--- title: Best Fraud Detection posts of 2024 | daily.dev description: The most upvoted Fraud Detection posts of 2024, curated by the daily.dev community. canonical: https://daily.dev/tags/fraud-detection/best-of/2024 twitter:card: summary_large_image twitter:site: @dailydotdev og:url: https://daily.dev/tags/fraud-detection/best-of/2024 og:type: website og:site_name: daily.dev og:title: Best Fraud Detection posts of 2024 | daily.dev og:description: The most upvoted Fraud Detection posts of 2024, curated by the daily.dev community. og:image: https://media.daily.dev/image/upload/s--VAY5ToZt--/f_auto/v1724209435/public/daily.dev%20-%20open%20graph --- # Best of Fraud Detection — 2024 1. 1 [](/posts/anti-money-laundering-and-fraud-prevention-with-mongodb-vector-search-and-openai-fkloq2tgn "Anti-Money Laundering and Fraud Prevention With MongoDB Vector Search and OpenAI") Article MongoDB · 2y Anti-Money Laundering and Fraud Prevention With MongoDB Vector Search and OpenAI Anti-money laundering (AML) and fraud prevention have evolved significantly, from manual processes and rule-based systems (Risk 1.0) to predictive modeling (Risk 2.0), and now to real-time analytics with vector search (Risk 3.0). MongoDB Atlas Vector Search, integrated with OpenAI embeddings, offers a powerful solution for detecting fraud and AML by addressing limitations like lack of context and manual feature engineering. This holistic approach leverages real-time data and continuous monitoring, making fraud detection more accurate and less reliant on extensive human oversight. 43 1 2. 2 [](/posts/a-better-way-to-build-auth-yxggokpvv "A better way to build auth") Article Community Picks · 2y A better way to build auth Enhance authentication and authorization with Stytch's purpose-built solutions for consumer and multi-tenant applications. It features pre-built UI, headless frontend SDKs, backend APIs, and an embeddable admin portal. It ensures high security with fingerprinting for bot detection, adaptive MFA, and reliable risk verdicts. Stytch boasts a 99.999% uptime SLA, scalable user and org data models, fraud and risk prevention mechanisms, and provider failover options. The service supports seamless integration into any language, with customizable login and signup forms. 25 3. 3 [](/posts/detecting-bank-fraud-with-neo4j-the-power-of-graph-databases-dk9tw79v7 "Detecting Bank Fraud With Neo4j: The Power of Graph Databases") Article neo4j · 2y Detecting Bank Fraud With Neo4j: The Power of Graph Databases Financial institutions are facing significant losses due to increasingly sophisticated fraud schemes. Traditional detection methods fall short, but Neo4j, a graph database, offers advanced solutions through entity link analysis. By identifying and mitigating fraud rings in real-time, Neo4j helps banks enhance their fraud detection capabilities, reduce losses, and improve security. The article provides practical Cypher queries for identifying shared information, assessing financial risks, and analyzing total credit limits among fraud rings. Neo4j's ability to visualize complex relationships further aids in speeding up investigations and improving decision-making. 22 1 4. 4 [](/posts/graph-neural-networks-fraud-detection-and-protein-function-prediction-znbijbusi "Graph Neural Networks: Fraud Detection and Protein Function Prediction") Article Medium · 2y Graph Neural Networks: Fraud Detection and Protein Function Prediction Graph Neural Networks (GNNs) are a powerful alternative for modeling relational data in financial networks and protein structures, which are complex and not well-represented in Euclidean space. GNNs capture relationships between entities more effectively than traditional deep learning architectures, making them crucial for tasks such as fraud detection and protein function prediction. GNNs use message-passing frameworks to update node embeddings based on aggregated features from neighboring nodes, ultimately improving detection and prediction accuracy in various applications. 14 5. 5 [](/posts/implementing-deep-learning-for-fraud-detection-in-fintech-cgxofn75z "Implementing Deep Learning for Fraud Detection in FinTech") Article Medium · 2y Implementing Deep Learning for Fraud Detection in FinTech Financial fraud is a significant issue affecting global companies, costing an estimated 5% of their revenue annually. Financial institutions and regulatory bodies are adopting advanced measures, including deep learning, to combat this problem. Deep learning excels at recognizing patterns and predicting fraud, offering scalability and reduced false positives. Companies like PayPal and Mastercard are already utilizing these techniques. However, challenges such as data privacy, transparency, and high computational costs must be addressed. The future promises more accessible and adaptive AI systems, better managing fraud detection while adhering to data privacy regulations. 12 6. 6 [](/posts/metrics-to-evaluate-a-classification-machine-learning-model-pe0rhoxpl "Metrics to Evaluate a Classification Machine Learning Model") Article Towards Data Science · 2y Metrics to Evaluate a Classification Machine Learning Model Evaluating a classification machine learning model involves understanding various performance metrics like precision, recall, F1 score, and accuracy. Precision helps measure the proportion of correct positive predictions, while recall assesses the model's ability to catch actual positive cases. Accuracy can be misleading in imbalanced datasets, like fraud detection, making metrics like precision and recall more reliable. The confusion matrix is a critical tool in visualizing these outcomes. 12 7. 7 [](/posts/how-sms-fraud-works-and-how-to-guard-against-it-a7qlxstug "How SMS Fraud Works and How to Guard Against It") Article Community Picks · 2y How SMS Fraud Works and How to Guard Against It This post explores the mechanics of SMS fraud and offers various strategies to guard against it, particularly in the wake of Twitter's decision to disable text message two-factor authentication for non-paid users. It delves into how bad actors exploit premium phone numbers to incur costs on web services and provides a list of preventative measures including IP blocking, rate-limiting, CAPTCHAs, and using alternative messaging platforms like WhatsApp. 12 [See all Fraud Detection archives](/tags/fraud-detection/best-of) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@graph":[{"@type":"CollectionPage","@id":"https://daily.dev/tags/fraud-detection/best-of/2024#page","url":"https://daily.dev/tags/fraud-detection/best-of/2024","name":"Best Fraud Detection Posts of 2024","description":"The most upvoted Fraud Detection posts of 2024, curated by the daily.dev community.","isPartOf":{"@type":"WebSite","url":"https://daily.dev"}},{"@type":"ItemList","@id":"https://daily.dev/tags/fraud-detection/best-of/2024#items","numberOfItems":7,"itemListElement":[{"@type":"ListItem","position":1,"url":"https://daily.dev/posts/anti-money-laundering-and-fraud-prevention-with-mongodb-vector-search-and-openai-fkloq2tgn","name":"Anti-Money Laundering and Fraud Prevention With MongoDB Vector Search and OpenAI"},{"@type":"ListItem","position":2,"url":"https://daily.dev/posts/a-better-way-to-build-auth-yxggokpvv","name":"A better way to build auth"},{"@type":"ListItem","position":3,"url":"https://daily.dev/posts/detecting-bank-fraud-with-neo4j-the-power-of-graph-databases-dk9tw79v7","name":"Detecting Bank Fraud With Neo4j: The Power of Graph Databases"},{"@type":"ListItem","position":4,"url":"https://daily.dev/posts/graph-neural-networks-fraud-detection-and-protein-function-prediction-znbijbusi","name":"Graph Neural Networks: Fraud Detection and Protein Function Prediction"},{"@type":"ListItem","position":5,"url":"https://daily.dev/posts/implementing-deep-learning-for-fraud-detection-in-fintech-cgxofn75z","name":"Implementing Deep Learning for Fraud Detection in FinTech"},{"@type":"ListItem","position":6,"url":"https://daily.dev/posts/metrics-to-evaluate-a-classification-machine-learning-model-pe0rhoxpl","name":"Metrics to Evaluate a Classification Machine Learning Model"},{"@type":"ListItem","position":7,"url":"https://daily.dev/posts/how-sms-fraud-works-and-how-to-guard-against-it-a7qlxstug","name":"How SMS Fraud Works and How to Guard Against It"}]},{"@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Tags","item":"https://daily.dev/tags"},{"@type":"ListItem","position":3,"name":"Fraud Detection","item":"https://daily.dev/tags/fraud-detection"},{"@type":"ListItem","position":4,"name":"Best of","item":"https://daily.dev/tags/fraud-detection/best-of"},{"@type":"ListItem","position":5,"name":"2024"}]}]} ```