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Friday, November 23, 2018

We're trying to marry the skills available in a startup with a corporate, says Barclaycard CIO Keith Little

Barclaycard is best known for its debit and credit cards in the UK, but the division of Barclays is actually a multinational payment services provider that is experimenting with the latest emerging technologies.

Keith Little, chief information officer (CIO) at the company, tells NS Tech that this includes using blockchain in various pilot projects, including solving problems such as verifying identify. For example, Barclaycard is involved with Evernym’s accelerator, which is helping the company to better understand the implications of self-sovereign identity.

Meanwhile, Barclays has joined the IBM Q Network, a worldwide community of companies, startups, academic institutions and national research labs working with IBM to look into quantum computing, and explore the practical applications for business and science. The company is also partnering with fintech businesses to develop new products; last year it partnered with fintech company Flux to deliver digital receipting, while it is also continuously looking at partnering with tech companies – its most recent partnership has been with spend management platform Coupa to held speed up supplier payments and streamline payment reconciliation for buyers.

This week, Little was able to compare whether his own team’s strategy and views mirrored those of other UK IT leaders, as Barclaycard revealed the results of a survey taken by 100 CIOs. Like Little, 35 per cent of the surveyed CIOs have adopted or are piloting blockchain to provide greater transparency and increased security for data, while one in five (20 per cent) are also using or testing quantum computing.

Little explains that some of the standout statistics from the research centred on recruitment, and while significant progress had been made across other departments, with 72 per cent of CIOs saying colleagues across the business are more tech-savvy than five years ago, and 71 per cent claiming their C-Suite colleagues are now more knowledgeable about technology issues – there were still gaps to be filled within the IT space.

Barclaycard found that 78 per cent of CIOs believed they needed a wider skill set than they did five years ago and over half (55 per cent) were extremely or moderately concerned that the expertise of their teams won’t keep up with the needs of their organisation.

“There was concern about talent in terms of breadth of skills, but also in addressing this gap,” Little says, before adding that Barclaycard is trying to marry the wider range of skills that are usually found in a start-up environment, with those found in a corporate setting to help them to keep up-to-date.

“At Barclaycard, we’re trying to create a full stack person who is much more mobile to drive the agility agenda, and this helps in terms of retention and people planning their careers. This isn’t just about full-stack engineers or front-end developers – core engineers are still valid, and the concept of mainframe computing can still be applied to cloud computing,” he states.

However, Little emphasises the company isn’t just trying to be seen as more of a startup environment to attract a specific type of candidate, but that it’s about retaining existing employees, and re-training talent to work in different ways.

“It’s less about having people who want to work in Shoreditch at a startup, and it’s more about how you bring a workforce along with you on your journey. If we can upskill or change skills or take people on different journeys to allow for flexibility, then in the long-term this will allow us to attract talent as they would see that an organisation the size of Barclaycard can offer a more agile way, rather than a pretence that it is so full of legacy that you can’t do anything innovative,” he says.

As well as exploring blockchain and quantum computing, Barclaycard is using machine learning in a number of cases, including to track down fraud.

“This resulted in a genuine decline [in fraud], and so machine learning is important for fraud detection but we also use it in terms of how to look at data to better enhance our products, asking how we can help our customers get a better understanding of their customers, and new ways we can partner up with them,” Little explains.



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