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Speaker 3: banks in as well. And and so I think it

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Speaker 3: comes back to the problem you're trying to solve, but switching.

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Speaker 3: You know, if you think about number portability with mobile

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Speaker 3: operators years ago now for actually switching banks today is

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Speaker 3: relatively easy, and there's a misperception of how hard it is.

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Speaker 3: That there are regulatory and compliance steps you just can't

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Speaker 3: be avoided, and there are things like account numbers that

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Speaker 3: will always need changing. So you know, again, if that's

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Speaker 3: the problem you're trying to solve, what's the inertia and

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Speaker 3: what's the what's the solution that you can actually tap

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Speaker 3: into to solve for that? So you know, if it's

436
00:24:37,760 --> 00:24:41,040
Speaker 3: new entrants entering the market and increasing competition, well there's

437
00:24:41,040 --> 00:24:44,840
Speaker 3: actually other bigger problems like the overhead of compliance and

438
00:24:44,880 --> 00:24:47,880
Speaker 3: regulatory and the platform and the you know in all

439
00:24:47,920 --> 00:24:50,879
Speaker 3: of that to run. So I just think actually open

440
00:24:50,920 --> 00:24:54,920
Speaker 3: banking is not a solver bullet. I think it's a

441
00:24:54,960 --> 00:24:59,560
Speaker 3: it's an important step towards a more open ecosystem, but

442
00:25:00,880 --> 00:25:03,720
Speaker 3: I'd love to see a much more sort of strategic

443
00:25:04,480 --> 00:25:07,080
Speaker 3: roadmap on what problems we're trying to solve for consumers.

444
00:25:07,280 --> 00:25:09,760
Speaker 2: Yeah. Look, I wrote about this in my Business Desk

445
00:25:09,800 --> 00:25:13,440
Speaker 2: column last week where I was looking around the world

446
00:25:13,520 --> 00:25:16,760
Speaker 2: and particularly the countries that were quite similar to culturally,

447
00:25:16,840 --> 00:25:20,960
Speaker 2: like Australia and the United Kingdom, much further down the

448
00:25:21,080 --> 00:25:23,800
Speaker 2: track on open banking than US, and it hasn't really

449
00:25:23,840 --> 00:25:27,560
Speaker 2: been a roaring success. But you really have to go

450
00:25:27,600 --> 00:25:32,040
Speaker 2: to countries like India and Brazil to see some actual

451
00:25:32,760 --> 00:25:35,320
Speaker 2: serious take up here. And in Brazil's case, I had

452
00:25:35,320 --> 00:25:37,480
Speaker 2: a look at that. They're sort of lauded as the benchmark.

453
00:25:37,520 --> 00:25:40,560
Speaker 2: They did this very quickly, but what they did was

454
00:25:40,560 --> 00:25:43,000
Speaker 2: at the same time they launched the service called Picks,

455
00:25:43,640 --> 00:25:46,199
Speaker 2: which is a instant payment service. It's a little bit

456
00:25:46,240 --> 00:25:49,520
Speaker 2: like we chat in China. You have a QR code,

457
00:25:49,560 --> 00:25:51,600
Speaker 2: you go into a restaurant or something, you just scan

458
00:25:51,680 --> 00:25:54,919
Speaker 2: the QR code instant payment for a fraction of what

459
00:25:55,600 --> 00:25:58,199
Speaker 2: a credit card or debit card would cost you. So

460
00:25:58,720 --> 00:26:00,800
Speaker 2: that was actually the killer. But then you had all

461
00:26:00,800 --> 00:26:05,040
Speaker 2: these FinTechs in Brazil utilizing that platform and you and

462
00:26:05,160 --> 00:26:08,480
Speaker 2: calling on APIs. So there's billions of calls on APIs

463
00:26:08,560 --> 00:26:12,680
Speaker 2: every every month in Brazil. As a result of that,

464
00:26:13,240 --> 00:26:15,920
Speaker 2: I'm not really seeing the same thing in New Zealand

465
00:26:15,960 --> 00:26:17,760
Speaker 2: that is going to build that momentum, at least in

466
00:26:17,800 --> 00:26:20,560
Speaker 2: the short term. It's great to see all these companies

467
00:26:20,600 --> 00:26:25,080
Speaker 2: like Dash and not doing innovative things, but overcoming that inertia.

468
00:26:25,160 --> 00:26:28,280
Speaker 2: People stay with the bank because they've fostered that relationship.

469
00:26:28,840 --> 00:26:30,960
Speaker 3: Yeah, I agree. And look, I went to China last

470
00:26:31,040 --> 00:26:35,640
Speaker 3: year and you know, their physical infrastructure in the last

471
00:26:35,640 --> 00:26:38,280
Speaker 3: twenty years as a country is you know, second to

472
00:26:38,320 --> 00:26:41,600
Speaker 3: none and leap progging. But as well, they're digital infrastructure

473
00:26:41,720 --> 00:26:44,399
Speaker 3: and actually the government's leading the way and it's not

474
00:26:44,920 --> 00:26:48,000
Speaker 3: a cowboy territory where you know, data's was flowing around

475
00:26:48,040 --> 00:26:53,399
Speaker 3: and unsecured and are unpermissioned. But they've all you know,

476
00:26:53,680 --> 00:26:56,280
Speaker 3: the government agencies have opened up their own APIs to

477
00:26:56,320 --> 00:26:59,679
Speaker 3: help organizations make better decisions and make it simpler for consumers.

478
00:27:00,080 --> 00:27:03,240
Speaker 3: To your point around the QR codes. You know that

479
00:27:03,240 --> 00:27:06,280
Speaker 3: that's a really good example of them looking at a

480
00:27:06,280 --> 00:27:08,560
Speaker 3: problem that they wanted to solve, which was to move

481
00:27:08,680 --> 00:27:11,920
Speaker 3: from a cashless you know, to a cashless society quickly

482
00:27:12,400 --> 00:27:14,680
Speaker 3: and to roll out the infrastructure that the West has,

483
00:27:14,760 --> 00:27:18,119
Speaker 3: you know, FBOs, machines and the networks, et cetera just

484
00:27:18,160 --> 00:27:21,520
Speaker 3: wouldn't work in China. So they turned to QR codes,

485
00:27:21,560 --> 00:27:24,000
Speaker 3: which is a very cheap and cost effective and fast

486
00:27:24,000 --> 00:27:26,919
Speaker 3: way to scale out to you know, very small merchants,

487
00:27:27,040 --> 00:27:30,040
Speaker 3: very very rapidly, and they've and they've gained cashless society

488
00:27:30,119 --> 00:27:33,119
Speaker 3: very very quickly. So again it goes back to for me,

489
00:27:33,160 --> 00:27:35,000
Speaker 3: it goes back to the problem we're trying to solve,

490
00:27:35,119 --> 00:27:38,000
Speaker 3: and if if we're trying to increase competition, I personally

491
00:27:38,000 --> 00:27:40,120
Speaker 3: think the best thing the government could do is support

492
00:27:40,240 --> 00:27:43,840
Speaker 3: a common platform for one, a bitible word banking platform

493
00:27:43,920 --> 00:27:48,520
Speaker 3: that you know, manage most of the underlying operational needs

494
00:27:48,520 --> 00:27:52,000
Speaker 3: of a bank, where any other when any any other

495
00:27:52,119 --> 00:27:55,239
Speaker 3: organization can consider on top of it and launch their

496
00:27:55,240 --> 00:27:59,040
Speaker 3: own brands and products to market relatively quickly with without

497
00:27:59,040 --> 00:28:01,800
Speaker 3: that overhead, you know, that be that would be a

498
00:28:01,800 --> 00:28:04,280
Speaker 3: good solution to support more competition.

499
00:28:04,640 --> 00:28:09,760
Speaker 2: Huh, that's interesting. So you basically all the infrastructure would

500
00:28:09,800 --> 00:28:13,320
Speaker 2: be on a common platform that's invested in maybe by

501
00:28:13,359 --> 00:28:16,320
Speaker 2: a group of companies, and then you run your services

502
00:28:16,320 --> 00:28:18,159
Speaker 2: over the top of that. Is that because for a

503
00:28:18,160 --> 00:28:21,720
Speaker 2: small country literally having five big banks trying to maintain

504
00:28:21,800 --> 00:28:24,639
Speaker 2: all of their own infrastructure is just such an expensive

505
00:28:25,240 --> 00:28:26,239
Speaker 2: and time consuming thing.

506
00:28:26,359 --> 00:28:29,119
Speaker 3: Well, I think I think it's it's probably for the

507
00:28:29,119 --> 00:28:30,919
Speaker 3: five big banks, it's O k Q, we bank it.

508
00:28:31,000 --> 00:28:33,639
Speaker 3: You know, it has all the same costs as an

509
00:28:33,680 --> 00:28:37,640
Speaker 3: A and Z and needs to do it smarter. But

510
00:28:37,760 --> 00:28:41,640
Speaker 3: the a bit new and new and emerging players that's

511
00:28:41,680 --> 00:28:45,160
Speaker 3: a big cost hurdle to get over to get into market.

512
00:28:45,280 --> 00:28:46,360
Speaker 3: So how do you make that easier?

513
00:28:53,200 --> 00:28:55,280
Speaker 2: Traditionally the bank's been very locked down for a very

514
00:28:55,280 --> 00:28:57,680
Speaker 2: good reason, and that's why we don't see big data

515
00:28:57,960 --> 00:29:02,000
Speaker 2: breaches typically in the banks, because they are so locked down.

516
00:29:02,280 --> 00:29:05,640
Speaker 2: When you're working with all these third parties, it's a

517
00:29:05,640 --> 00:29:08,280
Speaker 2: lot of trust, isn't it in small companies that don't

518
00:29:08,280 --> 00:29:10,480
Speaker 2: have much of a track record that are suddenly taking

519
00:29:10,520 --> 00:29:14,000
Speaker 2: a lot of data and sending data between banks.

520
00:29:14,160 --> 00:29:18,200
Speaker 3: Yeah, I think Simon, I think there's good security standards

521
00:29:18,240 --> 00:29:22,720
Speaker 3: for those that communication between and obviously that's where it's

522
00:29:22,800 --> 00:29:24,920
Speaker 3: very costly for the banks to implement. You know, they

523
00:29:24,920 --> 00:29:27,360
Speaker 3: need to be able to control who's getting access to

524
00:29:27,400 --> 00:29:31,640
Speaker 3: what data, they need to be able to revoke that access,

525
00:29:31,640 --> 00:29:33,000
Speaker 3: they need to be able to pull the data back,

526
00:29:33,040 --> 00:29:35,680
Speaker 3: you know, there's a lot of complexity in actually setting

527
00:29:35,760 --> 00:29:40,040
Speaker 3: up open banking. So I think the more data moves around,

528
00:29:40,200 --> 00:29:43,840
Speaker 3: the more suppliers or parties that are in the chain, Yes,

529
00:29:43,960 --> 00:29:48,040
Speaker 3: you do open yourself up for more risk, but there

530
00:29:48,040 --> 00:29:49,720
Speaker 3: are ways of managing that.

531
00:29:50,520 --> 00:29:52,280
Speaker 2: And yeah, it looks like that. You know, they're working

532
00:29:52,320 --> 00:29:55,520
Speaker 2: through all the details of that now, so they're applying

533
00:29:55,560 --> 00:30:00,440
Speaker 2: best practice to that. So Hamish, speaking off CyberSecure, you

534
00:30:00,560 --> 00:30:06,080
Speaker 2: spent about eleven months on the Ministerial Cybersecurity Advisory Committee

535
00:30:06,720 --> 00:30:10,000
Speaker 2: back in twenty twenty one, I think twenty twenty two,

536
00:30:10,240 --> 00:30:12,760
Speaker 2: so that's been disestablished now, but that spent an intense

537
00:30:12,800 --> 00:30:16,760
Speaker 2: period of time looking at our cybersecurity preparedness. What were

538
00:30:16,800 --> 00:30:19,600
Speaker 2: the impressions you got about the journey we were on

539
00:30:19,680 --> 00:30:24,400
Speaker 2: at that point around cybersecurity protecting our critical infrastructure and

540
00:30:24,440 --> 00:30:27,560
Speaker 2: getting that message out to small and medium sized companies

541
00:30:27,600 --> 00:30:30,760
Speaker 2: in particular that we need to invest more in our

542
00:30:30,800 --> 00:30:32,040
Speaker 2: preparedness in this space.

543
00:30:32,320 --> 00:30:35,280
Speaker 3: The purpose of it was how do we improve public

544
00:30:35,440 --> 00:30:40,760
Speaker 3: and private collaboration to improve the capability of New Zealand.

545
00:30:40,880 --> 00:30:45,720
Speaker 3: What we found was it's relatively disjointed ecosystem. You know,

546
00:30:45,800 --> 00:30:48,920
Speaker 3: as a small country, we've actually possibly you've probably got

547
00:30:48,960 --> 00:30:52,600
Speaker 3: quite a competitive advantage to be able to work collaboratively together.

548
00:30:52,840 --> 00:30:55,400
Speaker 3: You know, there was actually a really big opportunity for

549
00:30:55,520 --> 00:30:59,640
Speaker 3: us to come back cyber collectively. The second thing was

550
00:30:59,680 --> 00:31:02,840
Speaker 3: five You know, being part of five Eyes is a

551
00:31:02,880 --> 00:31:07,360
Speaker 3: significant advantage for us, and are we keeping pace with

552
00:31:07,600 --> 00:31:10,840
Speaker 3: the other five eye partners in our investment are our

553
00:31:10,960 --> 00:31:17,120
Speaker 3: and our capability and our digital infrastructure and cyber readiness.

554
00:31:17,160 --> 00:31:19,560
Speaker 3: So you know, that was a challenge we put back

555
00:31:19,600 --> 00:31:22,280
Speaker 3: to the to the government at the time. Like everything,

556
00:31:22,440 --> 00:31:26,000
Speaker 3: there's layers of onions in cyber defense. For small and

557
00:31:26,040 --> 00:31:29,720
Speaker 3: medium sized organizations, that's a really it's a really big challenge.

558
00:31:29,920 --> 00:31:33,320
Speaker 3: They just can't invest in the same tools that large

559
00:31:33,400 --> 00:31:37,040
Speaker 3: organizations can. Look, I think it's an ongoing battle that

560
00:31:37,080 --> 00:31:40,120
Speaker 3: will continue, but I think we've got a geographic and

561
00:31:40,480 --> 00:31:45,640
Speaker 3: island nation defense opportunity if we collaborate well together.

562
00:31:46,320 --> 00:31:49,440
Speaker 2: Yeah, So it's a it's a big issue that CIOs

563
00:31:49,840 --> 00:31:52,800
Speaker 2: are grappling with, clearly, but it's just one of many.

564
00:31:52,880 --> 00:31:56,160
Speaker 2: I mean, there's a lot of complex issues that CIOs

565
00:31:56,200 --> 00:31:59,840
Speaker 2: and IT departments are dealing with. We'll talk about AI

566
00:31:59,880 --> 00:32:02,280
Speaker 2: and BIT more in detail, but before you even do that,

567
00:32:02,320 --> 00:32:04,600
Speaker 2: getting your data house in order. That seems to be

568
00:32:05,360 --> 00:32:08,240
Speaker 2: a big priority for a lot of New Zealand organizations

569
00:32:08,320 --> 00:32:11,920
Speaker 2: actually getting the data in a clean format in the

570
00:32:12,000 --> 00:32:15,880
Speaker 2: right place so that you can actually draw on applications

571
00:32:15,920 --> 00:32:16,360
Speaker 2: like AI.

572
00:32:16,720 --> 00:32:20,400
Speaker 3: Yeah, one hundred percent. And you know, but like the

573
00:32:20,400 --> 00:32:24,000
Speaker 3: physical infrastructure deficit that most countries are carrying, there is

574
00:32:24,040 --> 00:32:28,840
Speaker 3: a digital infrastructure deficit and in legacy applications, and really

575
00:32:28,840 --> 00:32:31,800
Speaker 3: the biggest problem there is how those applications are integrated

576
00:32:31,840 --> 00:32:34,400
Speaker 3: and how tightly coupled they are, and how to get

577
00:32:34,440 --> 00:32:38,280
Speaker 3: yourself out of that is actually really complex. So it's

578
00:32:38,320 --> 00:32:40,920
Speaker 3: not just the legacy, it's how it all hangs together.

579
00:32:41,080 --> 00:32:42,760
Speaker 3: That's one of the big challenges for a lot of

580
00:32:42,800 --> 00:32:47,040
Speaker 3: CIOs to move through that. And frankly, you know some

581
00:32:47,080 --> 00:32:52,120
Speaker 3: of the operating models that we've had in the past

582
00:32:52,160 --> 00:32:56,600
Speaker 3: where you project oriented funding models where you sort of

583
00:32:56,640 --> 00:32:58,400
Speaker 3: work on one thing and then you leave it and

584
00:32:58,440 --> 00:33:01,000
Speaker 3: move on to another thing atually. If if it had

585
00:33:01,080 --> 00:33:04,640
Speaker 3: had more persistent teams that looked after and stewarded technology

586
00:33:04,680 --> 00:33:08,920
Speaker 3: for for for for the long term, we would have

587
00:33:08,920 --> 00:33:11,960
Speaker 3: avoided a lot of these problems. I think of tech

588
00:33:12,000 --> 00:33:15,640
Speaker 3: getting into the legacy status, but data to your point,

589
00:33:16,080 --> 00:33:19,480
Speaker 3: Peter is is, you know, a big challenge. It's often

590
00:33:19,520 --> 00:33:22,640
Speaker 3: locked away in these legacy systems, not governed well, not

591
00:33:22,720 --> 00:33:27,080
Speaker 3: granular enough, not fast moving enough. So there's a lot

592
00:33:27,120 --> 00:33:30,360
Speaker 3: of work to get that domain and service orientated architecture

593
00:33:30,360 --> 00:33:34,440
Speaker 3: where data is moving around freely to be to be used,

594
00:33:34,440 --> 00:33:37,840
Speaker 3: but well governed and ready for for AI. You know,

595
00:33:38,240 --> 00:33:40,160
Speaker 3: there's a lot of complexity around if you're going to

596
00:33:40,160 --> 00:33:44,400
Speaker 3: start using data for AI, you need to have good

597
00:33:44,960 --> 00:33:49,680
Speaker 3: data classification, You need to have good user access management

598
00:33:49,720 --> 00:33:52,720
Speaker 3: controls on who can access what data. If you suddenly

599
00:33:52,760 --> 00:33:56,200
Speaker 3: just put an AI over your entire shap point sweep,

600
00:33:56,240 --> 00:33:59,480
Speaker 3: for example, then you know you could be exposing a

601
00:33:59,480 --> 00:34:02,880
Speaker 3: lot of that you don't want to expose to certain individuals.

602
00:34:03,160 --> 00:34:05,840
Speaker 2: Yeah, I guess yeah.

603
00:34:05,600 --> 00:34:05,640
Speaker 1: You.

604
00:34:06,160 --> 00:34:09,839
Speaker 2: Generative AI really came onto the scene with chat GPT's

605
00:34:09,920 --> 00:34:13,920
Speaker 2: debut in late twenty twenty two. What's been your experience

606
00:34:13,960 --> 00:34:16,800
Speaker 2: over the last few years sort of you know, probably

607
00:34:16,840 --> 00:34:19,600
Speaker 2: experimenting like everyone in New Zealand is, with this technology,

608
00:34:19,680 --> 00:34:23,000
Speaker 2: trying to figure out how we can apply this to

609
00:34:23,760 --> 00:34:27,919
Speaker 2: a KII bank customers, you know, experience and also within

610
00:34:28,000 --> 00:34:31,080
Speaker 2: your own team and your own organization to make their

611
00:34:31,280 --> 00:34:35,160
Speaker 2: jobs easier and allow them to be more productive. Are

612
00:34:35,160 --> 00:34:40,400
Speaker 2: you a believer in gen AI and the potential it

613
00:34:40,440 --> 00:34:43,440
Speaker 2: has to maybe tackle our productivity problem in New Zealand.

614
00:34:43,520 --> 00:34:46,080
Speaker 3: It's a game changer and it will happen over time.

615
00:34:46,239 --> 00:34:48,799
Speaker 3: You know, it's going to fundamentally change everything we do

616
00:34:48,840 --> 00:34:51,360
Speaker 3: and how we do it. You know, example, copyrights and

617
00:34:51,440 --> 00:34:55,719
Speaker 3: IP you know, prediction accuracy. These ais now are predicting

618
00:34:56,760 --> 00:34:58,600
Speaker 3: weather far better than we've ever been out with the

619
00:34:58,640 --> 00:35:00,400
Speaker 3: pattern salad than that we've been out to do. So

620
00:35:00,440 --> 00:35:03,200
Speaker 3: you know what's next, Stop markets, et cetera, et cetera.

621
00:35:03,280 --> 00:35:05,680
Speaker 3: If you could think about the things in your business

622
00:35:05,719 --> 00:35:08,360
Speaker 3: that you would want to predict, and then you could

623
00:35:08,440 --> 00:35:11,600
Speaker 3: predict with really good accuracy, how would that change your

624
00:35:11,600 --> 00:35:15,400
Speaker 3: business model? And how would that change what competition environment

625
00:35:15,440 --> 00:35:18,240
Speaker 3: you sit in? So there's some really big GNALI challenges

626
00:35:18,280 --> 00:35:20,560
Speaker 3: coming ahead for a lot of industries and a lot

627
00:35:20,600 --> 00:35:25,000
Speaker 3: of and a lot of parts of organization. So, you know, look,

628
00:35:25,040 --> 00:35:27,960
Speaker 3: AI has been around for ages, and you know, nineteen

629
00:35:28,040 --> 00:35:34,520
Speaker 3: nineties machine learning algorithms became more more widely used and

630
00:35:34,680 --> 00:35:40,120
Speaker 3: more recently generative AI. I think what we're starting to

631
00:35:40,160 --> 00:35:42,160
Speaker 3: see is globally is a bit of a passion to

632
00:35:42,200 --> 00:35:44,040
Speaker 3: move what I heard a great saying the other day

633
00:35:44,760 --> 00:35:48,640
Speaker 3: away from god like AI to the realization now that

634
00:35:48,680 --> 00:35:51,840
Speaker 3: we need to focus on building actual products and use cases.

635
00:35:51,880 --> 00:35:54,480
Speaker 3: Because there's a lot of talk about what's possible and

636
00:35:54,600 --> 00:35:56,720
Speaker 3: what will be put, what will come, and I completely

637
00:35:56,760 --> 00:36:00,279
Speaker 3: believe a lot of it, but people on the on

638
00:36:00,320 --> 00:36:02,200
Speaker 3: the hype curve, people are starting to get into that

639
00:36:02,239 --> 00:36:04,640
Speaker 3: point where it's actually, what are the rare use cases

640
00:36:04,640 --> 00:36:07,200
Speaker 3: that we can extract value out of this? And I

641
00:36:07,200 --> 00:36:11,160
Speaker 3: think when AI becomes a product, and many of us

642
00:36:11,160 --> 00:36:14,120
Speaker 3: are using AI today, such as for fraud and you know,

643
00:36:15,400 --> 00:36:19,880
Speaker 3: decisioning and whatever it might be, personalization for customers, we

644
00:36:19,920 --> 00:36:21,920
Speaker 3: don't call it AI. We just call it a product.

645
00:36:21,960 --> 00:36:24,200
Speaker 3: You know, it's a thing that we do. It's it's

646
00:36:24,400 --> 00:36:27,000
Speaker 3: it's something that makes solves the problem, will make something

647
00:36:27,000 --> 00:36:29,680
Speaker 3: simple or better. So I think the best way to

648
00:36:29,719 --> 00:36:32,200
Speaker 3: look at AI is it's just another it's another tool,

649
00:36:32,760 --> 00:36:38,400
Speaker 3: it's another technology. And again I come back from companies

650
00:36:38,440 --> 00:36:41,960
Speaker 3: needing a really clear strategy identifying the problems that they

651
00:36:42,040 --> 00:36:44,600
Speaker 3: want to solve and looking at the tech that can

652
00:36:44,640 --> 00:36:49,880
Speaker 3: solve it, and that might be AI. And but you

653
00:36:49,920 --> 00:36:53,080
Speaker 3: know what I would say, is don't hold back from

654
00:36:53,400 --> 00:36:56,040
Speaker 3: investing in the right foundations because that takes time to

655
00:36:56,400 --> 00:36:58,480
Speaker 3: build up. You know, to get your data out of

656
00:36:58,520 --> 00:37:02,480
Speaker 3: the legacy systems, to have it at a granular level,

657
00:37:02,560 --> 00:37:05,560
Speaker 3: to have it well categorized, to have good user access

658
00:37:05,560 --> 00:37:09,040
Speaker 3: management over it. All of that takes time and those

659
00:37:09,040 --> 00:37:12,600
Speaker 3: controls are foundational for any AI that you want to

660
00:37:12,640 --> 00:37:13,200
Speaker 3: do in the future.

661
00:37:13,239 --> 00:37:14,880
Speaker 2: Yeah's a lot of work needs to be done on

662
00:37:15,400 --> 00:37:19,880
Speaker 2: government governance, on getting the right guide rails in place.

663
00:37:21,360 --> 00:37:24,640
Speaker 2: It looks as though now you've stepped down as Chief

664
00:37:24,680 --> 00:37:29,320
Speaker 2: Digital and Technology Officer Kiwi Bank, you've been in executive

665
00:37:29,320 --> 00:37:33,200
Speaker 2: non executive sort of roles on boards of companies and

666
00:37:33,640 --> 00:37:36,000
Speaker 2: that is that sort of on the agenda for you

667
00:37:36,640 --> 00:37:40,160
Speaker 2: helping organizations through the IT lens grapple with these sorts

668
00:37:40,160 --> 00:37:42,680
Speaker 2: of issues around deploying AI responsibly.

669
00:37:42,800 --> 00:37:45,319
Speaker 3: It is definitely and you know, my ambitions to be

670
00:37:45,360 --> 00:37:48,400
Speaker 3: involved in and help New Zealand and Australian companies create

671
00:37:48,560 --> 00:37:52,120
Speaker 3: an additional ten billion market CAPIT value over my life

672
00:37:52,200 --> 00:37:56,440
Speaker 3: and you know, using technology to do that, working backwards

673
00:37:56,440 --> 00:37:58,920
Speaker 3: from the customer team experience, so you know, whether that's

674
00:37:58,920 --> 00:38:01,400
Speaker 3: with one company or with more companies on on and

675
00:38:02,120 --> 00:38:04,960
Speaker 3: cross multiple boards or as an executive role.

676
00:38:04,960 --> 00:38:05,360
Speaker 1: It doesn't.

677
00:38:05,840 --> 00:38:08,520
Speaker 3: Yeah, it's that it's the interesting problems that help New

678
00:38:08,560 --> 00:38:10,840
Speaker 3: Zealand and Australia be successful in a global stage that

679
00:38:10,960 --> 00:38:13,120
Speaker 3: really does it for me. And the reason why I

680
00:38:13,120 --> 00:38:18,880
Speaker 3: think that's quite important is that there's a risk, a

681
00:38:19,000 --> 00:38:21,520
Speaker 3: very very risk in New Zealand Australia, particularly in New

682
00:38:21,600 --> 00:38:25,319
Speaker 3: Zealand that we just we just become you know, part

683
00:38:25,360 --> 00:38:30,040
Speaker 3: of the global cogs, you know, the big global organizations

684
00:38:30,040 --> 00:38:34,840
Speaker 3: that are dominating, and you know that the scale and

685
00:38:34,880 --> 00:38:37,440
Speaker 3: the funding that they've got to invest in these technologies

686
00:38:37,520 --> 00:38:40,759
Speaker 3: is humongous. So yeah, I think it's really important that

687
00:38:40,800 --> 00:38:43,560
Speaker 3: we continue to create meaningful jobs in New Zealand with

688
00:38:43,880 --> 00:38:47,440
Speaker 3: really successful New zeal companies and and help use tech

689
00:38:47,520 --> 00:38:51,279
Speaker 3: to solve societal problems and continue to grow.

690
00:38:51,480 --> 00:38:54,279
Speaker 2: That's great. You're also involved in this organization Tech for

691
00:38:54,360 --> 00:38:56,440
Speaker 2: Good New Zealand. What do they do?

692
00:38:57,040 --> 00:39:02,920
Speaker 3: It's part of a wider movement, I guess, and to

693
00:39:02,920 --> 00:39:06,520
Speaker 3: be honest, it's myself and the others have lost a

694
00:39:06,520 --> 00:39:09,040
Speaker 3: bit of focus and that recently, but hopefully with some

695
00:39:09,040 --> 00:39:10,960
Speaker 3: more time I'll be able to get back in to

696
00:39:11,080 --> 00:39:13,480
Speaker 3: supporting it. But really it's about how do we leverage

697
00:39:13,520 --> 00:39:18,080
Speaker 3: technology for good and we organize a bunch of I

698
00:39:18,120 --> 00:39:21,840
Speaker 3: can't take credit for this, Angela and Sam organize a

699
00:39:21,880 --> 00:39:24,799
Speaker 3: lot of meetups where we tried to focus on a

700
00:39:24,840 --> 00:39:31,120
Speaker 3: social problem and we bring people from different capabilities like UXCX,

701
00:39:31,160 --> 00:39:35,319
Speaker 3: design engineers and try and help talk about how we

702
00:39:35,320 --> 00:39:39,279
Speaker 3: could use technology to solve that problem. So some real

703
00:39:39,320 --> 00:39:42,560
Speaker 3: examples was a friend of mine who had a charity

704
00:39:42,600 --> 00:39:47,080
Speaker 3: that was helping kids that are in discol ten schools

705
00:39:47,120 --> 00:39:51,360
Speaker 3: who at Christmas time don't get the same gifts and

706
00:39:51,440 --> 00:39:55,520
Speaker 3: benefits that our kids are privileged to get, and we

707
00:39:55,640 --> 00:39:59,319
Speaker 3: automated and streamlined a system where they can roll that

708
00:39:59,360 --> 00:40:02,560
Speaker 3: out in scale, out to multiple to the whole school.

709
00:40:02,560 --> 00:40:06,240
Speaker 3: Basically where the kids would write a lesson to center

710
00:40:06,320 --> 00:40:09,560
Speaker 3: and we would distribute that out to friends and family

711
00:40:09,800 --> 00:40:11,959
Speaker 3: farm wide and they would actually go on to fill

712
00:40:12,000 --> 00:40:13,719
Speaker 3: that gift for that child.

713
00:40:13,960 --> 00:40:20,040
Speaker 2: Cool. Yeah, So it's not one specific type of service

714
00:40:20,120 --> 00:40:22,719
Speaker 2: that you're sort of supplying goes back to you, you know,

715
00:40:22,719 --> 00:40:25,000
Speaker 2: what is the problem. You're identifying problems in the end,

716
00:40:25,000 --> 00:40:28,480
Speaker 2: going hey, I know people in the tech world who

717
00:40:28,560 --> 00:40:33,000
Speaker 2: can help apply their experience, their expertise, their technology platforms

718
00:40:33,040 --> 00:40:33,839
Speaker 2: to solving this.

719
00:40:33,840 --> 00:40:36,719
Speaker 3: Problem exactly, yeap, and bringing light minded people together to

720
00:40:37,680 --> 00:40:39,480
Speaker 3: hopefully get on and do something about it.

721
00:40:39,520 --> 00:40:41,680
Speaker 2: Well, that's great, So that's what it's going to be

722
00:40:41,719 --> 00:40:44,400
Speaker 2: part of your portfolio. But what's in the immediate future

723
00:40:44,480 --> 00:40:44,719
Speaker 2: for you.

724
00:40:44,920 --> 00:40:48,719
Speaker 3: I'm advising a company called Constantinoble and Australia, which is

725
00:40:48,719 --> 00:40:52,759
Speaker 3: a banking platform and supporting them and the New Zealand

726
00:40:52,760 --> 00:40:57,319
Speaker 3: Australian markets. And then there's a few other things coming

727
00:40:57,320 --> 00:41:00,359
Speaker 3: which I can't mention at the moment, but yeah, I'm

728
00:41:00,719 --> 00:41:03,960
Speaker 3: I'm I'm relatively busy with four or five things under

729
00:41:04,080 --> 00:41:05,520
Speaker 3: underway for the moment.

730
00:41:05,520 --> 00:41:08,520
Speaker 2: Can you see yourself in a sort of CIO role

731
00:41:08,760 --> 00:41:10,440
Speaker 2: like for a big company like Kiwi Bank?

732
00:41:10,480 --> 00:41:13,160
Speaker 3: Again, yeah, one hundred percent. And as I said, it's

733
00:41:13,239 --> 00:41:16,719
Speaker 3: really about that that those really big, interesting problems that

734
00:41:16,840 --> 00:41:20,960
Speaker 3: help New Zealand. So yeah, I'm just keeping an open

735
00:41:21,000 --> 00:41:24,239
Speaker 3: mind on what's next and helping where I can. You know,

736
00:41:24,760 --> 00:41:27,920
Speaker 3: one of the things you realize is I've made a

737
00:41:27,960 --> 00:41:30,959
Speaker 3: lot of mistakes and the best way I can help

738
00:41:31,000 --> 00:41:33,600
Speaker 3: people is to avoid making those same mistakes and speed

739
00:41:33,680 --> 00:41:38,200
Speaker 3: up their decisions. So you know, that's that's that's an

740
00:41:38,280 --> 00:41:41,279
Speaker 3: incredible piece of value I can bring organizations well.

741
00:41:41,320 --> 00:41:45,760
Speaker 2: Once again, congratulations, I'm being CIO off the year, huge

742
00:41:46,280 --> 00:41:49,080
Speaker 2: accolade to pick up. Thanks so much for your time

743
00:41:49,080 --> 00:41:51,000
Speaker 2: and good luck for your future endeavors.

744
00:41:51,120 --> 00:41:52,919
Speaker 3: Thanks very much, Peter, I appreciate the time.

745
00:41:56,239 --> 00:41:59,520
Speaker 2: So there you go, being Hamish Rumbold gone from Kiwi

746
00:41:59,640 --> 00:42:02,400
Speaker 2: Bank looking for his next big gig where he can

747
00:42:02,440 --> 00:42:08,680
Speaker 2: add billions of dollars hopefully to some other business interested

748
00:42:08,719 --> 00:42:11,760
Speaker 2: particularly what you thought of what he said about open banking,

749
00:42:11,880 --> 00:42:14,279
Speaker 2: considering we've discussed this a bit on the podcast in

750
00:42:14,320 --> 00:42:15,200
Speaker 2: the last couple of weeks.

751
00:42:15,480 --> 00:42:17,840
Speaker 1: Yeah, I think I think what he said really reveals

752
00:42:18,560 --> 00:42:21,520
Speaker 1: kind of a problem with the way that open banking

753
00:42:21,560 --> 00:42:24,600
Speaker 1: has been talked about a little bit recently, which is

754
00:42:25,560 --> 00:42:27,680
Speaker 1: what he said was that open banking is not a

755
00:42:27,719 --> 00:42:33,120
Speaker 1: silver bullet, and we know, right like that's nobody has

756
00:42:33,120 --> 00:42:35,279
Speaker 1: said it is, and that's why it was one part

757
00:42:35,320 --> 00:42:40,200
Speaker 1: of the Commerce Commission's recommendations for back personal banking services.

758
00:42:41,040 --> 00:42:43,920
Speaker 1: And I think also what he missed was a really

759
00:42:44,040 --> 00:42:47,160
Speaker 1: big point about open banking was that it is a

760
00:42:47,239 --> 00:42:51,839
Speaker 1: first step in something much wider, which is allowing consumers

761
00:42:52,120 --> 00:42:55,360
Speaker 1: to have control of their data. Open banking is the

762
00:42:55,400 --> 00:42:58,960
Speaker 1: beginning of the consumer data right in New Zealand. So

763
00:42:59,719 --> 00:43:03,200
Speaker 1: whether or not open banking gets rapidly taken up ninety

764
00:43:03,239 --> 00:43:06,399
Speaker 1: percent adoption within the first week, YadA, YadA, YadA, that's

765
00:43:06,400 --> 00:43:10,359
Speaker 1: not really what it's about. It's about laying out what

766
00:43:10,400 --> 00:43:14,400
Speaker 1: it means for a massive organization to have tons of

767
00:43:14,480 --> 00:43:19,400
Speaker 1: data about you and unlocking the potential of that data

768
00:43:19,440 --> 00:43:23,759
Speaker 1: for the consumer as well. It is expanding to electricity,

769
00:43:24,120 --> 00:43:27,719
Speaker 1: it is probably eventually expanding to insurance and to other places.

770
00:43:28,239 --> 00:43:31,160
Speaker 1: Right So I think those are two really important things

771
00:43:31,160 --> 00:43:34,640
Speaker 1: that he missed. And yes, we can look internationally and

772
00:43:34,680 --> 00:43:37,000
Speaker 1: we can look and say open banking hasn't had the

773
00:43:37,040 --> 00:43:40,480
Speaker 1: massive adoption that we've expected, and maybe there are some

774
00:43:40,520 --> 00:43:42,640
Speaker 1: other things that we can that need to be done

775
00:43:42,760 --> 00:43:45,279
Speaker 1: around it. But you can't do those things if we

776
00:43:45,280 --> 00:43:48,640
Speaker 1: don't have the framework in place to actually enable some

777
00:43:48,800 --> 00:43:51,520
Speaker 1: of the baseline for those services. Because banks were never

778
00:43:51,600 --> 00:43:54,640
Speaker 1: going to give up their data easily. It was in

779
00:43:54,680 --> 00:43:57,840
Speaker 1: New Zealand, you know, so this needed to kind of happen.

780
00:43:58,080 --> 00:44:00,440
Speaker 1: I did like what he said, this idea about having

781
00:44:00,800 --> 00:44:02,600
Speaker 1: a layer. How did he put it?

782
00:44:03,360 --> 00:44:07,680
Speaker 2: Yeah, basically the plumbing or the infrastructure of banking. You

783
00:44:07,719 --> 00:44:11,200
Speaker 2: could have a common infrastructure so that each new entrant

784
00:44:11,239 --> 00:44:13,480
Speaker 2: didn't have to try and replicate all of that. You know,

785
00:44:13,560 --> 00:44:17,080
Speaker 2: it's very expensive to do so, and you know Keywi

786
00:44:17,200 --> 00:44:20,440
Speaker 2: Bank can do it as the fifth largest off the banks,

787
00:44:20,440 --> 00:44:22,880
Speaker 2: but anything smaller than that it starts to get really difficult.

788
00:44:23,360 --> 00:44:26,440
Speaker 2: I guess then the problem is you run into everyone

789
00:44:26,520 --> 00:44:32,120
Speaker 2: innovates at the same pace. Then, so what is cool

790
00:44:32,160 --> 00:44:35,319
Speaker 2: about open banking and neo banks as they come in

791
00:44:35,360 --> 00:44:37,600
Speaker 2: and do things in a different way, potentially much more

792
00:44:37,600 --> 00:44:41,840
Speaker 2: efficient customer friendly way. So will you just get stuck

793
00:44:42,480 --> 00:44:44,799
Speaker 2: innovating at the same rate as A and Z and

794
00:44:44,840 --> 00:44:48,040
Speaker 2: B and ZED who have dragged the chain on innovation

795
00:44:48,160 --> 00:44:50,319
Speaker 2: in many respects. So that that is what I was

796
00:44:50,360 --> 00:44:54,239
Speaker 2: thinking about that. But you know, he's basically coming back

797
00:44:54,280 --> 00:44:58,040
Speaker 2: to the premise of the question here. What problem are

798
00:44:58,080 --> 00:45:01,000
Speaker 2: we trying to solve? Is it more competition? And literally

799
00:45:01,000 --> 00:45:01,879
Speaker 2: how do we get there?

800
00:45:02,400 --> 00:45:04,560
Speaker 1: Yeah, but this is my thing. This is exactly what

801
00:45:04,600 --> 00:45:08,920
Speaker 1: I'm saying, Like, yes, open banking can help to improve

802
00:45:08,960 --> 00:45:12,600
Speaker 1: competition with all of these other things around. You know,

803
00:45:12,640 --> 00:45:14,799
Speaker 1: we need all of those other recommendations to come through

804
00:45:14,840 --> 00:45:17,160
Speaker 1: as well. But that is actually not The problem that

805
00:45:17,200 --> 00:45:19,120
Speaker 1: we are trying to solve the problem we are trying

806
00:45:19,160 --> 00:45:22,680
Speaker 1: to solve is businesses have a lot of data about

807
00:45:22,719 --> 00:45:26,239
Speaker 1: a person, about you and about your habits, and there

808
00:45:26,239 --> 00:45:28,600
Speaker 1: are other companies saying I can use that data to

809
00:45:28,640 --> 00:45:31,880
Speaker 1: help improve your life and offer you news services that

810
00:45:31,960 --> 00:45:34,759
Speaker 1: you might find really useful and interesting, and at the

811
00:45:34,760 --> 00:45:36,560
Speaker 1: moment they can't do that. Of course, it's not a

812
00:45:36,600 --> 00:45:39,600
Speaker 1: silver bullet. It's just something that we believe is really

813
00:45:39,600 --> 00:45:42,720
Speaker 1: going to help progress things in personal banking in New Zealand.

814
00:45:42,960 --> 00:45:45,120
Speaker 2: Yeah, but we do need, we will need a couple

815
00:45:45,160 --> 00:45:49,120
Speaker 2: of sort of killer apps essentially, something that will drive adoption.

816
00:45:49,280 --> 00:45:51,040
Speaker 2: So that key we to get into the headspace we're

817
00:45:51,120 --> 00:45:55,120
Speaker 2: quite conservative around our finances. If we see something where

818
00:45:55,160 --> 00:45:57,120
Speaker 2: we go, well, everyone else is using it, I'm in

819
00:45:57,320 --> 00:46:00,880
Speaker 2: I understand it. It's easy to use, fees are lower.

820
00:46:00,920 --> 00:46:02,960
Speaker 2: I love this. That's when we're going to start to

821
00:46:02,960 --> 00:46:05,759
Speaker 2: see the adoption which will lead to that greater competition.

822
00:46:06,239 --> 00:46:10,920
Speaker 1: Yeah, yeah, definitely, And you know that's a matter of

823
00:46:10,960 --> 00:46:13,759
Speaker 1: time really, I think. And it will be different for

824
00:46:13,800 --> 00:46:16,640
Speaker 1: different people. Some people will like being able to look

825
00:46:16,680 --> 00:46:20,440
Speaker 1: at their whole financial net worth over multiple you know, inputs.

826
00:46:20,440 --> 00:46:23,560
Speaker 1: Some people will like being able to budget for their

827
00:46:24,040 --> 00:46:27,120
Speaker 1: for their family more effectively and essentially do the old

828
00:46:27,160 --> 00:46:30,560
Speaker 1: cash and the envelope trick, but doing replicating it digitally

829
00:46:31,000 --> 00:46:33,440
Speaker 1: to make life easier a little bit for them. Maybe

830
00:46:33,440 --> 00:46:35,360
Speaker 1: that will be something that that spurs it to me.

831
00:46:35,640 --> 00:46:38,960
Speaker 1: I'm about, Yeah, let's let's let's see what we can

832
00:46:39,000 --> 00:46:44,120
Speaker 1: do when we disaggregate customer data from the clutches of

833
00:46:44,760 --> 00:46:47,160
Speaker 1: big companies who who are using it, you know, for

834
00:46:47,200 --> 00:46:50,560
Speaker 1: their own profit, you know, essentially because if they have it,

835
00:46:50,600 --> 00:46:52,319
Speaker 1: they can they can use it. No one else can.

836
00:46:52,600 --> 00:46:55,640
Speaker 2: Yeah, it should just be a standard thing in every

837
00:46:55,719 --> 00:47:00,520
Speaker 2: market now, and that's where we'll end up. And just finally,

838
00:47:00,600 --> 00:47:04,640
Speaker 2: he's obviously a big advocate of artificial intelligence. He's been

839
00:47:05,320 --> 00:47:09,040
Speaker 2: using aspects of that at Kiwi Bank and very much

840
00:47:09,080 --> 00:47:12,520
Speaker 2: sees his career going in that direction. He thinks it's

841
00:47:12,560 --> 00:47:16,560
Speaker 2: going to be a game changer in every capacity beyond banking.

842
00:47:17,200 --> 00:47:21,200
Speaker 2: So yet another CIO we've talked to's very much on

843
00:47:21,239 --> 00:47:22,960
Speaker 2: that train. Absolutely.

844
00:47:23,360 --> 00:47:25,920
Speaker 1: I mean it's been fairly clear and I think, well,

845
00:47:25,920 --> 00:47:27,440
Speaker 1: you know, I really liked what he said, which is

846
00:47:27,480 --> 00:47:30,200
Speaker 1: what I've been thinking about and saying as well, which

847
00:47:30,239 --> 00:47:32,520
Speaker 1: is that we're pasted the hype now and we're finding

848
00:47:32,520 --> 00:47:34,840
Speaker 1: the use cases. We're finding the things that are actually

849
00:47:34,960 --> 00:47:40,080
Speaker 1: useful for the new generative AI tools and rather than

850
00:47:40,239 --> 00:47:45,720
Speaker 1: just making big grant promises and not delivering on them. Yeah, okay,

851
00:47:45,760 --> 00:47:48,440
Speaker 1: Well that's it for this week's episode, and a big

852
00:47:48,480 --> 00:47:51,560
Speaker 1: thank you to Hamish Rumbold for coming on the show.

853
00:47:52,040 --> 00:47:55,080
Speaker 2: The Business Soft Tech is everywhere you get your podcasts from,

854
00:47:55,120 --> 00:47:59,560
Speaker 2: including iHeartRadio, where you can stream every single episode. Show

855
00:47:59,600 --> 00:48:02,400
Speaker 2: notes are in the Tech section on the Business Desk website.

856
00:48:02,560 --> 00:48:05,080
Speaker 1: You can get in touch with your feedback, ideas, topics,

857
00:48:05,320 --> 00:48:09,080
Speaker 1: and guest suggestions by emailing me Ben at Businessdesk dot

858
00:48:09,120 --> 00:48:12,600
Speaker 1: co dot z will find me or Peter on LinkedIn

859
00:48:12,719 --> 00:48:13,160
Speaker 1: or x.

860
00:48:13,400 --> 00:48:15,799
Speaker 2: Another dose of the Business of Tech coming your way

861
00:48:16,080 --> 00:48:16,880
Speaker 2: next Thursday.

862
00:48:17,000 --> 00:48:17,719
Speaker 1: We'll catch you then