Financial Wellbeing Resources - Wagestream

EWA Impact Assessment: H1 2021 - Wagestream

Written by Admin | Jun 7, 2021 11:00:00 PM

How do people use Earned Wage Access, and what impact does it have on their financial wellbeing?

These are the core questions we address in the H1 2021 EWA Impact Assessment, which is based on independent survey data of 2,200 users, anonymised transaction data of 1 million EWA transfers over 18 months, and global financial inclusion benchmarks.

Context & Methodology

This report tracks the impact of Earned Wage Access (EWA) on individual users. EWA is, quite simply, the way we all used to be paid. It means workers can access their already-earned income throughout the month, instead of waiting for the end of an extended, locked pay cycle.

Invented in the 1960s as banking infrastructure evolved and processing fees became costly for employers and banking providers, research suggests that extended, locked pay cycles drive irregular spending patterns and create a ‘liquidity trap’ for working adults.

With most (89%) workers now saying they would prefer a return to EWA, employers are responding by removing the locked pay cycle—typically offering EWA as part of a broader financial wellbeing programme.

This report tracks the impact of that shift through data provided by 60 Decibels, a leading impact measurement firm, and Wagestream, a financial wellbeing service offered by employers which includes financial education, coaching, savings, budgeting and EWA.

As Europe’s most widely used provider, Wagestream offers the most complete dataset currently available on usage and impact of removing the locked pay cycle, at an individual employee level. Specifically, this H1, 2021 report builds on:

  • Perception data, collected through anonymised surveys of 2,220 Wagestream users
  • Usage data, based on a sample 1,000,000 EWA transactions through Wagestream
  • Social impact data, based on the 60 Decibels global impact measurement framework

Collected between June – November 2020, we will use these datasets to explore how Wagestream’s EWA feature (‘Stream’) is used by UK workers, how this has changed over time, and most importantly, what impact this has had on users.

While there are areas requiring more analysis and discussion, the findings are encouraging. They serve as a helpful first step in understanding what it means to return to flexible pay cycles, and give us clear direction on questions and hypotheses future assessments should address.

Thank you to the experts at 60 Decibels, Big Society Capital and Fair By Design—for their support in gathering independent data, input on this report’s methodology and analysis , and guidance on how to meaningfully measure the impact of EWA and broader financial wellbeing services like Wagestream.

Section 1: Understanding EWA Usage

To better understand the impact of removing extended, locked pay cycles, we need to answer a set of fundamental questions about how workers interact with a more flexible pay cycle through EWA.

This section will focus on transaction data aggregated by Wagestream—a service which employers offer to employees (‘users’) as a holistic financial wellbeing programme. The app provides financial education, coaching, budgeting and savings tools, as well as integrating with payroll to provide EWA.

The research conducted for this report suggests Wagestream is serving a heterogenous user base: the majority (87%) of users ranged from 21-60 years old, and while EWA has typically been associated with part-time and low-income workers, a quarter (25%) of users represented an annual household income of over £30,000—almost double the UK ‘poverty line’ of £17,640 annual income.

As with most providers, Wagestream’s EWA feature currently offers users a semi-locked pay cycle: throughout the month, up to 50% of a user’s accrued gross earnings are available to access. Transfers are instant, and processing fees are subsidised by the employer or charged at a capped fee of £1.75 (per transfer) to the employee; we will refer to this as an ‘EWA transfer’.

How do users interact with a flexible pay cycle?

a) How often do users make EWA transfers?

This report does not cover the app’s broader feature set in detail, but it is important to note that a significant proportion (62%) of Wagestream users do not make any EWA transfers.

Instead, they choose to use the app exclusively for other features—most notably ‘Track’, which helps with in-month budgeting by showing accrued earnings in real-time, throughout the month. Feedback during the research suggested this is primarily about control: users often stated they find peace of mind simply in knowing their earnings are theirs to use, instead of being locked in an extended pay cycle.

On average, 20% of enrolled users are choosing to transfer one to three times each month, allowing them to roughly replicate the cadence of weekly pay. Meanwhile, 9% of enrolled users make more frequent transfers, resulting in seven or more transfers in a given pay period (roughly two transfers per week).¹

During the Covid-19 pandemic, this subset grew as users chose to transfer smaller amounts more often. This change was likely a symptom of the uncertain macro environment created by the pandemic, and resulting inconsistency in work patterns for some of the labour market.

While the vast majority seem to be using EWA in a moderate, controlled way, most apps—including Wagestream—apply additional safeguards, allowing companies and users to set usage controls; users of this particular service also receive targeted in-app reminders of fees associated with transfers

b) How much do users transfer?

As a reminder, this EWA feature allows employees to transfer up to 50% of their accrued gross wages.

Their available balance increases as shifts are completed, and it reduces whenever a transfer is made.

Overall, the average transfer is £58—though as set out earlier, we should expect to see a higher average after the pandemic, during which many users chose to transfer smaller amounts, more often.

The amount a user chooses to transfer is primarily governed by two things:

  • The amount they wish to transfer to their bank account (e.g. to cover a specific expense), and
  • The amount they have available to transfer at that time

The second of these points is instructive, since the amount available to transfer decreases after each time a transfer is made. Those who transfer larger amounts will, by design, be unable to transfer as frequently as those who transfer smaller amounts (assuming their overall earnings are similar). This unavoidably skews the previous graph to the lower amounts, and provides useful context to the 62% of transfers that are for less than £50.

To remove this nuance, consider instead the total amount that an employee transfers each month as a percentage of their salary.²

Again, we see that 62% of enrolled users are opting not to stream within a given month.

Those who do choose to make a transfer are accessing 26% of their gross salary on average, which represents roughly half of what they could have transferred in that pay period.

How does flexible pay usage evolve over time?

It can be insightful to look at these high level metrics concerning product usage over the short-term. But, to more comprehensively scrutinise the impact EWA is having on the financial resilience of individuals, we need to chart how these behaviours develop from one month to the next, and beyond.

If EWA is to tackle the ‘liquidity trap’ created by extended, locked pay cycles, we should seek to understand whether employees use EWA more or less, the longer they have access to it.

To do this, we’ll map distinct points in the customer journey: the month a user makes their first transfer, and then regular three-month intervals after that.³ We’ll examine how often employees make transfers, how much they are transferring, and when in the pay cycle they are making these transfers—and how this changes, over the first 12 months of the user journey.

a) Do users transfer more often, over time?

In the month of their first EWA transfer, the median user makes a total of two transfers. Six months later, the median has decreased to one transfer per month.

b) Do users transfer larger amounts, over time?

As with analysing transfer volumes earlier, it’s possible to bring more context to the longer-term usage journey by considering amounts transferred in a given month, as a percentage of gross salary.⁴

This trend towards lower amounts over time implies users may be improving their financial situation through access to EWA, over time, gradually building up financial resilience. To more fully understand these implications, in the report’s second section we’ll explore users’ own views on the removal of extended, locked pay cycles, and the impact it has had on their financial behaviours and overall wellbeing.

c) Do users transfer earlier in the pay cycle, over time?

The pattern of EWA usage becomes clearer once we begin to assess when users are choosing to access their earnings.

We can do this by starting with the first transfer users make in a given pay cycle, and recording how many days before the end of the pay cycle that transfer occurred.⁵ This allows us to gauge whether users are accessing their income earlier or later from one month to the next—in this case, over the period of a year.

In month ‘0’, users make their first transfer at an average of nine days before payday. By the end of their first year this has reduced to 8 days before payday, meaning employees are waiting slightly longer each month before choosing to access their earned wages.

One early concern, with returning to flexible pay cycles, had been that users may begin accessing their earnings increasingly early in the month—weakening their financial position as a result. Encouragingly, the usage data collected shows that this is not the case: within a year of making their first transfer users are, on average, transferring lower amounts, less often, and at later stages in the pay cycle than they were originally.

This means that at the height of a global pandemic, when the labour market experienced less job security and greater financial strain than any moment in recent history, EWA was still used in moderation and employees appear to have gradually built financial resilience, as a result of their employers returning to a flexible pay cycle.

Section 2: Evaluating EWA Impact

To start understanding the broader social impact of reverting to flexible pay cycles, we need to listen to the end-user. We need to invest time in understanding how workers feel about their finances, once locked pay cycles are removed and they are given choice over when and how they are paid.

It’s important to note this research was conducted within the context of ‘responsible EWA’—an EWA feature offered as part of a financial wellbeing service (in this case, Wagestream) which encourages better financial behaviours and decisions, through education, coaching, budgeting and savings tools.

How do users categorise their spend?

Firstly, we should evaluate how users think about their own EWA transfers. This simple step is important, because the way individuals categorise their usage links to the broader ways in which they manage income and think about their personal finances.

Following each transfer, users are asked to pick one of eight categories to identify why they made that transfer:

Over half (54%) of transfers are for ‘bills’ and ‘groceries’; ‘fun’ and ‘holidays’ make up less than 10%.⁶

Users were also extremely consistent in how they categorised their transfers from one month to the next, although the early phase of the Covid-19 pandemic saw a notable increase in Groceries, and decreases in Expenses, Travel, Holidays and Fun. This is covered in more detail in the appendix.

How does a flexible pay cycle impact personal finances?

We can now delve more meaningfully into how personal finance behaviours and perceptions change, once a user is accessing pay flexibly. This is the ultimate question our industry should aim to answer. In particular, we’ll turn our attention to two specific areas of impact:

  • The financial products which currently benefit most from the locked pay cycle ‘liquidity trap’
  • Key inputs and outputs of financial resilience

a) Does EWA impact the use of credit products?

When we think about the impact of a flexible pay cycle through EWA, it’s important to correct one common misconception. EWA has, at times, been incorrectly referred to as replacing forms of lending—most notably ‘payday loans’, a form of high-cost credit which creates profit at the detriment of financially vulnerable segments of the population.

Instead, EWA replaces the locked (often monthly) pay cycle. It is also unproductive to equate these two, as research suggests individuals treat credit and their own income in fundamentally different ways; regulators in the United Kingdom and United States now state that flexible pay should be viewed as income, and not lending.

This reversion to a more flexible pay cycle can, however, lead to a number of changes in financial behaviour by the end-user. It has been a widely held belief that one of the most common changes would be reduced use of last-resort credit, since adoption for this had been inflated by those experiencing a lack of liquidity towards the end of a pay cycle, and a lack of access to affordable credit.

To test this, users were first asked about the sources of liquidity they most commonly used towards the end of a pay cycle, before enrolling with Wagestream.

After ‘borrowing from friends and family’ (30%), the most commonly used options they cited were overdrafts, credit cards and payday loans. Users were then asked to reflect on any change in their use of these products, after having flexible access to income; all users had enrolled with Wagestream three months prior to taking the survey.

Around a quarter (23%) of respondents say they use payday loans less, after enrolling with Wagestream. Since 74% of respondents had never used payday loans prior to this, the data suggests that ‘responsible EWA’ has reduced payday loan usage for 88% of those previously reliant on it as a source of liquidity.

Again, the results indicate a positive overall impact: 21% of respondents are using their credit card less often and 16% are resorting to an overdraft less often, since joining Wagestream. This equates to a 39% and 31% decrease in usage for those that previously relied on credit cards and overdrafts, respectively

While the results are positive, this should not be the final time impact on credit usage is studied. Future research should, firstly, track whether this trend is maintained long-term. It would also be beneficial to carry out more qualitative analysis, to better understand why a very small subset (3%) see increased credit usage—at least initially—after three months of adjusting to a flexible pay cycle.

a) Do users become more financially resilient?

Through this assessment, we also set out to test which other financial behaviours change when EWA is introduced, beyond an improvement in liquidity. To do so, we asked users to consider any change in behaviours that we consider to be core inputs and outputs of long-term financial resilience: budgeting, saving, a sense of control, and a sense of improved quality of life.

Survey responses suggest that users feel overwhelmingly positive about the impact that Wagestream has had on their lives across a range of financial resilience indicators.

These findings span a representative proportion of all Wagestream users, including those exclusively using features other than the EWA feature; it is noteworthy then, that users of the EWA feature actually reported more pronounced positive impact. A majority (55%) of respondents reported improvements to their ability to plan their finances, for instance, and almost a third (31%) felt it had become easier to save. However, these figures rose to 60% and 33% respectively, among EWA users.

Similarly, significant majorities of users felt more in control (72%) and a sense of improved quality of life (61%)—which rose to 78% and 72% specifically among users of the EWA feature. These are relatively small increments, and may be explained by the moment of relief EWA users often describe, when using the feature for the first time. However, future studies could benchmark these differences and use qualitative methods to explore the underlying reasons in more detail.

These results also appear to highlight why recent adoption of EWA has been so swift: the results cited by users outperform global benchmarks for financial inclusion services (72% improved quality of life vs. 37% global average; 56 Net Promoter Score vs. 42 global average), meaning EWA is playing a profoundly positive role in the delivery of fairer financial services.

In future research we aim to build on these findings by assessing whether users’ lives have improved in the ways they perceive, through open banking data. In the interim, this ‘perceived impact’ can serve as a helpful first step in understanding the effects of replacing extended, locked pay cycles with EWA.

References

  1. The average transfer amount for those making 7+ transfers per month is £36; it is £105 and £66 for those making 1-3, and 4-6 transfers respectively.
  2. Gross salary estimated by assuming standard UK income tax deductions. This may underestimate salary where there are non-standard deductions on payslips (e.g. student loan repayments), or where the user has more than one job.
  3. These metrics exclude any user enrolled less than 12 months ago, to ensure we are analysing the same set of users in month 0 as we are in month 12. For the same reason, we have excluded any user who left their employer within 12 months of their first EWA transfer.
  4. For reasons discussed previously the gross salary figures may underestimate the gross salary of some users, hence the percentages in this graph may be slightly higher than in reality.
  5. If an employee does not make a transfer, they are assumed to have made their first ‘transfer’ on their payday (i.e. 0 days until the end of the pay cycle).
  6. As with other data collected, it is likely this was affected by the Covid-19 pandemic; in future research, it will be possible to identify any notable change in transfer usage patterns.