AI-powered financial fraud detection spend to hit $10bn
AI-powered financial fraud detection spending will exceed $10bn by 2027 as firms try to cope with increasingly complex attacks.
Fight Payment Fraud with AI and Machine Learning from SAS
SAS Fraud Management enables organizations to defend against the fast-growing and rapidly-changing challenges of payment fraud. Bringing the power of AI and machine learning from SAS to real-time fraud management, your organization can monitor all events and transactions in real time, rapidly gain insights from third-party data and quickly detect patterns of fraudulent behavior and fight payment fraud.
Learn more at – https://www.sas.com/securityintelligence
Monitoring payments and nonmonetary transactions, as well as events, can help you identify and respond to unwanted and suspicious behavior in real time. Your organization can respond faster to new threats, reduce false positives – all leading to a better customer experience.
SAS offers an end-to-end fraud detection and prevention solution to mitigate payment fraud. Incorporating data management, omni-channel fraud detection and real-time adaptive decisioning, your organization can respond faster to new threats as they arise.
Employing powerful machine learning methods, the SAS solution examines data from multiple sources and analyzes it for patterns and inconsistencies every time a transaction is processed. This enables your organization to stay ahead of constantly shifting tactics and new payment fraud schemes.
Learn More about SAS Software
Artificial Intelligence (AI) Solutions – https://www.sas.com/en_us/solutions/ai.html
SAS Trials: Free Software Trials – https://www.sas.com/en_us/trials.html
Sprout ai Health Insurance Solution
Sprout.ai’s augmented AI decision making plug-in for health insurance claims.
About Sprout.ai (previously BlockClaim)
Developed at Imperial College London, the advanced claims automation and fraud detection plug-in is already used by global insurers across three continents. The technology empowers insurers to settle claims in as little as 24 hours by providing data driven insights. Sprout.ai customers can expect a magnitude of benefits including reduced settlement times, increased fraud detection, reduction in operational costs and industrial grade security.
Fraud Detection: How AI is Transforming Financial Security #ai #fraud #aifyit
In this video, we’ll discuss how AI-powered fraud detection is transforming the way we protect our financial security. We’ll cover topics like digital authentication, face recognition, and more.
If you’re concerned about the rise of AI-powered fraud, then this video is for you. We’ll discuss how technology is changing the way we protect our financial security and what you can do to stay safe. After watching this video, you’ll know everything you need to know about AI-powered fraud detection and how it’s affecting the way we protect our financial security.
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Detecting Financial Fraud at Scale with Machine Learning – Elena Boiarskaia (H2O ai)
Detecting fraudulent patterns at scale is a challenge given the massive amounts of data to sift through, the complexity of the constantly evolving techniques, and the very small number of actual examples of fraudulent behavior. In finance, added security concerns and the importance of explaining how fraudulent behavior was identified further increases the difficulty of the task. Legacy systems rely on rule-based detection that is difficult to implement and run at scale. The resulting code is very complex and brittle, making it difficult to update to keep up with new threats. In this talk, we will go over how to convert a rule based financial fraud detection program to use machine learning on Spark as part of a scalable, modular solution. We will examine how to identify appropriate features and labels and how to create a feedback loop that will allow the model to evolve and improve overtime. We will also look at how MLflow may be leveraged throughout this effort for experiment tracking and model deployment. Specifically, we will discuss: -How to create a fraud-detection data pipeline -How to leverage a framework for building features from large datasets -How to create modular code to re-use and maintain new machine learning models -How to choose appropriate models and algorithms for a given fraud-detection problem.
About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business.
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