Gender pay gap: Our progress so far

2019 figures correct as of March 2021. 2017 and 2018 figures are correct as of 5 April 2019.

The figures are calculated based on an average of what we pay all men and women regardless of their role, so the numbers don’t mean that women are paid less for equal work as men - that would be illegal. They show that on average, women at Starling earn £71.91 for every £100 earned by men. When you use the median - the midpoint of all salaries - women earn £80.00 for every £100 earned by men.

While I’m pleased that we have narrowed the gap, particularly at a time when some reports suggest it’s actually getting wider in the country at large, it’s clear from these figures that we’ve still got a long way to go to eliminate the gap entirely. That is our goal at Starling, not only because it is the right - and fair - thing to do, but also because it is likely to make for a more successful company. And that, in turn, should mean a better service for our customers.

There’s no shortage of evidence to support the view that diverse teams perform better in the workplace overall. In fact, the business case for diversity of all sorts is now widely accepted in management courses and boardrooms around the world, even if it is rarely rigorously applied in practice.

In Starling’s case, as with other tech companies, the global shortage of software engineers adds an element of urgency to the argument against drawing talent from a narrow pool of male candidates.

Our figures this year show that we are succeeding in getting a greater proportion of women into senior roles. Women occupy 21% of jobs in a highest-paying quartile, compared to 15% last year.

You’ll notice that the data shows that we have proportionately more men among our lowest paid group. This too gives us pause for thought as it is a reflection of the fact that we’re hiring more men than women into roles that fall in the lower quartiles. This is something we will be looking at this year.

At Starling we’re not yet legally required to publish our gender pay gap numbers, but we’ve decided to do so because we think it’s a good way to hold ourselves accountable and a good starting point for understanding the root causes of the gap.

As I’ve said before, I believe that part of the gender pay gap problem is to do with the ideas we have about the kind of jobs that ‘men do’ and ‘women do’. At Starling, we operate at the axis of two traditionally male-dominated professions, banking and technology. Banking has long been dominated by men, but this wasn’t always the case with technology.

From the Second World War to the 1960s, women represented an important engine of growth in tech. My heroes from this era include the film star Hedy Lamarr, who, with the composer George Antheil, developed a radio system essential to the creation of GPS and wifi technology. There’s also Katherine Johnson, an African-American mathematician celebrated in the film Hidden Figures, who contributed to America’s space programme.

I’m a computer scientist by training myself and believe that the success of these extraordinary women shows the importance of breaking down stereotypes about who can do different kinds of jobs.

So what else are we doing at Starling to narrow the gap?

We’re taking particular care with our job ads to make sure they are inclusive and capture the widest possible range of applicants. We do this by running the copy through a language decoder where appropriate to spot hidden bias and by keeping our engineering job descriptions high level and not overly prescriptive.

We’re also introducing more creative ways of working that allow a better work/life balance and help us throw our hiring net far and wide.

A major aim of the gender pay gap rules was to encourage organisations to look beyond the traditional catch-all excuses surrounding women’s “career choices” and to actively seek new ways of creating a pipeline taking talented women to the top jobs. So we’re also working harder on promoting from within.

On their own, the new gender pay gap reporting rules are a blunt tool. They don’t show how race, education, experience, class, age, ability, neurological differences or other factors play into pay. But if they start us talking openly about pay and promotion discrepancies, that has to be a good start.

The provisional 2019 figures originally published, before the above revision, were: median gender pay gap 13.83%; mean gender pay gap 21.18%. The provisional 2019 figures for the proportion of women in higher paying roles were as follows, with the highest paid quartile first: Quartile 1, 23%; Quartile 2, 42%; Quartile 3, 39%; Quartile 4, 38%.