Credit scores 'don't show full picture', Rollee CEO says

Credit scores don't take into account the full picture of a worker's situation, particularly within the gig economy, according to the CEO of Rollee

Inclusive credit scoring starts with integrated data that takes into account the full picture of an individual’s dispersed set of income and employment records, according to Ali Hamriti, CEO and Co-Founder of employment data platform Rollee.

This is because, in the current market, there is a combination of both conventional workers and gig workers who have different streams of income.

The findings of Rollee’s The Hidden Cost of Gig Worker Living report reveals that 7 in 10 UK gig workers have been denied access to basic financial products such as a loan, despite having and maintaining a good credit score.

Gig workers often misunderstood by FIs

Hamriti tells FinTech Magazine that “the challenge faced by these independent workers does not stem from their inability to afford a loan or mortgage, but rather, because the current credit scoring system is ill-equipped to understand and recognise these new and emerging ways of working”.

“Financial institutions typically favour applicants who have a singular source of income in a long-term career,” he adds. “These records signify as a sign of stability and can be easily assessed to understand workers' income and their ability to pay back a loan. Workers who don't follow these traditional paths are considered by default as someone with a higher risk.”

Instead, it’s time the finance industry built a fairer and more transparent scoring system that takes into account the variations between workers.

Hamriti has three specific recommendations for improving upon the current system. Here they are in full in his own words:

Evaluating risk manually

“There are financial institutions who continue to rely on manual methods to conduct credit risk assessments. With the varied nature of salary records of independent workers across multiple platforms, these institutions struggle to retrieve, consolidate and verify the data that is required, manually and still in a timely manner. This not only means that these businesses will suffer losses due to inefficiencies in the process, but it also means gig workers continue to face barriers to accessing financial services.”

Potholes of data integration

“Other financial institutions acknowledge the importance of leveraging alternative income and employment data through integration with freelance platforms and HR software through APIs. However, this approach of building integrations in-house can be met by roadblocks and bottlenecks. It requires companies to negotiate directly with platforms to gain direct access to a private API which can sometimes result in refusals. Also, with the need to integrate several new platforms, scalability becomes an even bigger challenge. It also requires an investment of resources from the backend, data and DevOps teams all in an effort to drive data-driven decisions to support growth. However, this approach is limited up to a point due to technological complexity.”

Scaling up integration

“In order to develop inclusive scoring models that will cater to all kinds of independent workers, financial institutions require fast and frictionless access to alternative data points that accurately reflect the solvency of self-employed individuals. Integration with an external API infrastructure enables automated connections to numerous income and employment platforms, allowing for scalable data connectivity across markets and regions. When automation is taken advantage of to consolidate and standardise the data, time-consuming manual processes and the complexity of internal tech team efforts can be left in the past. It also empowers independent workers by granting them control over their own data and allowing them to share financial ownership without giving up ownership of the data itself.

“Financial institutions know it is a necessity to adapt scoring rules for today’s market of diversified workers. By gaining swift and scalable access to granular professional data, such as income and activity, their services will become inclusive to all kinds of workers. They’ll also be able to do business in confidence with a growing market which represents the workers of today and the future.”

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