FRAUD & SECURITY INSIGHTS
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Articoli e altre risorse su Fraud & Security
- The state of insurance fraud technologyA 2019 Coalition Against Insurance Fraud study surveyed 84 companies on their use of anti-fraud technologies and compared results to 2014 and 2016. Get the highlights here.
- How AI and advanced analytics are impacting the financial services industryTop SAS experts weigh in on the topics that are keeping institutions up at night and fraudsters in a job.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Top 5 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.
- Chi ha paura della digital transformation?I protagonisti di Analytics Experience 2016 ci raccontano che i dati disegnano la nuova geografia del mondo e gli analytics sono la bussola per orientarsi. E, secondo David Shing, le emozioni avranno sempre più un ruolo centrale.
- “Io sono tecnologia”. La storia dell’artista cyborgNeil Harbisson grazie all’occhio bionico può sentire i colori tradotti in suoni
- 5 steps to sustainable GDPR complianceFollow these steps to achieve GDPR compliance by the May 2018 deadline – and get added benefits along the way.
- Know your blind spots in tax fraud preventionWhat can tax agencies do differently today than just a few years ago? Find out where fraud may lurk inside your agency – and the role analytics can play in tax fraud prevention.
- Cybersecurity? Tutto quello che c’è da sapere in otto punti essenzialiCome passare da un approccio alla sicurezza informatica basato sulla difesa passiva dagli attacchi a un modello più proattivo basato sull’analisi dei profili di rischio.
- How can analytics change the world of 'Narcos'?Surveillance, wire-taps, interrogations, informants… all valuable intelligence gathering techniques. But modern law enforcement and federal agents are now aided by a new technology to zero in on drug trafficking: analytics.
- Data management for cybersecurity: Know the essentialsSecurity teams tend to underestimate the importance of data management for cybersecurity. See the seven key reasons data management has been so difficult and five steps to getting it right.
- Analytics for prescription drug monitoringPrescription drug monitoring programs (PDMPs) are a great start in combating abuse of prescription drugs, but they could be doing much more. Better data and analytics can inform better treatment protocols, provider education and policy decisions – and save lives.
- Containing health care costs: Analytics paves the way to payment integrityFor payment integrity, health care organizations need to uncover a wider range of abuse, waste and errors and data-driven analytics is making that possible.
- Prevent child abuse 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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