The latest articles on DEV Community by Tanvir Rahman (@tanvir_rahman). https://dev.to/tanvir_rahman https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3169275%2Fd9479d18-7ac5-4bb4-9a9e-c58672196612.jpeg https://dev.to/tanvir_rahman en Tanvir Rahman Fri, 16 May 2025 07:42:07 +0000 https://dev.to/tanvir_rahman/a-data-analysts-guide-to-ai-in-fintech-3j4g https://dev.to/tanvir_rahman/a-data-analysts-guide-to-ai-in-fintech-3j4g <p><em><em>By Tanvir Rahman</em></em></p> <p>Artificial Intelligence (AI) is changing how financial companies work. It helps detect fraud, predict credit risk, and personalize services for customers. As a Senior System Data Analyst, I’ve seen how AI can turn complex financial data into useful insights that help businesses make better decisions and protect their customers.</p> <h2> What Data Analysts Do in AI and Fintech </h2> <p>Data analysts play an important role in making AI work. They clean and prepare data, create features that help AI models understand the information, and check how well models perform. They also explain results to business teams and help keep the AI models working well over time.</p> <h2> Common AI Uses in Fintech </h2> <ul> <li> <strong>Fraud Detection:</strong> AI learns what normal transactions look like and spots anything unusual that could be fraud.</li> <li> <strong>Credit Risk Modeling:</strong> Machine learning predicts how likely a customer is to repay a loan by analyzing lots of data.</li> <li> <strong>Personalization:</strong> AI groups customers by their behavior so companies can offer services that fit their needs.</li> <li> <strong>Churn Prediction:</strong> AI helps predict which customers might leave, so companies can try to keep them.</li> </ul> <h2> Tools I Use </h2> <p>Some of the main tools I work with include:</p> <ul> <li> <strong>Python</strong> for programming</li> <li> <strong>pandas</strong> and <strong>NumPy</strong> for data handling</li> <li> <strong>scikit-learn</strong>, <strong>XGBoost</strong>, and <strong>LightGBM</strong> for machine learning</li> <li> <strong>imbalanced-learn</strong> to deal with rare fraud cases</li> <li> <strong>SHAP</strong> and <strong>LIME</strong> to explain model decisions</li> <li> <strong>Azure ML</strong> and <strong>AWS SageMaker</strong> for deploying AI models</li> </ul> <h2> Why Ethics Matter </h2> <p>AI affects real people’s lives, so it must be fair and transparent. I check models for bias and use tools that explain how they make decisions. This helps build trust with customers and regulators and ensures compliance with laws like GDPR.</p> <h2> What I’ve Learned </h2> <ul> <li>AI models need regular updates to stay accurate.</li> <li>Human judgment is important alongside AI, especially for big decisions.</li> <li>Good communication between analysts and business teams helps AI succeed.</li> </ul> <p>Interested in learning more? Let’s connect and explore the future of AI in fintech!</p> <p><strong>About the Author:</strong><br><br> <em>Tanvir Rahman</em><br><br> Senior System Data Analyst | AI in Fintech<br><br> Specializing in fraud detection, credit risk modeling, Python, machine learning, and data analytics.</p> webdev programming ai