Traditional credit scoring methods are proving insufficient in meeting the changing demands of today’s workforce. A recent study highlights a significant issue – gig workers in the UK are experiencing financial exclusion due to a disconnect in data accessibility between banks and lenders. 

Research conducted by Rollee indicates that 70% of gig workers in the UK encounter difficulties in obtaining approval for financial products. Among those surveyed, a staggering two-thirds (66%) have faced loan rejections despite demonstrating affordability, leading them to apply for an average of three credit cards or loans before finally securing approval. The implications extend to housing, with 34% losing the opportunity to secure a new home despite having financial means. The struggle for financial service access has resulted in 80% of gig workers feeling they lack equal financial service opportunities compared to traditional full-time workers, causing financial stress and prompting consideration of alternative employment options. 

The root cause of this financial exclusion lies in the limited transparency of income and employment data for gig workers compared to their PAYE counterparts. Financial institutions acknowledge the shortcomings of their current risk assessment processes, with 73% expressing an inability to obtain a comprehensive picture of a gig worker’s payments, income, and employment records. Consequently, 34% of financial institutions are more inclined to approve applications from PAYE workers, citing better visibility into their income and employment details. 

Addressing the data disconnect 

Independent workers contribute £20 billion to the UK economy annually, making them a vital and expanding workforce. Addressing these challenges is crucial for both financial inclusivity and enabling financial institutions to cater to a growing market.

Let’s imagine an example of a Senior Software Engineer switching from full-time employee to freelancer on a freelancer platform such as Upwork. This employee works only during the first and the last quarter of a year with a daily rate of £800, generating a yearly revenue of £96,000. We all agree that this would be enough to have a more than comfortable life in Europe. However, if you look at the employee’s banking transactions during the summer, you will see no income at all. A traditional credit scoring system as we know it would unfairly consider this a red flag. Unfortunately, this is exactly what is happening when financial institutions make a loan decision based on the regularity of a person’s income without considering the dynamics behind their activity.  

One’s skill set, the duration of a project, the quality of customers, or a workers’ demand are all alternative data points which are essential to building fair credit scoring rules for different categories of self-employed or freelance workers. We should not apply the same rules to an Uber Driver, an Etsy Sole trader or an Upwork Developer simply because they share a similar working status. 

To build fairer and transparent scoring rules, each worker category needs suitable scoring features which best represent their professional behaviours. 

The solution lies in closing the gap between the current limited data available for credit risk assessment and obtaining a complete view of a worker’s income, employment status, and activity records. A holistic view ensures that credit assessments consider not only financial transactions but also the capacity of gig workers to repay. 

Data transparency challenges 

However, attempts to leverage alternative data points often encounter challenges in data integration. Efforts to use data from freelance platforms and HR software through public APIs leads to obstacles and bottlenecks. Negotiations with platforms for access to private APIs can result in refusals, and scalability becomes a daunting challenge when integrating multiple platforms. This method demands significant investments in resources from backend, data, and DevOps teams, hindering data-driven decision-making and growth. The technological complexity of this approach further limits its effectiveness. 

Why marketers should be talking about code

While open banking has shown promise in secure data sharing, its focus on bank-based payment data remains a limitation. Financial institutions need seamless access to alternative data sources in real-time, achieved through automated connections to various income and employment platforms. Scaling up integration efforts across markets and regions through an external API infrastructure is essential. 

The adoption of automation in consolidating and standardising data not only eliminates time-consuming manual processes but also simplifies the complexities faced by internal tech teams. Moreover, it empowers gig workers by giving them control over their data, allowing them to share financial ownership without relinquishing control of the data itself. 

The final frontier of open finance 

Embracing this transformation requires substantial investments in data infrastructure and a fundamental willingness among financial institutions to evolve. Bridging the data disconnect is the last frontier for open finance, crucial for levelling the playing field for gig workers and recognising their contributions to the economy. 

Wildstone raises £350m to expand in Europe