Using Alternative Data to Credit Score Millennials

May 7, 2021

At first glance, the financial profiles of millennials may seem incomplete or complex to banks and financial institutions. Young people in their 20s and 30s are sometimes affected by the lack of credit history and disabled to meet their goals of buying a home, car, obtaining credit or making an investment. On many occasions their loan applications are rejected or are imposed high interest rates that prevent them from obtaining profitable loans.


In any case, the lack of a traditional credit history does not mean that these young people are unreliable or not eligible for credit. On the contrary, many of them are the ideal clients that financial institutions need.


The relationship between millennials and banks


Millennials move in a 100% online world. Unlike their parents, their first contact and interaction with banks and money flows is completely digital. This is a key factor when generating online credit scores. Thanks to the use of alternative data with artificial intelligence, it is possible to obtain all the necessary information in order to evaluate and analyze this new generation and distinguish potential clients with a low credit risk.


Faced with the great demand in the banking market, millennials often opt for fintech startups that meet their credit expectations.  These new companies have a closer relationship with young people, adapting to their needs in the entire evaluation processes: from their credit assessment to the way in which they communicate. As well, they use alternative data and score apps to carry out the evaluations, which makes it more likely to grant loans to millennials that do not have a traditional credit history.


In Latin America 30% of the population is millennial, so financial companies have quickly had to adapt to the new demand. At the same time, more and more new digital banking companies have incorporated young people into their client portfolio. Thanks to their power of flexibility and the incorporation of an alternative scoring method with artificial intelligence, they can offer credits adapted to their needs.


The benefit of onboarding Millennials


The incorporation of millennials into the financial circuit is extremely beneficial, since it reduces costs for companies and increases the effectiveness of payment behaviors. The use of alternative data allows banks to obtain accurate information and more accurately predict the behavior of young people, thus reducing credit risk.


Millennials live in immediacy, so fintechs have quickly adapted to their demand, granting loans digitally and with fewer bureaucratic obstacles. The use of alternative data with artificial intelligence has allowed institutions to obtain updated insights in real time, capturing the attention of millennials and boosting the market.



Most used alternative data sources by millennials


Mobile applications are the most important sources of alternative data that allow companies to have a deeper comprehension about this segment of the population. Among them, digital payments stand out, prevailing those that operate 100% digital, such as Venmo - a digital payment application belonging to PayPal-, Apple Pay and digital wallets.


Job search engines, such as LinkedIn and Facebook, are also a great source of alternative data, which allow banks to obtain reliable information on employment history.


At the same time, other alternative data sources that help to generate credit scoring for millennials are emails, social networks, satellites and geolocation.





Today it is essential to stop and observe the behavior of the younger generations. Their habits are highly changeable and companies must have the power of flexibility to adapt to their new demands. In addition, it is essential to be able to generate financial inclusion that benefits both young people and banking companies.


The percentage of millennials in the world is on the rise and knowing them is a guarantee of growth and economic development. Alternative data sources with artificial intelligence are undoubtedly a key point to reduce credit risk.


Having a correct understanding of millennials and generating an accurate credit score is essential in order to build a profitable relationship between society and the economic circuit. Credit models help predict the behaviour patterns of millennials by evaluating them, improving effectiveness and reducing costs. It is a guarantee of social growth and a healthy economy.