If you have ever moved to a new country, started your first job after school, or decided to take an entrepreneurial route and become self-employed, then it is likely that you have been penalized by existing credit-score providers like Equifax and Experian when seeking access to financial products. In industry lingo, you have been labeled as a “thin file.”
That simple categorization carriers significant implications: You could not qualify for a credit card, you might not be able to get a cell phone or you are highly unlikely to be able to apply for a mortgage. In other words, you are pushed out to the fringe of the modern financial system simply because an API call returned a null value.
Many members of the White Star Capital team have been immigrants to new countries and entrepreneurs, and we have all been labeled in this manner. Technically, given I am the co-founder of a new company, and despite having lived in the UK for close to 11 years, I am still considered “thin file” when applying for a new American Express (despite already having one!).
We at White Star Capital hold a strong belief that the vast amounts of open and proprietary data sources combined with advanced analytical methods can help create insights and value across a multitude of verticals, and in the financial world this also applies to the ability to better measure and determine financial risk at at the atomic level of each and every individual consumer, rather than at a fictitious aggregated pool that gets grouped into a life-impacting FICO score bucket.
The macro-trends in the economy support the fact that credit scoring algorithms have to be modernized:
Self-employment continues to grow and in the UK it now represents 15% of the workforce.
The “gig-economy” will only help accelerate this across the world.
Secondly, as the middle class continues to rise in emerging markets, countries like Brazil or India, lenders will have to make creditworthiness assumptions with a much more limited historical data set and the opportunity is therefore vast for a new model of credit scoring.
Thirdly, as new financial products, such as peer-to-peer lending and two-sided marketplaces proliferate, new definitions of “risk” need to be defined.
It is, therefore, because of both the large opportunity and our own experience with this pain-point, that we gained the conviction to lead Aire’sSeed round earlier this year. Aneesh and his team are using machine learning algorithms combined with behavioral science to asses the creditworthiness and risk profile of credit applicants currently penalized by incumbent credit scoring models.
Today is an important milestone for Aire as they announce that they have received authorization from the UK’s Financial Conduct Authority to become only the fourth authorized Credit Reference Provider in the nation (and the first one founded since 2000!). The FCA, in its mandate to benefit consumes through increased competition, has highlighted Aire as an innovator in the space. As their Director of Strategy & Competition stated:
The $2 million seed round and the FCA authorization are two significant milestones for Aire, but the real impact of their work will come from millions of individuals across the world who will now be embraced into the financial system thanks to the algorithms being built by Aire out of East London, and we are thrilled to be part of the voyage to take on the opportunity.