FRAUD & SECURITY INSIGHTS
Protect your data, protect your customers
Recent Fraud & Security articles
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Analytics can help prevent substance use disorder and over-prescribingStates 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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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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Detect and prevent banking application fraudSince credit fraud often starts with a falsified application, it makes sense to have analytics-driven tools in place to detect fraud from the earliest point and across the life of the account.
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Medicaid and benefit fraud in 2018 and beyondTo curb the growing amount of Medicaid and benefit fraud and improper payments, agencies and their commercial counterparts need fraud and abuse detection systems with data management and analysis that can keep up and even stay one step ahead.
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Strengthen your payment fraud defenses with stronger authenticationThe rapid growth of digital wallets and payment applications has ushered in new payment fraud threats to consumers and organizations. Find out how the use of innovative technologies to combat payment fraud is a viable and effective solution with additional benefits.
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Anti-money laundering and counter-terrorist financingTo monitor for financial crimes, an essential element for both anti-money laundering and counter-terrorist financing is using data analysis to detect unusual activity during processing by monitoring transactions, customers and the network of behaviors.
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What do drones, AI and proactive policing have in common?Law enforcement and public safety agencies must wrangle diverse data sets to be effective in their operations. Intelligence analysts are using that data to apply machine learning and AI for more proactive policing.
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4 strategies that will change your approach to fraud detectionTechnology advances are giving financial institutions a better arsenal than ever for fraud detection. Take a look at four ways to turbocharge your defenses.
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Super-charge your fraud detection techniquesPreview a white paper by the International Institute for Analytics on how to evolve the fraud function from a set of fraud detection techniques to a cohesive, continuously improving system.
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Transaction monitoring: To segment or not?A typical anti-money laundering transaction monitoring program treats all customers as if they transact the same. A better practice is to analyze customer segments and apply more focused monitoring to reduce false positive alerts based on scenario thresholds.
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How to prevent procurement fraudPerpetrated in several ways, procurement fraud is difficult to detect. Arm yourself with hybrid analytics that offer various approaches for cross-pollination of data and analysis.
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Intelligent policing: Data visualization helps crack down on crimeUse data visualization for real-time views of locations, layered with data sources, including crime, traffic and weather for more intelligent policing.
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Improve child welfare through analyticsWith tremendous potential for child welfare agencies to use data and analytics to prevent child abuse and improve outcomes for children and families, child welfare advocates discuss the benefits of using data and establishing a data-driven culture to advance practice and policy.
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6 ways big data analytics can improve insurance claims data processingWhy make analytics a part of your insurance claims data processing? Because adding analytics to the claims life cycle
can deliver a measurable ROI.
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New data on the latest digital fraud trendsGet a quick, fact-filled view of what ISMG, Longitude Research and Javelin discovered in recent studies of fraud trends and anti-fraud strategies.
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Fraud detection and machine learning: What you need to knowFrom integrating throughout operations to maintaining customer service, machine learning – supervised and unsupervised – is a critical part of the fraud detection toolkit. Here’s what you’ll need to consider to get started.
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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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Is it case management or alert management?Both AML and payments fraud generate alerts, but handle them differently - making a common understanding of case management and alert management paramount.
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Proactive detection – A new approach to counter terrorTo counter terror, investigative teams can better utilize the data they already have by applying a fresh approach with these steps to proactive detection.
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Health care cost containment through big data analyticsTaking an enterprise approach to payment integrity – one that combines advanced data management and sophisticated analytics – can help payers detect and prevent fraud; effect positive change in how providers, employees and patients behave; and substantially reduce health care costs.
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