Credit Check

Project Overview

Alternative Credit Scoring Model was developed during the inaugural Deutsche Bank Early Career Hackathon. I was placed on a team with three other students and challenged to create an innovative approach to rethinking how credit scores are calculated. We had just 7 hours to brainstorm, prototype, and present our solution.

The project initially began using VueJS and NodeJS for frontend and backend development, respectively. However, due to unexpected hosting constraints, we transitioned the frontend to AngularJS to meet the final submission requirements within the time limit.

Key Features:

• Student-Focused Credit Evaluation: Our model was designed with students in mind—an often overlooked demographic in traditional credit scoring systems.
• Expanded Scoring Metrics: Rather than relying solely on financial history, we considered a range of academic and socioeconomic factors:
  • GPA: Higher GPA scores positively influence credit evaluation, signaling responsibility and performance.
  • Graduation Year: Students closer to graduation are considered more likely to gain stable employment soon.
  • College Major: Certain disciplines with higher employment rates receive favorable scoring.
  • Work History: Prior part-time jobs, internships, or co-op experiences improve scores by showing early financial engagement.
  • Parental Income: A proxy for potential financial backing, parental income was factored in to account for support systems that could influence repayment likelihood.

Innovative Thinking:

The project pushed boundaries by incorporating behavioral and contextual data into credit evaluation. A traditional model might assign equal scores to two users who take out a $1,000 loan, regardless of personal financial behavior. However, we discussed future enhancements that consider psychological prioritization of repayment. For example:

• A user earning $50,000 annually who delays repayment may indicate low financial responsibility, resulting in a lower score.
• Conversely, a user earning $2,000 who prioritizes repayment demonstrates a high degree of responsibility and should receive a higher score.

Technologies Used:

• AngularJS: Used for the final user interface after pivoting from VueJS due to deployment limitations.
• NodeJS: Powered the backend API to process user input and simulate score calculation logic.
• JavaScript & REST: Enabled real-time interaction between frontend inputs and backend logic.

Conclusion:

The Alternative Credit Scoring Model reimagines financial evaluation through the lens of potential, behavior, and background—not just past transactions. By targeting student users and emphasizing holistic metrics, the project opens up credit opportunity to a group often underrepresented by traditional scoring systems.

Future development could deepen the behavioral aspect of credit evaluation, using machine learning or behavioral economics to build profiles that more accurately reflect financial reliability beyond raw income or debt history.