FRAUD & SECURITY INSIGHTS

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Recent Fraud & Security articles

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.
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.
How AI and advanced analytics are impacting the financial services industryTop SAS experts weigh in on topics that keep financial leaders up at night – like real-time payments and digital identity. See how advanced analytics and AI can help.
Intelligent policing: Data visualization helps crack down on crimeLearn how data visualization can give police real-time views of locations enriched with other data to help them make intelligent, fact-based decisions.
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.
Know your blind spots in tax fraud preventionTax agencies sometimes miss fraud that's happening right under their noses – despite robust external fraud prevention efforts. Find out where traditional tax fraud prevention and detection efforts fall short, and how analytics can change that.
Containing health care costs: Analytics paves the way to payment integrityTo ensure payment integrity, health care organizations must uncover a broad range of fraud, waste and abuse in claims processing. Data-driven analytics – along with rapid evolutions in the use of computer vision, document vision and text analytics – are making it possible.
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.
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.
Strengthen your payment fraud defenses with stronger authenticationThe rapid growth of digital wallets and payment applications ushered in many new payment fraud threats. Today, it’s more critical than ever to authenticate users. Learn four innovative to ways strengthen your authentication defenses while reducing false positives and protecting customers’ assets.
Payment fraud evolves fast – can we stay ahead?Payment fraud happens when a criminal steals a person’s private payment information, then uses it for an illegal transaction. As payment trends evolve, so do the fraudsters. Banks and PSPs can fight back with advanced analytics techniques that adapt quickly to spot anomalies in behavior.
Unemployment fraud meets analytics: Battle lines are clearly drawnMany fraudsters seized opportunities presented by the COVID-19 pandemic. During the crisis, unemployment fraud became a battleground between international criminal networks and government agencies. Learn how analytics can save billions – and deliver benefits to those truly in need.
Continuous monitoring: Stop procurement fraud, waste and abuse nowProcurement fraud, waste and abuse silently robs businesses an average of 5% of spend annually. And even when organizations invest in detection methods, they’re often let down by their techniques. Learn what continuous monitoring is and why this proven analytical method is key to fighting back.
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.
Next generation anti-money laundering: robotics, semantic analysis and AIAnti-money laundering taken to its next level is sometimes referred to as AML 2.0 or AML 3.0. What does this next wave of AML technology look like? What can it do that you can’t do with traditional AML? See the results innovative financial institutions around the globe are already getting.
The best gift you can give to thieves this holiday season? Your identity.While the use of EMV in cards has helped to mitigate fraud perpetrated at retail stores, undeterred fraudsters have focused their efforts online. Find out how advanced analytics and machine learning help combat this threat.
Applying technology to ensure voter integrity in electionsVoter integrity is becoming a serious concern for many elections. Recent disclosures of foreign influence campaigns using social media highlight the potential impact on the integrity of the democratic process. In monitoring your systems, technology can identify both legitimate and fraudulent activity; the balancing act is to minimize the impact on legitimate activity while preventing acts of cyber-criminals and fraudsters.
Detect and prevent banking application fraudCredit fraud often starts with a falsified application. That’s why it’s important to use analytics starting at the entrance point. Learn how analytics and machine learning can detect fraud at the point of application by recognizing the biggest challenge – synthetic identities.
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.
What do drones, AI and proactive policing have in common?Law enforcement and public safety agencies must wrangle diverse data sets – such as data from drones – in their proactive policing operations. To be most effective, they need modern tools that support AI techniques like machine learning, computer vision and natural language processing.

Fraud & Security: The Basics

No organization looks forward to hearing about fraud – which the Association of Certified Fraud Examiners defines as “any intentional or deliberate act to deprive another of property or money by guile, deception or other unfair means.” Yet fraud is one of the biggest risks many organizations face. Fraud and financial crime can be committed by employees, customers, vendors, suppliers and others. Regardless of where it starts or how it happens, it’s important to stay up to date on the latest fraud trends and techniques you can use to fight it. Explore the topic of fraud from the perspectives of many experts in the field.

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What is fraud prevention?

The incidence and sophistication of fraud, waste and abuse are on the rise in every industry, fueled in part by the ongoing financial uncertainty gripping the world's economy. No matter what industry you're in – banking, insurance, health care, government – your organization is likely feeling the effects. And feeling the pressure do something about it.

To fight fraud effectively, you must continually improve the way you monitor customer behavior across multiple accounts and systems. Get the latest insights on fraud prevention and the technology that gives organizations the upper hand in detecting fraud in any form, at any touch point.

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What is anti-money laundering (AML)?

Criminals use money laundering – a financial crime – to hide the origins of their “dirty money” so it will appear to be from a legitimate source. Fraudsters follow a complex, three-step process to cover their tracks.

Banks and other financial institutions perform anti-money laundering activities to fight money laundering. They do so for moral reasons and to achieve compliance with legal requirements.

The list of criminal activities tied to money laundering is long. Smuggling, embezzlement, bribery, terrorist financing, prostitution rings and human and drug trafficking are just a few examples.

Learn more about anti-money laundering