Florida High School Student Creates App That Outsmarts Credit Score Algorithms

For some students, pursuing scholarships takes up their evenings. However, one Fort Lauderdale student dedicated his time to perfecting a simulation that subtly alters our perception of financial identity. That project is a prototype app dubbed “FairWorth,” which is yet unofficially named but is colloquially known as such. Its purpose is to explain and simulate how certain financial actions could affect your credit score before you make them.

The tool, which was created by a 17-year-old senior in high school, doesn’t change or access anyone’s real score. Rather, it generates scenarios using publicly accessible FICO modeling criteria and aggregated data. It poses the following queries: What would happen if you paid off a high-interest credit card first? Should you pay off debt or raise your credit limit? What happens if you open a secured card and don’t use it more than 10%? Every input results in a customized simulation, which is quite similar to a financial GPS in that it silently recalculates your journey depending on the choices you make.

Through the use of publicly available scoring models and case study behavior patterns, the app provides computationally inexpensive simulations that are especially helpful for users who are unfamiliar with the credit system, such as young adults, recent immigrants, or people with little credit history. It doesn’t raise your score. It explains scores.

The student demonstrated the tool last fall at a regional youth entrepreneurship forum in Tampa using a fictitious profile of a 22-year-old freelancer with three open accounts and inconsistent income. The audience observed while the software demonstrated several possible actions, such as avoiding a store-branded credit line, moving the repayment sequence amongst cards, and postponing a car loan application by six months. With clear, understandable language such as “Maintains a steady upward trend” or “Risk of short-term score dip due to new inquiry,” each option produced a projection.

A financial counselor in the audience gave a grateful nod. The explanation was incredibly clear—not cluttered with technical terms, but supported by sound reasoning.

Many people, particularly teenagers starting adulthood, find credit scoring to be a mystery with rules that appear capricious and merciless. FairWorth makes an effort to shed light by providing justification in addition to results. Its engine integrates weights based on how lenders often react to credit behaviors and uses conditional branching, which is comparable to decision trees. You can understand the underlying reasoning if you’ve ever played a strategy game where every move changes the course of events.

The app’s initial versions were linear and even awkward, but once a mentor recommended switching to a matrix-style simulation, it significantly improved. Response lag was greatly decreased by that one modification, which also improved the results’ readability. The program has started to produce patterns by modeling more than 3,000 credit scenarios; some of these patterns support conventional wisdom, while others highlight discrepancies in what are thought to be “safe” behaviors.

The student mentioned something that stuck with me during a quiet Zoom conversation: “Most people don’t make bad choices on purpose.” They simply lack a sandbox in which to test them beforehand. For someone who hasn’t even applied for his first credit card yet, I thought that was incredibly smart.

Seeing his older sister struggle to get an apartment lease after graduation served as his own inspiration. She simply hadn’t made enough bad financial choices, not that she had made any. No past-due payments, but no discernible credit history either. He found the system of silent penalties bothersome.

Two Florida fintech accelerators are currently reviewing the app, and they are both interested in its potential to serve as a simulation tool rather than a service provider. It’s important to note that FairWorth does not take the place of credit bureaus or facilitate loans. Rather, it functions as an instructional manual—similar to a financial flight simulator for customers traversing uncharted territory.

The student intends to start limited beta testing through South Florida community centers and charities that promote financial literacy through targeted mentorships. If everything goes according to plan, seniors in high school might be investigating credit scenarios before to graduation—something that is much needed but rarely taught. Knowing “why it matters” as well as “what to do” could be immensely powerful for early-stage adults.

Another way that FairWorth distinguishes itself is by refusing to gather personally identifiable information. Sessions are not saved, and inputs are anonymised. That dedication to privacy was not only considerate; it was also a very solid basis for confidence. This would probably put the initiative in a good position for future collaborations with credit unions or educational institutions, according to a number of consultants.

FairWorth sat next to more expensive and larger apps at the recent Miami Dade College AI exhibition. But the commotion around it persisted for a longer time. Maybe because, in contrast to test-prep tutors or calorie monitors, this gadget appeals to something more subdued and universal: the need to be understood by a system that seldom explains itself.

A formal release date has not yet been set. Sleep, AP tests, and college applications still cause problems. However, the goal is powerful. The student is bridging the gap between human decision-making and opaque algorithms, not attempting to go viral. If this experiment is successful, credit scoring—which has long been seen as inflexible—may finally begin to resemble something that is more understandable, attainable, and possibly even equitable in the months to come.