I’m currently an AI Analyst at FinTech Solutions, where I deal with diverse projects that utilize AI tools and predictive models for financial forecasting. One notable assignment was the development of a risk assessment model for credit card approvals.
We adopted a machine learning approach for this task, employing a Random Forest algorithm. The tool was built using Python, with Pandas for data manipulation and scikit-learn for implementing the ML algorithms. To enhance model accuracy, we ensured comprehensive data preprocessing and implemented techniques like cross-validation and hyperparameter tuning.
The predictive model we developed was successful in assisting the credit department in making informed decisions and minimizing the risk of bad debts. It reduced manual error and bias, increasing efficiency and accuracy of credit card approvals.