FRAUD & COMPLIANCE INSIGHTS
Protect your data, protect your customers
Recent Fraud & Security articles
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Top prepaid card fraud scamsThe margin for prepaid cards is slim, so it's particularly important to root out the scams. Here are some tips for combating and mitigating prepaid card fraud.
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Rethink customer due diligenceTo streamline compliance and protect against financial and regulatory risk, re-examine your customer due diligence processes and technologies regularly. With new analytical tools, you can monitor customer transactions or personal information in real time, and accurately segment customers by the risk they represent.
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When it matters: Safeguarding your organization from the insideWith evolving threats, fraud detection technologies have to be flexible and nimble, and automated risk detection is a crucial component of decision advantage.
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Fraud detection and machine learning: What you need to knowMachine learning and fraud analytics are critical components of a fraud detection toolkit. Discover what you’ll need to get started defending against fraud – from integrating supervised and unsupervised machine learning in operations to maintaining customer service.
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Are you covering who you think you’re covering? Payers often don't focus enough on healthcare beneficiary fraud in public and private healthcare plans. Before paying a claim, payers need to ensure beneficiaries are eligible. Advanced analytics applied to a broad range of data can help them accurately detect and prevent beneficiary fraud.
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Small-time cheats and organized crime: Benefits fraud re-examinedTo combat benefits fraud, better utilize resources and improve ROI, analytics can detect organized crime rings rather than just small-time fraudsters.
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How to uncover common point of purchaseFraudsters use many techniques to steal card data. Banks that want to stay ahead of common point of purchase (CPP) and contain the costs of fraud need to implement advanced analytics techniques to strengthen their fraud prevention programs.
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Next generation anti-money laundering: robotics, semantic analysis and AIAdding AI and machine learning to your anti-money laundering program can combat rising compliance pressures, complexity and risks. Learn about the results innovative financial institutions around the globe are getting from next-generation AML.
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Online payment fraud stops hereBillions of dollars each year are lost to online payment fraud through channels that provide convenient – yet vulnerable – ways to shop and bank. See how to fight back and win with advanced analytics.
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Next generation anti-money laundering: robotics, semantic analysis and AIAdding AI and machine learning to your anti-money laundering program can combat rising compliance pressures, complexity and risks. Learn about the results innovative financial institutions around the globe are getting from next-generation AML.
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4 strategies that will change your approach to fraud detectionTechnology advances are giving institutions a better arsenal than ever for fraud detection. Take a look at four fraud solutions to turbocharge your defenses. SAS NL
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Shut the front door on insurance application fraud!Fraudsters love the ease of plying their trade over digital channels. Smart insurance companies are using data from those channels (device fingerprint, IP address, geolocation, etc.) coupled with analytics and machine learning to detect insurance application fraud perpetrated by agents, customers and fraud rings.
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Intelligent policing: Are data analytics systems the key to public safety?Police agencies are navigating rapidly changing landscapes, rising data volumes, evolving threats, and growing expectations for transparency and coordination. They can't keep pace if they're dependent on siloed data, aging platforms and legacy practices. Intelligent policing can help. This evolution from reactive to problem-oriented policing relies on shared data, visualization and a scalable analytics ecosystem.
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Analytics: A must-have tool for leading the fight on prescription and illicit drug addictionStates and MFCUs now have the analytics tools they need to change the trajectory of the opioid crisis by analyzing data and predicting trouble spots – whether in patients, prescribers, distributors or manufacturers. The OIG Toolkit with free SAS® programming code makes that possible.
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Online fraud: Increased threats in a real-time worldOnline and mobile banking is convenient for customers -- and an opportunity for fraudsters. With fraud methods constantly evolving, an analytical approach is a must for banks seeking early, accurate detection.
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Mobile payments, smurfs and emerging threatsM-payment remittances are replacing traditional banks and money services that have historically charged high fees for small transfers. Former US Treasury Special Agent John Cassara maps what he sees in the road ahead and gives advice for protecting your firm.
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Managing fraud risk: 10 trends you need to watchSynthetic identities, credit washing and income misrepresentation – these are just some of the trends to watch if you’re trying to understand how to manage fraud risk. Find out what’s on the top 10 list of trends according to experts like Frank McKenna and Mary Ann Miller.
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Health care cost containment through big data analyticsHealth insurers are plagued by fraud, waste and abuse. For health care cost containment, an enterprise approach to payment integrity using data management and analytics can help. With this approach, payers can detect and prevent fraud; influence provider, employee and patient behavior; and substantially reduce costs.
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Applying technology to ensure voter integrity in electionsVoter integrity is becoming a serious concern. Recent disclosures of foreign influence using social media highlight the potential impact on the democratic process. Technology can identify both legitimate and fraudulent activity; the key is to minimize the impact on legitimate activity while thwarting cyber-criminals and fraudsters.
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Uncover hidden financial crime riskEscalating threats call for a financial crime risk framework that uses powerful, visual, interactive techniques to proactively identify hidden risks.
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