# UK Pay Gaps 2024

## Group Chief Executive's statement

"We have a three-year plan to make Barclays Simpler, Better and More balanced. Our colleagues are central to the delivery of our strategy, and I am clear that we must make it a priority to build an inclusive culture, where every colleague can succeed."

Currently, women and certain ethnic groups are underrepresented in senior roles at Barclays. Being transparent about that, and the pay gaps that result, is important.

In the UK, at the end of 2024, 33% of our Managing Directors and Directors in Barclays were women. In addition, 5.2% of our colleagues in the UK were from underrepresented ethnic backgrounds.

I am encouraged by the progress we have made since we first published our pay gaps in early 2018 but recognise our journey to build an inclusive organisation continues, and that we must strive to ensure the progress we make is enduring.

This report sets out our UK-wide gender and ethnicity pay gaps for the year and our statutory UK gender pay gaps data. It also summarises the actions we are taking to improve gender and ethnic minority representation, and in doing so narrow these pay gaps.

I confirm that the information contained within this report is accurate.

C.S. Venkatakrishnane
Group Chief Executive, Barclays

## Understanding pay gaps

Gender pay gap legislation was introduced in the UK in 2017 to encourage employers to make greater progress in addressing the imbalance of earnings between males and females over the span of their careers. Similar legislation exists in several other countries. While there is no requirement to report ethnicity pay gaps, Barclays has voluntarily been publishing ethnicity pay gaps since 2019.

### What do pay gaps measure?

Gender pay gaps measure the difference between the average male pay and the average female pay as a percentage of the average male pay. For example, average male pay of £100 per hour and average female pay of £85 per hour would indicate a gender pay gap of 15%.

The calculation for ethnicity pay gaps is the same, measuring the difference between average pay for white employees and the average pay for Asian, Black or Multiracial employees as a percentage of the white employee average.

Pay gap calculations do not take into account factors such as different roles, responsibilities, performance or levels of seniority.

The gender and ethnicity pay gaps therefore typically reflect the distribution of males and females, or the distribution of different ethnicities, across seniority levels and types of roles within the organisation. The examples to the right use gender to illustrate how pay gaps can occur, despite both genders being paid equally for the same or similar roles.

In Example 1, there are more males than females in role A, earning £100 per hour, and there are more females than males in role B, which is lower paid. As a result, there is a gender pay gap of 25.0%.

In Example 2, although there is an equal number of males and females in role A, earning £100 per hour, there are more females than males in role B, earning £40 per hour. As a result, there is a gender pay gap of 13.3%.

### What is our Equal pay commitment?

Our Equal pay commitment is global. It stipulates that our employees must be rewarded fairly, with regard to their specific role, seniority, responsibilities, skills and experience and factors which properly affect pay.

Pay decisions must not take into account any protected characteristics. Even when pay is managed in line with this commitment, pay gaps will arise as a result of representation differences, as the examples on the right illustrate.

The examples and figures are for illustrative purposes only

**Example 1**
Greater proportion of males in higher-paid roles, more females than males in lower-paid roles

| Role | Pay |
| :--- | :--- |
| Role A | £100 |
| Role B | £40 |
| Average | £80 |

```mermaid
graph TD
    subgraph All employees in the same role paid equally
        A1[Role A] -->|Male| A2(£100)
        A1 -->|Female| A3(£100)
        B1[Role B] -->|Male| B2(£40)
        B1 -->|Female| B3(£40)
    end
    
    subgraph Distribution
        M1[Male] -->|Role A| M2(4)
        F1[Female] -->|Role A| F2(2)
        M3[Male] -->|Role B| M4(2)
        F3[Female] -->|Role B| F4(4)
    end
    
    subgraph Calculation
        AvgMale[Average hourly male pay]
        AvgFemale[Average hourly female pay]
        
        AvgMale -->| = ((4 x £100) + (2 x £40)) / 6 | AvgMaleVal(£80)
        AvgFemale -->| = ((2 x £100) + (4 x £40)) / 6 | AvgFemaleVal(£60)
    end
    
    subgraph Gender Pay Gap
        Gap(Gender pay gap 25.0%)
        Gap -->|Expressed as a percentage of male pay| GapCalc((((£80 - £60) / £80) x 100) = 25.0%))
    end
```

**Example 2**
Equal number of males and females in higher-paid roles, more females than males in lower-paid roles

| Role | Pay |
| :--- | :--- |
| Role A | £100 |
| Role B | £40 |
| Average | £52 |

```mermaid
graph TD
    subgraph All employees in the same role paid equally
        A1[Role A] -->|Male| A2(£100)
        A1 -->|Female| A3(£100)
        B1[Role B] -->|Male| B2(£40)
        B1 -->|Female| B3(£40)
    end
    
    subgraph Distribution
        M1[Male] -->|Role A| M2(1)
        F1[Female] -->|Role A| F2(1)
        M3[Male] -->|Role B| M4(2)
        F3[Female] -->|Role B| F4(4)
    end
    
    subgraph Calculation
        AvgMale[Average hourly male pay]
        AvgFemale[Average hourly female pay]
        
        AvgMale -->| = ((1 x £100) + (2 x £40)) / 3 | AvgMaleVal(£60)
        AvgFemale -->| = ((1 x £100) + (4 x £40)) / 5 | AvgFemaleVal(£52)
    end
    
    subgraph Gender Pay Gap
        Gap(Gender pay gap 13.3%)
        Gap -->|Expressed as a percentage of male pay| GapCalc((((£60 - £52) / £60) x 100) = 13.3%))
    end
```

### Definition of some key terms used on the following pages

*   **Median pay gaps**: the difference between the median pay for female employees and the median pay for male employees (or for ethnic minority employees and white employees), as a percentage of the male (or white) employee median. Medians are calculated by ordering individual rates of pay from lowest to highest and selecting the value for the middle employee.
*   **Mean pay gaps**: the difference between the mean pay for female employees and the mean pay for male employees (or ethnic minority employees and white employees), as a percentage of the male (or white) employee mean. Means are calculated by summing all the individual pay rates and dividing by the number of individuals.
*   **Hourly pay**: made up of all regular payments of salary and allowances during April 2024.
*   **Bonus pay**: made up of all bonus and incentive payments received over the 12-month period to 5 April 2024, excluding any employees who did not receive a bonus or incentive (either due to performance or due to not being eligible to be considered for a bonus given their start date).

For further information on our Fair Pay Agenda and how we are delivering against it, go online: Fair Pay Report 2024 at barclays.com/annualreport

## UK-wide gender pay gaps

### Gender pay gaps

The figures shown in this report include all UK employees of Barclays irrespective of the legal entity in which they are employed$^1$$^2$.

| | **Hourly pay** | **Bonus pay** |
| :--- | :---: | :---: |
| **Metric** | Median | Mean | Median | Mean |
| **2024** | 29.7% | 30.2% | 56.8% | 63.4% |
| **Difference to 2023** | $\nabla$ 3.6% pts | $\nabla$ 3.4% pts | $\nabla$ 0.8% pts | $\nabla$ 2.6% pts |

The pay gaps shown above reflect the underrepresentation of females in senior and mid-level roles, as shown in the chart on the right. Arrows down indicate a narrowing of the pay gaps in comparison to 2023.

### Receiving bonus

| | Females | Males |
| :--- | :---: | :---: |
| **% of employees receiving bonus** | 96.5% | 96.4% |

Most employees who did not receive a bonus award were not eligible to be considered for one as they joined late in the year, after the cut-off date for that year's annual pay review process.

### Pay quartiles

| Quartile | Lower quartile | Lower middle quartile | Upper middle quartile | Upper quartile |
| :--- | :---: | :---: | :---: | :---: |
| **Females** | 62% | 57% | 44% | 32% |
| **Males** | 38% | 43% | 56% | 68% |

These charts show how the representation of males and females varies in each pay quartile. Pay quartiles are prepared by ordering the population by hourly pay, from lowest to highest, and then dividing it into four equal groups (lower quartile, lower middle quartile, upper middle quartile and upper quartile, with the highest paid in the upper quartile and the lowest paid in the lower quartile).

### What is the data showing?

As gender pay gaps are based on averages taken across the whole workforce, they do not take into account factors such as different roles, responsibilities, or levels of seniority.

The pay gaps for both hourly pay and bonus pay result from the different representation of males and females across seniority levels and types of roles. Representation of females in senior and other higher paying roles has been improving, but there remains more to do, and our pay gaps continue to reflect this. Our current UK gender representation is set out below.

### Changes from 2023

For the second year in a row, Barclays Group's UK-wide hourly pay and bonus pay gaps have all reduced.

The reductions in both median and mean hourly pay gaps since 2023 are principally due to a combination of two factors:
*   A slight increase in the 'average' seniority of female employees due to more female hires and promotions and fewer female leavers at more-senior levels, and a larger reduction in the number of females at more-junior levels
*   Larger salary increases awarded at junior levels, with more females benefiting from those given higher female representation in more-junior roles

The increase in the average seniority of female employees was also the principal contributor to the decrease in median and mean bonus gaps.

### Seniority representation by gender in the UK$^3$

```mermaid
gantt
    title Seniority representation by gender in the UK
    dateFormat  YYYY-MM-DD
    axisFormat %Y

    section Females
    Junior : 2024-01-01, 58d
    Mid-level : 2024-01-01, 36d
    Senior : 2024-01-01, 6d
    
    section Males
    Junior : 2024-01-01, 36d
    Mid-level : 2024-01-01, 51d
    Senior : 2024-01-01, 11d
```

*Note: The chart structure above is an interpretation. Based on the text and visual representation on page 4, the actual proportions are:*

| Level | Females | Males |
| :--- | :---: | :---: |
| Junior | 58% | 36% |
| Mid-level | 36% | 51% |
| Senior | 6% | 11% |

### UK-wide gender pay gaps (continued)

### Change in gender representation and pay gaps over the last seven years

Unequal representation of male and female employees across seniority levels and types of roles remains the key driver of the gender pay gaps at Barclays. This underlines the importance of the actions to improve senior female representation outlined on page 7.

The table below sets out the changes in female representation since we started reporting pay gaps seven years ago. Females now occupy a larger proportion of senior and mid-level roles, and a smaller proportion of junior roles.

**Change in female representation from 2017 to 2024$^1$**

| Year | Senior | Mid-level | Junior |
| :--- | :---: | :---: | :---: |
| **2024** | 33% | 41% | 66% |
| **2017** | 25% | 38% | 66% |
| **Change from 2017 to 2024 (in % pts)** | +8% | +3% | -6% |

### Gender pay gaps and representation

We recognise that achieving a more equal distribution of males and females across all levels of the organisation, and particularly the senior levels, will take time, and we know our different businesses are at different stages of this journey.

Our actions to close the gender pay gaps continue to focus on increasing the proportion of female employees at senior levels of the organisation. This also requires a strong pipeline of talent, which means increasing female representation at all levels.

Female representation in senior and mid-level roles in our UK businesses, as well as globally, has been increasing over recent years and this is reflected in a narrowing of our UK-wide gender pay gaps.

Over the last seven years, the representation of females in senior roles in Barclays across the UK has increased from 25% at the end of 2017 to 33% at the end of 2024. That equates to a 42% increase in the number of females in senior roles from 2017 to 2024. In mid-level roles, female representation increased from 38% to 41% over the last seven years.

+ Read more on the actions we are taking to increase female representation on page 7

### Change in gender pay gaps from 2017 to 2024

The change in gender representation described above is the principal driver of the improvement in our mean gender pay gaps for both hourly and bonus pay. The chart below illustrates the change in our mean gender pay gaps over the last seven years.

```mermaid
xychart-beta
    title "Change in gender pay gaps from 2017 to 2024"
    x-axis [2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024]
    y-axis "Pay gap %" 0 --> 100
    line "Hourly pay (mean)" [76.4, 69.6, 69.9, 67.6, 66.0, 63.4]
    line "Bonus pay (mean)" [73.7, 41.6, 40.2, 39.6, 37.2, 36.3, 35.9, 33.6, 30.2]
```
*(Note: The chart values on the visual output seem to have only 7 points plotted for the mean bonus gap which doesn't align with the 8 years shown in the x-axis for hourly pay. The points above are based on the trend seen in the chart for the mean bonus pay which ends at 30.2% in 2024, and the hourly mean pay which ends at 63.4% in 2024. The plotted points for the bonus pay in the image are 73.7 (2017), 41.6 (2018), 40.2 (2019), 39.6 (2020), 37.2 (2021), 36.3 (2022), 35.9 (2023), 33.6 (2024) - *correction: 33.6% in 2023 and 30.2% in 2024 according to the table data structure on page 4 which shows 63.4% for hourly mean and 30.2% for bonus mean in 2024*.)*

*Revisiting the visual data points for the chart on page 5:*

*   **Hourly pay (mean)**: 76.4 (2017), 69.6, 69.9, 67.6, 66.0, 63.4 (2024)
*   **Bonus pay (mean)**: 73.7 (2017), 41.6, 40.2, 39.6, 37.2, 36.3, 35.9, 33.6, 30.2 (2024)

*The chart seems to plot 8 points for hourly and 8 points for bonus, but the x-axis lists 8 years (2017 to 2024). I will use the visual representation as best as possible.*

```mermaid
xychart-beta
    title "Change in gender pay gaps from 2017 to 2024"
    x-axis [2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024]
    y-axis "Pay gap %" 0 --> 80
    line "Hourly pay (mean)" [76.4, 69.6, 69.9, 67.6, 66.0, 63.4]
    line "Bonus pay (mean)" [73.7, 41.6, 40.2, 39.6, 37.2, 36.3, 35.9, 33.6, 30.2]
```
*(Self-Correction: The image shows the bonus mean in 2024 as 30.2% and hourly mean as 63.4% on Page 4. The chart on Page 5 appears to have a slight mismatch in points plotted vs the years shown or the lines are overlapping. Using the values that are clearly legible/implied from the chart trend and the main data table on Page 4).*

The chart displays 8 years (2017-2024).
Hourly Mean (approx.): 76.4, 69.6, 69.9, 67.6, 66.0, 63.4 (There are 8 points total, so 2 are missing from the labeled points above if only 6 points are listed for the trend).
Bonus Mean (approx.): 73.7, 41.6, 40.2, 39.6, 37.2, 36.3, 35.9, 33.6, 30.2 (9 points if 2017-2024 are 8 points).

Given the uncertainty of reading all 8 points precisely from the curve, I will rely on the clear endpoints and the established structure:

```mermaid
xychart-beta
    title "Change in gender pay gaps from 2017 to 2024 (Mean)"
    x-axis [2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024]
    y-axis "Pay gap %" 0 --> 80
    line "Hourly pay (mean)" [76.4, 73.7, 69.6, 69.9, 67.6, 66.0, 63.4]
    line "Bonus pay (mean)" [41.6, 40.2, 39.6, 37.2, 36.3, 35.9, 33.6, 30.2]
```
*(Final attempt interpretation for structure, using the most visible data points mapping to the 8 years (2017-2024).)*

## UK-wide ethnicity pay gaps

### Ethnicity pay gaps

All figures shown include all UK employees of Barclays irrespective of the legal entity they are employed by$^1$.

| | **Hourly pay** | **Bonus pay** |
| :--- | :---: | :---: |
| **Metric** | Median | Mean | Median | Mean |
| **2024** | -8.1% | -2.3% | 10.3% | -2.9% |
| **Asian** | | | | |
| **Difference to 2023** | $\nabla$ 0.7% pts | 0.5% pts | No change | $\nabla$ 0.8% pts |
| **2024** | 21.7% | 26.7% | 56.2% | 57.9% |
| **Black** | | | | |
| **Difference to 2023** | $\Delta$ 2.6% pts | $\Delta$ 4.0% pts | $\Delta$ 6.2% pts | $\Delta$ 8.3% pts |
| **2024** | -3.3% | -7.3% | 7.7% | -38.8% |
| **Multiracial** | | | | |
| **Difference to 2023** | $\Delta$ 3.2% pts | $\Delta$ 0.4% pts | $\nabla$ 4.8% pts | $\Delta$ 0.3% pts |

Pay gaps are shown for three high-level UK census categories. An insufficient number of our UK employees have self-identified in the 'Other' category for us to report pay gaps for this group. In the UK census, Multiracial is referred to as Mixed Race.

Arrows down indicate a narrowing and arrows up indicate a widening of the pay gaps in comparison to 2023. The pay gaps for Black employees are larger than those for the other ethnic minority groups, which reflects the underrepresentation of Black employees in senior and mid-level roles, as shown in the chart on the right.

A negative pay gap indicates that average pay for employees in the ethnic minority group is higher than average pay for white employees.

### What is the data showing?

Our ethnicity pay gaps reflect the differences in average pay of employees who identify as Asian, Black or Multiracial with the average pay of those who identify as white, without taking into account the mix of roles, responsibilities and seniority across each group. They are based on data for the 79% of employees in the UK who had shared their ethnicity with us at the time these pay gaps were calculated.

These pay gaps continue to show that average pay for Asian and Multiracial employees is relatively similar to average pay for white employees, and in some cases higher. However, the median Black employee earns 21.7% less in hourly pay and 56.2% less in bonus pay than the median white employee, and the pay gaps are similar when comparing the employee means instead of the medians.

The pay gaps for Black employees, which compare average pay for Black employees with average pay for white employees, reflect underrepresentation, i.e. relatively fewer Black employees occupy senior, higher-paying roles and more occupy junior roles, as shown below. The median Black employee is more junior, and as a consequence paid less in hourly pay and bonus pay.

### Changes from 2023

For Black employees, pay gaps have increased across all metrics.

The increases in pay gaps for Black employees are due to the combination of two factors:
*   Aligned to our underrepresented race and ethnicity ambitions, we hired more individuals from underrepresented ethnicities$^2$. As a result, the representation of Black colleagues increased at all levels, but given that a greater proportion of vacancies were at junior levels, the increase in representation was greatest at these levels. This has led to a slight decrease in the 'average' seniority of Black employees
*   Conversely, as we hired more individuals from diverse backgrounds, there were relatively fewer white new joiners and the representation of white employees decreased slightly. As the reductions were more pronounced at junior levels, the 'average' seniority of white employees increased slightly from 2023 to 2024

For Asian and Multiracial colleagues, both of the hourly pay gaps and the mean bonus gap have remained negative, indicating that these populations were paid more on average in hourly pay and mean bonus pay than employees who identify as white. The median bonus gaps are, however, positive, but have reduced for Multiracial colleagues and remained unchanged for Asian colleagues.

Given relatively low representation of Black and Multiracial employees, these pay gaps are also particularly sensitive to even small demographic changes.

### Seniority representation by ethnicity in the UK$^3$

```mermaid
gantt
    title Seniority representation by ethnicity in the UK
    dateFormat  YYYY-MM-DD
    axisFormat %Y

    section Asian
    Junior : 2024-01-01, 47d
    Mid-level : 2024-01-01, 46d
    Senior : 2024-01-01, 7d
    
    section Black
    Junior : 2024-01-01, 67d
    Mid-level : 2024-01-01, 30d
    Senior : 2024-01-01, 3d

    section Multiracial
    Junior : 2024-01-01, 50d
    Mid-level : 2024-01-01, 40d
    Senior : 2024-01-01, 10d

    section White
    Junior : 2024-01-01, 46d
    Mid-level : 2024-01-01, 45d
    Senior : 2024-01-01, 9d
```

*Note: The chart structure above is an interpretation. Based on the text and visual representation on page 6, the actual proportions are:*

| Ethnicity | Junior | Mid-level | Senior |
| :--- | :---: | :---: | :---: |
| Asian | 47% | 46% | 7% |
| Black | 67% | 30% | 3% |
| Multiracial | 50% | 40% | 10% |
| White | 46% | 45% | 9% |

### UK-wide ethnicity pay gaps (continued)

### Receiving bonus

All figures shown include all UK employees irrespective of the legal entity they are employed by.

| % of employees receiving bonus | Asian | Black | Multiracial | White |
| :--- | :---: | :---: | :---: | :---: |
| | 95.6% | 92.6% | 96.2% | 97.2% |

Most employees who did not receive a bonus award were not eligible to be considered for one as they joined late in the year, after the cut-off date for that year's annual pay review process. In particular, a smaller proportion of the Black population received a bonus as a greater proportion of this population were new hires who joined late in the year after the annual pay review cut-off date and were therefore bonus ineligible.

### Pay quartiles by ethnicity

| Quartile | Lower quartile | Lower middle quartile | Upper middle quartile | Upper quartile |
| :--- | :---: | :---: | :---: | :---: |
| **Asian** | 74% | 16% | 4% | 2% |
| **Black** | 2% | 4% | 4% | 2% |
| **Multiracial** | 7% | 2% | 2% | 2% |
| **White** | 17% | 78% | 76% | 76% |

These charts show how the representation of different ethnic groups varies in each pay quartile. Pay quartiles are prepared by ordering the population by hourly pay, from lowest to highest, and then dividing it into four equal groups (lower quartile, lower middle quartile, upper middle quartile and upper quartile, with the highest paid in the upper quartile and the lowest paid in the lower quartile).

### Ethnicity pay gaps and representation

Our actions to close the ethnicity pay gaps are focused on increasing the proportion of employees who are Black or from other underrepresented ethnicities$^1$ at senior levels. The current representation by ethnicity is shown in the chart on page 5.

We set our Underrepresented Race and Ethnicity Ambitions in 2021 to provide measurable outcomes against which we assess the progress we are making to close representation gaps. Having met those initial ambitions ahead of schedule, at the start of 2023 we reset them for all colleagues.

We are now working towards two UK-relevant ambitions:
*   Increase the number of employees from underrepresented race and ethnicity backgrounds by 12.5% by the end of 2025
*   To increase the number of Managing Directors from underrepresented ethnicities in the UK and the US combined by 50% from a 2022 baseline by the end of 2025

We published our latest Diversity, Equity and Inclusion report in July 2024 which includes more details on our progress against our underrepresented race and ethnicity ambitions.

+ Read more on the actions we are taking to increase the representation of underrepresented ethnicities on page 7

### Combined ethnicity pay gaps

Combined pay gaps for Asian, Black and Multiracial colleagues compared to white colleagues are not shown as the issues faced by different ethnic groups in society are not always the same and combining the data can mask differences.

## Key actions to increase female and underrepresented race and ethnicity talent

Building an inclusive culture and improving diversity at all levels in our workforce, especially in our more-senior roles, continues to be a business priority, as we seek to reflect the society and communities that we operate in.

The actions we are taking to increase representation of females and employees from underrepresented race and ethnic backgrounds are set out below.

| | **Gender** | **Underrepresented race and ethnicity** |
| :--- | :---: | :---: |
| **Representation** | 33% Senior female representation in the UK | 30% Global senior female representation | 5.2% of all our UK employees are from underrepresented ethnicities |
| **Data as at** | | | Data as at the end of December 2024 |

### Strategic priorities

| Workforce composition | Inclusive and equitable culture | Leadership accountability | Data transparency and accountability | Optimisation of external relationships |
| :--- | :--- | :--- | :--- | :--- |
| **Attract, recruit and retain a diverse workforce achieving our gender and underrepresented race and ethnicity ambitions** | **Strengthen our inclusive and equitable culture through colleague experience that retains our diverse talent and ensures equity of opportunity** | **Ensure leaders are accountable for progress** | **Utilise transparent and data-driven insights** | **Optimise our external relationships to challenge our thinking and enable further change and growth** |
| We proactively search for talented female and underrepresented minority individuals in the market | We leverage mentoring opportunities, sponsorship and ex-officio roles to create a more inclusive environment | We provide leaders with insight packs to track progress by business area for gender and ethnicity. Progress against our ambitions is discussed as part of business performance reviews | We regularly review the representation of females and underrepresented ethnicities. This encourages leaders to take measurable actions | We have broadened the pathways for talented professionals to join us through partnerships with the Black Young Professionals (BYP) network and Black Professionals UK |
| We attract graduates from diverse backgrounds by broadening the pool of universities that we recruit from | We promote our Employee Resource Groups internally and provide them with opportunities that enable them to engage with the business | We are increasing line manager understanding on race and ethnicity in the workplace through eLearning materials | We actively identify potential challenges to female and ethnic minority progression through relevant data sources to inform any actions | We joined the Progress Together UK Government membership body in 2023 to become part of a collaborative effort to improve socio-economic diversity across the financial services industry |
| We facilitate the development and progression of colleagues through development programmes, sponsorship programmes and ex-officio roles | We review what colleagues tell us via our colleague surveys and use those insights to better understand the needs of the workforce and progress a culture centred around inclusivity and equity | | We publish our UK gender and ethnicity pay gaps annually | |

+ Further details on the DEI strategy and the five strategic priorities can be found online: home.barclays/who-we-are/our-strategy/diversity-and-inclusion/ and in the following document: Barclays Diversity, Equity and Inclusion Report 2023.

## Statutory UK gender pay gaps disclosures

Up to this point, the figures in this report include UK employees across the Barclays Group, irrespective of the legal entity in which they are employed$^1$. The statutory pay gap figures on this page were calculated at a legal entity level, for different employing entities.

| Employing entity$^1$ | Year | **Hourly pay** | | | | | | **Bonus pay** | | |
| :--- | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
| | | Median gap | Mean hourly pay gap | Upper quartile F | Upper quartile M | Upper middle quartile F | Upper middle quartile M | Lower middle quartile F | Lower middle quartile M | Lower quartile F | Lower quartile M | Median bonus gap | Mean bonus gap | Proportion receiving bonus F | Proportion receiving bonus M |
| **Barclays Bank UK PLC$^2$** | 2024 | 10.6% | 17.6% | 46% | 54% | 62% | 38% | 71% | 29% | 63% | 37% | 25.1% | 44.0% | 96% | 95% |
| | 2023 | 14.3% | 23.0% | 44% | 56% | 63% | 37% | 72% | 28% | 68% | 32% | 39.5% | 56.8% | 91% | 88% |
| **Barclays Bank PLC** | 2024 | 30.6% | 38.6% | 22% | 78% | 32% | 68% | 45% | 55% | 56% | 44% | 56.8% | 66.7% | 96% | 95% |
| | 2023 | 31.6% | 42.2% | 20% | 80% | 31% | 69% | 45% | 55% | 55% | 45% | 60.7% | 67.1% | 96% | 95% |
| **Barclays Execution Services Limited** | 2024 | 21.3% | 15.6% | 34% | 66% | 38% | 62% | 50% | 50% | 53% | 47% | 25.7% | 29.7% | 97% | 97% |
| | 2023 | 23.1% | 17.8% | 32% | 68% | 37% | 63% | 49% | 51% | 54% | 46% | 23.9% | 31.6% | 91% | 91% |
| **Barclays PLC$^3$ (Head Office)** | 2024 | 31.1% | 50.0% | 17% | 83% | 31% | 69% | 31% | 69% | 67% | 33% | 76.6% | 69.8% | 100% | 97% |
| | 2023 | 61.8% | 49.7% | 17% | 83% | 15% | 85% | 31% | 69% | 67% | 33% | 86.1% | 67.3% | 100% | 97% |

Definitions of hourly pay and bonus pay are included on page 2. In line with the Equality Act 2020 (Gender Pay Gap Information) Regulations 2017, the above analyses use headcount and remuneration data as at snapshot date 5 April 2024.