fraud analytics

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Published By: SAS     Published Date: Feb 29, 2012
This collection is part of the ANA Magazine Thought Leadership Series sponsored by SAS. The articles explore the variety of ways to use analytics to create marketing functions that are more accountable and profitable.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics
    
SAS
Published By: SAS     Published Date: Feb 29, 2012
This paper provides an intro to managers and marketing professionals applying analytics to marketing to significantly improve outcomes. It explains not only why you need to make this shift, but also how you get started and what tools you'll need.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics
    
SAS
Published By: SAS     Published Date: Oct 03, 2018
Risks have intensified as retailers and financial organizations embrace new technologies to meet customer demands for convenience. The rise of mobile and online transactions introduces new risks – and with that, new requirements for fraud mitigation. This paper discusses key steps for fighting back against fraud risk by establishing appropriate and accurate data, analytics and alert management.
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SAS
Published By: SAS     Published Date: Oct 03, 2018
Fraudsters are only becoming smarter. How is your organization keeping pace and staying ahead of fraud schemes and regulatory mandates to monitor for them? Technology is redefining what’s possible in fighting fraud and financial crimes, and SAS is at the forefront, offering solutions to: • Protect from reputational, regulatory and financial risks. • Reduce the cost of fraud and financial crimes prevention. • Gain a holistic view of risk across functions. • Include cyber events in regulatory report filings. In this e-book, learn the basics in how to prevent fraud, achieve compliance and preserve security. SAS fraud solutions use advanced analytics and artificial intelligence to help your organization better detect and prevent fraud. By applying analytics and powerful machine learning on a unifying platform, SAS helps organizations around the globe detect more financial offenses, reduce false positives and run more efficient investigations.
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SAS
Published By: SAS     Published Date: Nov 16, 2018
Medicaid fraud is prevalent, costly and difficult to prevent. With a combination of more integrated data and advanced analytics, state agencies can turn the tables on fraudsters. They can accelerate the transition from detection to prevention, as new forms of fraud are recognized faster and fewer improper payments go out the door. This IIA Discussion Summary explores the challenges and opportunities in preventing Medicaid fraud in an interview with SAS’ Ellen Joyner-Roberson, Principal Marketing Manager for Fraud and Security Intelligence, and Victor Sterling, Principal Solutions Architect.
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SAS
Published By: SAS     Published Date: Nov 16, 2018
More account openings are taking place through digital devices and online, giving the access and anonymity fraudsters need to steal or fabricate identities. Since credit fraud often starts with a falsified application, it makes sense to have strong tools to monitor loans and credit lines from that point onward. This paper discusses analytics-driven methods for validating applications and spotting trouble at all three stages of bust-out fraud schemes.
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SAS
Published By: SAS     Published Date: Jan 04, 2019
As the pace of business continues to accelerate, forward-looking organizations are beginning to realize that it is not enough to analyze their data; they must also take action on it. To do this, more businesses are beginning to systematically operationalize their analytics as part of a business process. Operationalizing and embedding analytics is about integrating actionable insights into systems and business processes used to make decisions. These systems might be automated or provide manual, actionable insights. Analytics are currently being embedded into dashboards, applications, devices, systems, and databases. Examples run from simple to complex and organizations are at different stages of operational deployment. Newer examples of operational analytics include support for logistics, customer call centers, fraud detection, and recommendation engines to name just a few. Embedding analytics is certainly not new but has been gaining more attention recently as data volumes and the freq
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SAS
Published By: IBM     Published Date: May 07, 2015
Learn how to build a proactive threat and fraud strategy based on business analytics. You’ll see extensive examples of how organizations worldwide apply IBM Business Analytics solutions to minimize the negative impact of risk and maximize positive results.
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business analytics, risk management, threat management, fraud, proactive threat, analytics solutions, reduce exposure, reduce threats
    
IBM
Published By: SAS     Published Date: Apr 16, 2015
We often hear about how the massive volumes of data the US government collects hold a treasure trove of answers to our most challenging questions – be it on population health, national security, education or how to recoup losses from tax fraud. If only the government could figure out how to make use of all that information. Texas is one example of a government that is using analytics to solve complex problems. As the case studies here demonstrate, agencies and academia in the Lone Star State are putting big data and analytics to work to eliminate waste, improve productivity and, in some cases, even enhance transparency.
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SAS
Published By: SAS     Published Date: Aug 03, 2016
Insurance fraud has existed wherever insurance policies are written, taking different forms to suit the economic times. Today the magnitude of insurance fraud is not only startling but increasing. Recent studies by the US National Insurance Crime Bureau (NICB) reported a 24 percent rise in questionable claims for the period 2011 to 2013. The full scale of insurance fraud is not known. And if fraudulent behavior is not discovered at the time the claim is submitted, the insurer may never know it occurred. Consequently, an uninvestigated claim can’t be labeled as fraudulent to investigate.
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technology, best practices, security, analytics, insurance fraud
    
SAS
Published By: IBM     Published Date: Jul 24, 2012
Detect and prevent fraud by finding subtle patterns and associations in your data. IBM SPSS predictive analytics solutions have proved to be very effective at helping tax collection agencies to maximize revenues by detecting non-compliance more efficiently and by focusing investigations on cases that are likely to yield the biggest tax adjustments.
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fraud, business, healthcare, taxes, government, ibm, spss
    
IBM
Published By: Google     Published Date: Dec 03, 2018
The Internet of Things is growing fast: By 2025, IoT devices will transmit an estimated 90 zettabytes of data to their intended targets, according to IDC. Armed with information, businesses can revolutionise everything from fraud detection to customer service. But first, they need an architecture that supports real-time analytics so they can gain actionable insights from their IoT data. Read the complete report sponsored by Google Cloud, and learn how to mitigate key IoT-related challenges.
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Google
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