fraud analytics

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Published By: Akamai     Published Date: Jun 04, 2010
Predictive analytics have been used by different industries for years to solve difficult problems that range from detecting credit card fraud to determining patient risk levels for medical conditions. It combines data mining and machine-learning technologies to create statistical models based on historical data. It then uses these models to predict future events. Extracting the power from the data requires powerful algorithms behind predictive analytics.
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akamai, predictive, online advertising, tracking pixels, online shopping, in-market, site visitors, performance marketing
    
Akamai
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: 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: 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: 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: 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: 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: HP     Published Date: Jan 20, 2015
Security breaches can happen anywhere in an organization, and having the ability to analyze any form of data can give you the edge against fraud, theft, and infiltration by pinpointing abnormal behavior patterns. Understanding your security vulnerabilities requires rapid, deep analytics against business data, machine data, and unstructured human information.
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big data, hp haven, scalable, secure data platform, ecosystem, security
    
HP
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: IBM     Published Date: Jul 24, 2012
Tax revenues have been declining recently and some of this loss is caused by fraud, tax evasion, and various forms of tax cheating. The ineffective recovery techniques can give government agencies poor results, which results in 20% of broad-approach audits ending in "no charge". By using IBM SPSS Predictive Analytics Solutions it is possible to maximize revenues, analyze the data you already collect, detect non-compliant accounts efficiently, and identify important differences in tax records. This program has tremendous power and features an easy to use interface that focuses investigations on case that yield large adjustments ensuring a successful ROI for clients.
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tax revenues, fraud, ibm, business analytics, spss solutions, tax cheating, roi
    
IBM
Published By: IBM     Published Date: Sep 25, 2013
Learn why an Enterprise Fraud Management Platform allows for data to be shared more efficiently while simultaneously applying analytics to prioritize workflows, which will increase productivity per employee and assist insurers in detecting emergent fraud patterns in order to reduce loses.
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investigation management, investigation management team, fraud, enterprise fraud management platform, fraud management, data, analytics, fraud detection, reduce loss, employee productivity, workflow, fraud analytics
    
IBM
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: IBM     Published Date: Jul 12, 2016
Join us for a complimentary webinar with Mark Simmonds, IBM big data IT Architect who will talk with leading analyst Mike Ferguson of Intelligent Business Strategies about the current fraud landscape. They will discuss the business impact of fraud, how to develop a fraud-protection strategy and how IBM z Systems analytics solutions and predictive models can dramatically reduce your risk exposure and loss from fraud.
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ibm, z systems, fraud loss reduction, fraud management, fraud prevention, fraud analytics, roi
    
IBM
Published By: IBM     Published Date: Jan 18, 2017
Predictive analytics has come of age. Organizations that want to build and sustain competitive advantage now consider this technology to be a core practice. In this white paper, author Eric Siegel, PhD, founder of Predictive Analytics World, reveals seven strategic objectives that can only be fully achieved with predictive analytics. Read this paper to learn how your organization can more effectively: Compete – Secure the most powerful and unique competitive stronghold Grow – Increase sales and retain customers competitively Enforce – Maintain business integrity by managing fraud Improve – Advance your core business capacity competitively Satisfy – Meet today's escalating consumer expectations Learn – Employ today's most advanced analytics ....and finally, render your business intelligence and analytics actionable.
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predictive analytics, increase sales, customer retention, fraud management, consumer expectations
    
IBM
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
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: 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: 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: 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: ParAccel     Published Date: Nov 15, 2010
This solution brief explains how Fidelity Information Services (FIS) executives realized that they needed an analytics database solution that could keep up with additional fraud complexity as well as much larger sets of data to improve detection rates.
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paraccel, analytic database, financial fraud analytics, fidelity information services
    
ParAccel
Published By: ParAccel     Published Date: Dec 16, 2010
This solution brief explains how Fidelity Information Services (FIS) executives realized that they needed an analytics database solution that could keep up with additional fraud complexity as well as much larger sets of data to improve detection rates.
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paraccel, analytic database, financial fraud analytics, fidelity information services
    
ParAccel
Published By: SAS     Published Date: Feb 29, 2012
In this white paper, Ian Henderson of Sword Ciboodle and Retha Keyser of SAS describe what that ideal can look like and how to achieve it.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics, it management, ondemand solutions, performance management, risk management, sas® 9.3, supply chain intelligence, sustainability management
    
SAS
Published By: SAS     Published Date: Feb 29, 2012
This paper presents technologies and recommendations for not only surviving, but thriving, as a marketer in today's demanding and dynamic business climate.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics, it management, ondemand solutions, performance management, risk management, sas® 9.3, supply chain intelligence, sustainability management
    
SAS
Published By: SAS     Published Date: Feb 29, 2012
This paper presents the 5 most common practices that result in losing a customer and how to avoid those pitfalls. You'll also learn how more customer-centric measures can help you deepen and grow relationships with your most valuable customers.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics, it management, ondemand solutions, performance management, risk management, sas® 9.3, supply chain intelligence, sustainability management
    
SAS
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