Fraud Detect AI: A High-Impact Finance Student Project

Introduction: High-Impact Finance Student Project

AI in finance often feels distant reserved for banks, hedge funds, and experts. But what happens when a student steps into that world and asks, “Can I build something that genuinely protects people?”

This is the journey of Merwan Santosh Indukuri, who set out to build Fraud Detect AI, a project that blends financial reasoning with machine learning to confront one of the biggest risks in modern digital payments.

About the Student

Merwan’s interest in finance has always stemmed from understanding how money moves and how systems maintain trust at scale. But he didn’t just want to study markets he wanted to understand the hidden vulnerabilities beneath them.

Choosing fraud detection wasn’t accidental. He recognized that the digital financial world is growing faster than its safeguards. With a developing passion for data science, he wanted to challenge himself with a problem that combines pattern analysis, human behavior, and financial risk. His motivation was simple: “If fraudulent transactions can harm millions, learning how to stop them is a meaningful place to start.”

About the Project

Fraud detection is one of the most complex and essential applications of AI in finance. Every transaction carries subtle signals some normal, some suspicious. The challenge is distinguishing between them before the damage is done.

Merwan’s Fraud Detect AI takes structured transaction data and learns to identify unusual patterns. By comparing legitimate spending behaviors with anomalies, his model assigns a risk score that can help detect potentially fraudulent activity.

Explore How AI in Finance is a Great Passion Project Idea

How the Student Built It

Merwan worked through our structured, mentorship-driven process where each week pushed his understanding a little deeper. He began by studying financial fraud cases and learning how institutions model risk. Instead of diving straight into coding, he first mapped the problem like a real analyst.

Challenges came quickly: highly imbalanced datasets, noisy features, and model predictions that initially fluctuated wildly. With guidance, he learned techniques to handle uneven data and refine his evaluation strategy. His breakthrough moment arrived when he realized that improving accuracy wasn’t about adding complexity—it was about understanding the story the data was trying to tell.

Along the way, he strengthened soft skills essential for finance and data science: strong documentation, analytical clarity, and step-by-step iteration.

Student Impact & Outcomes

This project didn’t just give Merwan a model it gave him an authentic entry point into finance and data science. He learned how AI tools are used to protect consumers, maintain trust, and manage financial risk.

For competitive program applications and future university admissions, Fraud Detect AI stands out as a serious, real-world project. It demonstrates technical maturity, ethical awareness, and the ability to work through complex datasets qualities selective colleges actively look for.

It also strengthens his long-term path in finance, data science, and applied analytics, giving him a strong foundation for future internships, research, and advanced coursework.

Testimonial Section

“This project showed me how much responsibility comes with building AI in finance. Detecting fraud isn’t just a technical challenge it’s a trust challenge, and that made the work feel real.” — Merwan

FAQ

1. Why is fraud detection a strong student AI project?

It mirrors real industry challenges and teaches students how financial institutions use machine learning to protect consumers. Colleges value its relevance and impact.

2. How does mentorship improve learning in AI projects?

Guided mentorship helps students avoid common mistakes, understand the math behind models, and build industry-style workflows instead of quick prototypes.

3. Does a project like this help with college applications?

Yes. It demonstrates domain knowledge, data literacy, and the ability to complete a complex, socially meaningful project traits admissions officers respect.

4. What skills does a student gain from building Fraud Detect AI?

Students strengthen analytical thinking, risk modeling, data preprocessing, and ethical decision-making core skills for finance and data science pathways.

Conclusion

Merwan’s journey shows how impactful AI education becomes when it meets mentorship and real-world responsibility. Fraud detection isn’t just a project it’s preparation for the kind of thinking top universities and industries expect.

To explore more student journeys, visit bettermindlabs.org.