By Ali Hamriti, CEO and Co-Founder at Rollee
Independent workers are a swiftly growing group of employees who contribute a substantial £20bn to the UK economy each year.
With ongoing economic uncertainty amid the current cost-of-living crisis, we have witnessed financial pressures escalate for many people, 5.2 million of which have since taken on extra jobs.
For gig workers who are a part of this new way of working, they will generate varied streams of incomes which comes with several benefits. For one, workers are able to achieve more financial security than they would in a single job. Being made redundant or experiencing burnout can affect any of us, but with several jobs on the roster, the option to fall back on a different venture is a mitigating factor. What’s more, the freedom to focus on the line of work which financially or emotionally fulfils you, is viable.
Despite the benefits which accompany working in a gig economy, many workers struggle when it comes to accessing financial services and products such as mortgages and loans. Rollee’s Hidden Cost of Gig Worker Living report found that 7 in 10 UK gig workers have been denied access to basic financial products such as a loan, despite having a good credit score.
On top of that, the survey revealed that 57% of 1000 gig workers have had to apply to three different lenders before receiving access to a credit card or loan. Unfortunately, 52% of gig workers have missed out on the purchase of a home due to being declined by a bank or building society, even though they have the affordability to be approved.
The Problem at Hand
The struggle that these workers experience is not a result of a lack of funds to secure a loan or mortgage, but because the current credit scoring system is not set up to understand and recognise these new ways of working. Having a single source of income and a work history of being at the same company for many years is what financial institutions identify as ‘good’ applicants. These records can be easily assessed to understand workers’ income and their ability to pay back a loan. Therefore, the workers who don’t follow these traditional paths are by default considered a higher risk.
Let’s take the example of a Senior Software Engineer switching from full-time employee to freelancer on a freelancer platform such as Malt. Working only during the first and the last quarter of a year with a daily rate of 800 euros can generate a yearly revenue of 96K euros. We all agree that it’s enough to have a (pretty) comfortable life in Europe. However, if you look at her banking transactions during the summer, you will see… no income at all. Making a loan decision based on the regularity of a gig worker’s income without considering the dynamics behind their activity will inevitably lead to biased decisions.
It is imperative that this is addressed so that gig workers can be given a fair assessment of their finances, particularly as this population of workers grows. It really is in the best interest of financial providers to ensure that their services are inclusive to all eligible customers, even if their income flow is not deemed ‘stable’.
Financial providers need to navigate secure ways to gain full visibility of independent workers employment data. But the current manual verification operations used are time consuming and inefficient. Workers are unfairly left to prove their solvency to financial institutions because the financial institutions are unable to successfully track down different income data records which are separated and dispersed in various places. In other cases, financial institutions do not have the time to manually track down all sets of data, which results in gig workers being denied access to financial services and valuable business being lost in the process.
However, financial institutions are conscious of the problem and know that new systems are needed – there is potential for change.
Automation is the Answer
To build fairer scoring models that work for all kinds of workers, financial institutions need access to alternative data points which reflect the solvency of all different categories of self-employed workers. We shouldn’t apply the same rules to an Uber Driver, an Etsy trader or a Malt Developer simply because they share a similar working status. Therefore, it is vital that financial institutions have direct visibility of the workers income and employment data so they can gain a better understanding of each applicant’s financial situation.
For financial institutions to evolve their offerings in a fruitful way, a fully digitised, automated process is required. Once implemented, providers can gain full visibility and transparency of multiple, diverse and dispersed data sets in real-time. Data automation plays a key role in consolidating and standardising the data so that time-consuming manual processes can be left behind. Automation saves time, money and helps to speed-up the decision-making process.
With automated access to alternative data points which reflect the solvency of all different categories of self-employed workers, financial institutions can achieve fairer scoring models.
Having a single and central monitored system to analyse employee data in also ensures that greater transparency is achievable whilst eliminating the risk of fraudulent activity or the tampering of data.
Another bonus that comes with adopting a digitised system is the shift of power in favour of independent workers. For the first time, independent workers are empowered as the owners of their employment data. Workers can decide how they would like to grant permissions to access their financial data, all without completely parting with the data itself.
It is unfortunate that new ways of working are not currently considered within credit scoring however, with support from The Financial Conduct Authority (FCA), the current rules that financial institutions are required to follow should be revised to make credit score calculations a fairer assessment for independent workers.
A Future of Trust
Financial institutions are aware of the necessity to adapt their scoring rules to suit independent gig workers. If they find a way to gain access to a worker’s granular professional data like income and activity, the doors open to a diverse set of modern workers.
After all, independent workers are representative of a growing population of us who choose to value and practice flexible working. Doing business in confidence with a growing market which represents the workers of today is something to be proud of.
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