By Magnolia Potter
The availability of large quantities of consumer data, also known as big data, has broad implications for the way we measure credit. No longer will consumers be tied to traditional banking for building credit. Now, all kinds of metrics can help prove credit worthiness.
These changes mean credit is more accessible than ever, democratized to meet the needs of all kinds of demographics. But how is big data making this accessibility possible?
With the power of big data, the credit-score landscape is losing some of its barriers for consumers who are seeking to earn and improve their credit. Here’s what you should know.
The Role of Big Data in Credit Scores
Historically, credit scores have been a compilation of the same five factors generated through traditional financial institutions. These factors measured use and availability of credit in the only comprehensive way previously possible. But the modern era brings with it technical innovations.
Now, your credit score isn’t necessarily limited to these five factors:
- Loan and credit applications
- On-time payments
- Types of credit used
- Credit history
- Credit capacity usage
With the power of big data, the three major credit bureaus (Equifax, TransUnion, and Experian) have put together a new method of establishing eligibility. The new system, called VantageScore, works as a competitor to the traditional FICO rating. With it, big data can now help you rebuild and establish credit in more comprehensive, big-picture ways than ever before.
For example, VantageScore looks at all kinds of established credit patterns. Perhaps previously a high credit capacity usage rate (or debt-to-income ratio) meant getting denied additional opportunities. VantageScore goes beyond that and can determine if there has been a clear pattern of repayment and surrounding good behaviors, utilizing data from all kinds of sources.
Ultimately, this opens up credit to all demographics as big data looks to replace traditional credit scores.
The new big-data-powered credit system means substantial changes for all kinds of people, potentially easing credit-building restrictions like needing access to traditional credit cards and financial institutions. With big data, the 2.5 billion people in the world without such access now have a chance to be seen for more than just a set of numbers.
These new credit-risk models look at factors like the following in order to gauge eligibility:
- Mobile phone usage patterns
- Utility bill payment history
- Identity verifications for fraud reduction
- Ability to repay
- Willingness to repay based on consumer history
These factors and more can give financial institutions a picture of someone’s credit responsibility without necessarily needing a set FICO score. As a result, many options are opened up for proving eligibility and building credit.
In the past, consumers had to rely solely on paying down debts and making payments on time. Often, the only way to achieve this was to enter a field like teaching and engage in a student loan forgiveness program. Clearly, however, such credit-building options are not possible for everyone. That’s where a big data-based system comes in handy.
The changes coming to big data and credit scores mean more people than ever before have a shot at opportunities previously reserved for a select few. As long as the data and AI models are built to further reject biases of the past, such a system can serve as a democratizing and life-changing model of credit for consumers all over the world.
People’s opportunities should not be limited to a single number. Big data use in credit analysis allows for a larger picture of a person and the empathy that comes with it.