fraud analytics

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Published By: Google     Published Date: Jan 24, 2019
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
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: 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
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: Google     Published Date: Oct 26, 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
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: TIBCO Software APAC     Published Date: Aug 13, 2018
The combination of legislation, market dynamics, and increasingly sophisticated risk management strategies requires you to be proactive in detecting risks like fraud quicker and more effectively. Dynamic detection systems need to adapt to evolving compliance regulations, scale to deal with growing transaction volumes, detect sophisticated risk specific patterns, and reduce false-positives. TIBCO's Risk Management Accelerator uses a combination of predictive analytics, streaming analytics, and business process management to deliver a powerful and cost-effective system for detecting anomalies. Download this solution brief to learn more.
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TIBCO Software APAC
Published By: Microsoft Azure     Published Date: Apr 11, 2018
Developing for and in the cloud has never been more dependent on data. Flexibility, performance, security—your applications need a database architecture that matches the innovation of your ideas. Industry analyst Ovum explored how Azure Cosmos DB is positioned to be the flagship database of internet-based products and services, and concluded that Azure Cosmos DB “is the first to open up [cloud] architecture to data that is not restricted by any specific schema, and it is among the most flexible when it comes to specifying consistency.” From security and fraud detection to consumer and industrial IoT, to personalized e-commerce and social and gaming networks, to smart utilities and advanced analytics, Azure Cosmos DB is how Microsoft is structuring the database for the age of cloud. Read the full report to learn how a globally distributed, multi-model data service can support your business objectives. Fill out the short form above to download the free research paper.
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Microsoft Azure
Published By: SAS     Published Date: Mar 06, 2018
Industry leaders from the banking and vendor landscape are working to streamline the customer experience while closing the opportunities for fraud and exposure. Balancing security and convenience will require an approach that combines consumer-facing authentication (such as passwords, PINs and biometrics) with background security measures (such as transaction and session-behavior analytics).
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SAS
Published By: SAS     Published Date: Mar 06, 2018
The 2016 ACFE Report to the Nations on Occupational Fraud and Abuse analyzed 2,410 occupational fraud cases that caused a total loss of more than $6.3 billion.8 Victim organizations that lacked anti-fraud controls suffered double the amount of median losses. SAS’ unique, hybrid approach to insider threat deterrence – which combines traditional detection methods and investigative methodologies with behavioral analysis – enables complete, continuous monitoring. As a result, government agencies and companies can take pre-emptive action before damaging incidents occur. Equally important, SAS solutions are powerful yet simple to use, reducing the need to hire a cadre of high-end data modelers and analytics specialists. Automation of data integration and analytics processing makes it easy to deploy into daily operations.
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SAS
Published By: SAS     Published Date: Mar 06, 2018
Tax fraud is already prevalent, and fraudsters are more sophisticated and automated than ever. To get ahead of the game in detecting fraud and protecting revenue, tax agencies need to leverage more advanced and predictive analytics. Legacy processes, systems, and attitudes need not stand in the way. To explore the challenges, opportunities, and value of tax fraud analytics, IIA spoke with Deborah Pianko, a Government Fraud Solutions Architect within the SAS Security Intelligence practice.
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SAS
Published By: CA Technologies     Published Date: Feb 08, 2018
CNP fraud is showing no signs of deceleration and is, in fact, expanding rapidly. New trends and new threats call for a revolutionary approach to effectively stop fraud. Learn how to deploy solutions that can quickly distinguish between genuine and fraudulent transactions and take appropriate action instantly. Explore the CA Risk Analytics Network.
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CA Technologies
Published By: SAS     Published Date: Jan 17, 2018
Insurers have long been plagued by fraud, error, waste, and abuse in health care payments. The costs are huge – amounting to as much as 25 percent of payments made. Today’s data management and analytics platforms promise breakthroughs by incorporating comparative and behavioral data to predict as well as detect loss in all its forms. To explore the opportunities and how insurers can capitalize on them, IIA spoke with Ben Wright, Sr. Solutions Architect in SAS’s Security Intelligence Global Practice.
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SAS
Published By: Intel Corp.     Published Date: Nov 21, 2017
This whitepaper will provide an overview on how powerful computing and software technologies enable real time fraud detection to cut losses and reduce risks.
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Intel Corp.
Published By: Fiserv     Published Date: Nov 09, 2017
Financial institutions seeking to attract new customers and revenue channels are expanding into digital services, real-time payments and global transactions. However, with every new service, criminals are developing innovative ways to infiltrate financial systems, and older technologies that mitigate fraud no longer work as effectively. So how can financial institutions respond to this growing threat? Fortunately, more advanced technologies hold great potential for real-time financial crime mitigation. Learn about five current and emerging technologies that could impact money laundering and fraud mitigation, including artificial intelligence/machine learning, blockchain, biometrics, predictive analytics (hybrid model) and APIs. Read the latest Fiserv white paper: Five Tech Trends That Can Transform How Financial Institutions Detect and Prevent Financial Crime.
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kyc, know your customer, beneficial ownership, financial crime, financial crimes, compliance, enhanced due diligence, suspicious activity report, currency transaction report, aml directive, anti-money laundering laws
    
Fiserv
Published By: SAS     Published Date: Oct 18, 2017
Health insurers have long been plagued by issues of fraud, waste, abuse, error and corruption. Taking 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. Payers can achieve better outcomes when software support for the core disciplines of payment integrity run on a single platform.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
How much are fraud, error, waste and abuse costing your organization? Costs to insurers are huge – as much as 25 percent of payments made. But data management and analytics can save the day. This paper discusses how data can be used to predict and detect loss in all its forms.
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SAS
Published By: SAS     Published Date: Jun 08, 2017
The underground economy is thriving, thanks in part to new technologies and business models such as digital currencies and online marketplaces for freelance services. SAS fraud specialists reveal how government agencies can uncover these activities – and the tax obligations not reported from them. A former head of compliance for the country’s fourth-largest state workers' comp program describes how a comprehensive analytics program found a tax gap of $718 million and was granted funding to double the team’s size without even asking.
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SAS
Published By: IBM     Published Date: May 26, 2017
A significant challenge for many organizations has been enabling their analysts to find the "unknown unknown." Whether that unknown is malware lurking within the enterprise or within slight variations in fraudulent transactions, the result has been the same: enterprises continue to fall victim to cybercrime. IBM is addressing this challenge with IBM i2 Enterprise Insight Analysis. By pairing multi-dimensional visual analysis capabilities with powerful analytics tools, IBM is giving the analyst team an effective early-detection, cyberintelligence weapon for its arsenal.
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security. ibm, ibm i2, cyber-intelligence, fraud, malware
    
IBM
Published By: IBM     Published Date: Apr 27, 2017
It’s hard to grow your business if you can’t see what’s coming next. What will the demand be for a specific product or service and how should you adjust production? What revenue can be expected and from which channels? Where are the best areas to expand your business? Predictive analytics can provide the answers executives, analysts and business managers need to reduce costs, operate more efficiently and increase the bottom line. Join IBM SPSS and guest Mark Lack, Manager of Strategy Analytics and Business Intelligence with industrial products company Mueller Inc. for a look at how to decrease costs and improve your business’ profitability with predictive analytics. You’ll learn how Mueller extends the value of its Big Data environment by applying predictive techniques to accurately forecast sales, prevent fraud and reduce losses from damaged inventory, saving the company significant time and money.
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predictive analytics, fraud detection, increase revenue, decrease costs, customer retention, hr efficiency, advanced analytics
    
IBM
Published By: SAS     Published Date: Apr 25, 2017
Insurers have long been plagued by fraud, error, waste, and abuse in health care payments. The costs are huge – amounting to as much as 25 percent of payments made. Today’s data management and analytics platforms promise breakthroughs by incorporating comparative and behavioral data to predict as well as detect loss in all its forms. To explore the opportunities and how insurers can capitalize on them, IIA spoke with Ben Wright, Sr. Solutions Architect in SAS’s Security Intelligence Global Practice.
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SAS
Published By: CA Technologies     Published Date: Apr 06, 2017
CA Technologies (NASDAQ: CA) creates software that fuels transformation for companies and enables them to seize the opportunities of the application economy. Software is at the heart of every business, in every industry. From planning to development to management and security, CA is working with companies worldwide to change the way we live, transact and communicate—across mobile, private and public cloud, distributed and mainframe environments.
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enterprise security, it security, payment card fraud, risk management, cyber attacks, risk, data protection, threat analytics, integrated mitigation
    
CA Technologies
Published By: IBM     Published Date: Jan 26, 2017
By taking full advantage of the integration and advanced capabilities currently being offered by leading counter fraud solution providers - including predictive analytics and cognitive computing - enterprises can expect to achieve significantly better outcomes.Aberdeen Group's analysis helps to quantify the value of counter fraud analytics in the insurance industry.
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ibm, analytics, fraud analytics, insurance, fraud
    
IBM
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