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.
- Conheça 6 formas de utilizar a análise de big data que podem melhorar o processamento dos pedidos de indemnização de segurosPorque é que deve incluir a análise de processamento de dados nos seus pedidos de indemnização de seguros? Porque é que juntar a análise e a AI, ao ciclo de vida dos pedidos de indemnização, pode proporcionar um ROI quantificável.
- 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.
- Impeça fraudes em aplicações de seguros!Os vigaristas adoram a facilidade com que conseguem cometer crimes nos canais digitais. As companhias de seguros inteligentes estão a utilizar dados desses canais (impressão digital do dispositivo, endereço IP, geolocalização, etc.) juntamente com análise e machine learning para detetar fraudes nas aplicações de seguros que são perpetuadas por agentes, clientes e grupos criminosos organizados.
- 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.
- Detetar e prevenir a fraude nas aplicações bancáriasA fraude nos créditos, por norma, começa por uma candidatura falsa. É por isso que é tão importante usar a análise logo no ponto de partida. Aprenda como a análise e a aprendizagem automática podem detetar fraudes logo nos primeiros pontos de contacto dos pedidos ao reconhecer os maiores desafios – identidades sintéticas.
- 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.
- A fraude nos pagamentos evolui rapidamente - será que podemos estar um passo à frente?A fraude nos pagamentos acontece quando um criminoso rouba a informação de pagamentos privada de uma pessoa, e depois a utiliza para uma transação ilegal. À medida que as tendências de pagamento evoluem, o mesmo acontece com os autores das fraudes. Os bancos e os PSP podem combater as fraudes com técnicas avançadas de analytics que se adaptam rapidamente à deteção de anomalias no comportamento.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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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