| Category | Assignment | Subject | Programming |
|---|---|---|---|
| University | BPP Business School | Module Title | Programming For Data Analysts Summative-Answer |
This report dives into Zappy Financial Services' loan data to figure out how they can improve their loan approval process. With a recent surge in loan applications due to a digital marketing push, ZFS must streamline its data handling and decision-making. We looked at factors like gender, marital status, education, and credit history to see how they impact loan approvals.
Our findings show that credit history is a major player in whether someone gets approved for a loan. Interestingly, we also noticed that men and married individuals tend to have higher approval rates. This raises questions about fairness in the approval process, suggesting that ZFS should ensure everyone is evaluated equally.
To improve things, we recommend refining their risk assessment models by including more variables, like income stability and savings patterns. It’s also crucial for ZFS to regularly check for any biases in their algorithms. Lastly, creating tailored loan products for different demographics could help them meet the unique needs of their clients. Overall, these steps will help ZFS build a more inclusive and efficient loan approval system, ultimately attracting more customers and fostering loyalty.
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