Smartnumbers’ Post

In one of our previous posts, we showed how to detect Fraud and also prevent it by using Data analytics. Now, here are the benefits of using data analytics to tackle fraudulent activities.

Could predictive analytics be a game-changer in the fight against payment fraud? With over 90% accuracy in detecting fraud, predictive analytics may very well take on superhero status! Read the Data Science Central article--> https://buff.ly/3YAFACC #PredictiveAnalytics #PowerofData

You wouldn't leave your car with all the doors open and the keys in the ignition...so, why would you leave your spend data unclassified for fraudsters to take advantage of? We need to start viewing the data we use in a more important light, are you with us? Find out how to instantly turn your business data into an insights goldmine by joining our community of dirty data fixers >>> https://lnkd.in/edf5NXCP

Topic: Financial Data Analysis & Fraud Detection link: https://lnkd.in/dtxrZzD5 Part-4 (Customer Behavior Insights) This SQL analysis provides ranking customers by total transaction volume over the last year, identifying dormant high-balance accounts with fewer than three transactions and pinpointing the most popular transaction types based on frequency, enabling targeted engagement strategies.

⚖️ 𝐃𝐚𝐭𝐚 𝐈𝐦𝐛𝐚𝐥𝐚𝐧𝐜𝐞: 𝐀 𝐇𝐢𝐝𝐝𝐞𝐧 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 𝐢𝐧 𝐌𝐋 If your dataset has significantly more of one class than another, your model might struggle. This is common in fraud detection, where fraud cases are rare but critical. Solutions: ✅ Oversampling the minority class (e.g., SMOTE). ✅ Using evaluation metrics like precision-recall over accuracy. 💡 Tip: Always visualize your class distribution first to detect imbalances. 👉 Have you ever dealt with imbalanced datasets? What worked for you? #machinelearning #data

NeuroID's modern and frictionless capabilities amplify Experian's fraud risk suite by providing a new layer of insight into digital behavioral signals and analytics observed for both new and returning users throughout the customer lifecycle

WHAT MUST BE CONSIDERED WHEN PROCESSING CUSTOMER'S UNSRUCTURED NARRATIVE DATA? FORM FACTOR (FAMILY-OCCUPATION-RECREATION-TIME & MONEY)

🔍 Need to identify outliers in your data? Try using the Local Moran's I stat! Identify key spatial hotspots and outliers - great for fraud detection, customer churn reduction, mobility planning, and more! Get started with our guide & free trial! 👇 https://hubs.ly/Q02LrhXC0

Welcome to November! 📊 It's time for a data audit to uncover critical call metrics you may be missing. Boost accuracy, spot fraud, and strengthen your network. Keep an eye out for more insights on this all month long! #TelecomAudit #CallMetrics #NovemberAudit #DataInsights

Financial institutions are stepping up—are you ready? Join our on-demand webinar to uncover how real-time insights can prevent drop-offs, stop fraud, and smooth customer journeys across platforms.