Chennai, India /
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Financial Risk Prediction Engine

Project
Intelligent Loan Default Risk Prediction
Focus
Predictive modeling
Platform
Random Forest / FastAPI
Status
Independent project
Financial Risk prediction dashboard

Actual supplied application running locally with its built-in synthetic customer examples and a temporary SQLite preview database.

(Overview)

An end-to-end machine-learning application for estimating borrower loan-default risk.

Borrower information and repayment-related features need a consistent path from data preparation to a usable risk estimate.

Technologies
  • Random Forest
  • FastAPI
  • Next.js
  • MySQL

(The build)

Intelligent Loan Default Risk Prediction

The supplied project description combines a Random Forest classifier, a FastAPI model-serving layer, a Next.js interface and MySQL storage.

Financial Risk feature importance and prediction form
Local demo prediction and model feature-importance interface; no production customer data.

(Engineering details)

04
01

Random Forest classification

02

FastAPI model-serving workflow

03

Frontend integration

04

Relational data storage

(Architecture)

  1. 01

    Borrower information

  2. 02

    Risk classifier

  3. 03

    FastAPI serving

  4. 04

    Next.js interface

  5. 05

    MySQL storage

(Evidence & context)

The supplied implementation supports a complete local prediction workflow. The resume-reported accuracy figure remains separate from the synthetic demonstration shown here.

The supplied source repository is hosted by aryan-astra. Screenshots use its built-in synthetic examples, a locally trained model and a temporary SQLite preview database; the application is designed for MySQL.

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