Credit Risk with Precision

Introduction

Client is a fast-growing business based out of Philippines

Background

An outdated lending system, which over relied on humans in providing lending decisions.

Problem Statement
  • Outdated Technology and manual risk prediction.
  • Limited Data Accessibility.
  • Rule based risk prediction.
  • Inflexible and time consuming to change risk predictions and to check credit worthiness.
  • Increased operational risks.
Solution

CodeBoard Tech solution provided flexible integration with the legacy system with a new AI based risk and automation module. Our solution is designed to streamline and enhance the credit risk assessment process, enabling our customer to make more accurate and informed lending decisions. Our AI algorithms automated the analysis of vast amounts of data, including financial statements, credit histories, and market trends. Sophisticated machine learning models to develop customized risk scoring models. These models considered multiple variables and provided a comprehensive evaluation of creditworthiness.

Benefits
  • Automated Credit Risk Analysis
    • Enabled faster and more accurate credit risk assessments, reducing manual effort, and improving efficiency.
  • Improved Accuracy

    • Enhanced the accuracy of credit risk assessments, reducing the likelihood of default and improving overall portfolio quality.

  • Risk Mitigation
    • Identified and mitigated credit risks more effectively, leading to better risk management practices and reduced exposure to potential losses.
  • Customization and Flexibility

    • Adapted the risk models and parameters to align with their specific risk appetite and business strategies.

  • Competitive Advantage

    • Resulting in a stronger and more resilient portfolio and reduced bad debts.

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