Fintech Feature – fastPAYE
fastPAYE is a On Demand pay application that allows businesses to pay staff before payday. fastPAYE is not providing a loan, so there is no interest. Earned salary is drawn down early for a small transaction fee, but free for those on minimum wage.
We spoke to Ian Hogg, CEO of fastPAYE, to find out more about this exciting workforce management FinTech.
How would you describe fastPAYE?
fastPAYE is helping companies to improve the financial well-being of their workforce, and at the same time removing some of the cumbersome and manual processes that businesses go through to pay the correct wages.
Imagine you are working in a coffee shop. You are 15 days into the month. You have worked 80 hours and clocked up £800 worth of salary. Your manager has signed off on your hours and you can see all of this in your fastPAYE app.
It is near the end of the month and you need a little extra cash to tie you over. You go into the fastPAYE app and in 30 seconds the money that you needed is in your account. Your employer has set the rules, allowing you to withdraw up to £100 of your salary before payday. It saves you asking mum or dad, your boss, or getting an expensive payday loan.
Is the employee charged for the salary withdrawal?
For people on minimum wage it is always free. Those earning more will pay a small transaction fee, or the employer will pick up the bill.
If the employer is not picking up the bill and the employee wants £100 early they will be deducted £101 from their salary. With many employers seeing the benefits from improved financial well-being they are mostly picking up the bill. The advance of pay is coming directly from the employer’s bank account.
The power is in the hands of the employer. They get to choose if an alert goes out to the employees when the service is open, they choose when the service is open, whether to charge the employee for the service, and how much is available. fastPAYE never promotes directly to the employee.
The insight helps employers minimise churn. For example, it may prompt a conversation if the employer can see that someone uses the service every month up to their maximum – this could well be a sign of an underlying issue that the employer is now empowered to support.
What does the fastPAYE product roadmap look like, have you considered any partnerships or integrations with other PFM solutions?
Our AI team is in Scotland and we do have plans for wider integrations, but we are still amassing data and are focusing on making our core business as solid as it can be.
The roadmap is focussed on features that will support employee well-being and those that allow us to offer the ultimate flexibility with the service.
We have recently launched a benefits calculator to allow employees to check their entitlement to benefits before taking an advance, and we are offering ways to earn extra salary – such as overtime – which can be accessed immediately to prevent the advance coming from basic pay. We are also looking at a savings offering and ways of building credit scores. Our long-term goal is that the request for an advance of pay is a trigger to offer other services so that an advance of pay is no longer, or very rarely, needed.
We still need to see advances in banking infrastructure to fully deliver our roadmap. For example, by leveraging Open Banking we want to be able to go into any bank account, verify and authenticate, and send the salary advance on to an employee account with any bank. We would like to see a disruption of the Direct Debit process, as this remains one of the key challenges to fully disrupting the payroll process, but that is not something for our roadmap at this stage.
Have you seen a difference in demand from companies with high paid salaried employees versus companies with employees that are paid by the hour?
Not really. We have tested fastPAYE in companies with highly paid salaried workers and it has been popular. What fastPAYE has uncovered for employers is where an employee uses the service every month because they have got into a bit of financial trouble. The employer can then have a conversation with the employee to understand if it is something that they can support with.
Providing a small loan to help an employee through a difficult time is something most employers would favour over losing a good person and finding a replacement when it could have easily been avoided.
Do you see the way that the tech could help make that employer-to-employee conversation easier?
We have released an AI powered feature that can predict how likely a person is to leave. It generates a percentage-based prediction for every staff member’s likelihood to leave in the next 30 days by monitoring data points such as sickness, lateness and other behavioural patterns to flag up those at high risk of leaving.
We have to be careful of the sensitivity of this data to ensure it is GDPR compliant, and we want to ensure that there is enough data of sufficient quality that we can be confident that the insights do not include any bias. We have recently finished the research into how we can use this data both in a legally compliant and fair way.
The AI doesn’t make any decisions, it just provides additional insight to the employer to help them have better conversations with some of their employees. We are due to go live with our first beta customer in March and will be looking to measure the impact that fastPAYE has on retention.
What has been your approach to the technology powering the FastPAYE platform?
Our approach to fastPAYE’s technology has been automation and simplicity. That means it is fully integrated into HR, time and attendance, and payroll platforms. Clients rarely touch the back-end once it is configured, they mainly use their dashboard to control everything. The user interface that the employee logs into is a simple app that says how much money they can take now – the demo takes 10 seconds because the UI is that simple, the way it should be.
We take financial responsibility very seriously though. We have an ethics board that approves any major feature release and anything with AI.
When it comes to the data we are sitting on we value long term responsibility over short term commercial gains. For instance, we would never promote loans to people in short term difficulty; instead we would refer them to debt advisors or give the employer the tools to intervene. The industry is full of businesses that had good ideas, but did not place great enough weight on their responsibility of doing things ethically. We plan to add value without compromising on ethics.
Where do you see this going?
The economy is geared towards a monthly payroll cycle and that will not change soon. There are many factors that have led to that, and strong forces keeping it that way. Companies have been keen to minimise the administrative burden. Rent, utility bills, car payments, gym memberships; most bills are monthly. Most of the western world is geared towards a monthly payroll but technology is removing some of the blockers that may allow this to change.
In our experience companies do not care if the money is paid slowly over the month or in a chunk at the end, provided the administration is automated. Progress in the payments industry is making this feasible because the transaction costs of large bulk payments versus many micro payments is changing.
Almost every adult in the UK has 5 direct debits and standing orders. It is quite a cheap process, but it takes 2 days. fastPAYE’s process can do this instantly. Our current version of fastPAYE is a use case where we can solve 80% of the financial wellbeing problem with 20% of the cost. This is the way we see it going once Open Banking has its “Uber” moment.
Final thoughts:
fastPaye’s value proposition is clear. It helps employers to get more control over workforce management and it gives employees more flexibility with their earnings.
The solution plays directly on the link between financial stress, employee wellbeing and employee effectiveness.
Research has shown that employers will get a return of £5 for every £1 spent on employee mental wellbeing. Given that financial stress is the biggest contributor to mental health issues, the fastPAYE solution could create a direct return for both employers and employees.
This novel use of AI will only become more powerful over time. As the availability of data increases, the insights that fastPAYE can provide will help employers get the most out of their employees, focusing more and more on the human element of the process.
Linking solutions like fastPaye, that manage money coming in, with PFM solutions that manage money going out, has the potential to take financial well-being to a whole new level. It will be interesting to watch how this ecosystem evolves with more partnerships and integrations between the different solutions.
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