If you have ever tried to purchase a home, buy a car, or apply for a credit card, chances are you might have heard of the FICO credit score. The FICO score may seem to be a formidable opponent: it serves as the dividing wall between a consumer and any major purchases and life decisions. Having a good FICO score can help you achieve your life goals, and get finance for all your major purchases! Unfortunately, having a poor FICO score can have the opposite effect. A low FICO score can send a car loan, mortgage application, or credit card application back to you: rejected.
At this point, you’re probably wondering: what does this FICO score mean? Why was it created, and what does it mean in simple English? Luckily, the answer to these questions is simple. The purpose of the FICO score is to predict your credit risk as a borrower. In its simplest form, the purpose of the score is to predict whether or not a consumer will be a 90 day late payer within the next 24 months.
So how on earth does the FICO Score make this prediction? There is one company who dictates the process behind these predictions. This company is, not surprisingly, named FICO. This company creates a mathematical equation, known as an algorithm, which produces the score. This algorithm uses real data from people who have had late payments to see what ‘late payers’ have in common. The company, FICO, will go out and buy credit reports from the 3 major credit bureaus: Trans Union, Experian, & Equifax. FICO will buy 2 million credit reports from each bureau. Then, the company will then wait for 2 years and update those same 2 million credit reports. Finally, the computer analyzes the reports to see what those consumers who went 90 days past due had in common, and create the FICO algorithm.
In the interest of keeping the FICO score as accurate as possible, FICO (the company) is making a major change for its next update cycle. Instead of using the standard 2 million reports, as described above, FICO has decided to increase the number of reports that it pulls biannually. In fact, they have increased that number to a shocking 7.5 million! This will increase the sample size of ‘late payment’ consumers, and is intended to make the algorithm more accurate. Only time will tell how this may change the field of consumer FICO scores.