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By: CA Technologies     Published Date: Jul 13, 2015
Issuers need to balance eCommerce payment transaction security and a smooth customer checkout experience. The crux of the matter is how to provide a seamless checkout experience for legitimate customers so they won’t abandon their transaction or use a different form of payment while at the same time stopping illegitimate attempts to transact. The use of behavior-based authentication to determine which transactions should be impacted by requiring the customer to go through additional means of authentication is critical for reducing customer friction while creating better assurance that the transaction is legitimate. Rules are an important component when providing this risk- and behavior-based authentication. When models are added, and used to guide the application of risk-based rules, the impact upon illegitimate authentication attempts can be greatly increased while the impact on legitimate customers is decreased, providing a better experience for the cardholder and loss reduction for
Tags : ecommerce, 3dsecure, risk analytics, behavioral
     CA Technologies
By: Lenovo and Intel     Published Date: Jul 10, 2018
The risk of cyber attacks and the cost of failure are increasing. Penalties associated with failure are only going to increase. And these challenges are compounded by increasing collaboration, use of cloud-based solutions, and an increasingly mobile workforce. Join experts from Forrester, Lenovo and Microsoft as they explore Forrester’s newly updated Zero Trust Extended framework. Then Lenovo covers how the four core components of its Data, Identity, Online and Device (DIODe) approach can minimize risk to data and critical IT. By taking these important steps toward a full Zero Trust Extended framework, you can: Protect the business from advanced threats Reduce the impact of breaches Easily support new business and operating models Rise to the challenge of evolving regulations like FISMA, HIPPA, PCI and GDPR
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     Lenovo and Intel
By: Interactive Intelligence     Published Date: Apr 23, 2014
If a contact center executive could have anything, it would be certainty… of contact demand, resource availability, operational efficiency, and of agent performance and customer experience delivery. But certainty in a contact center is nearly impossible, and in the absence of a crystal ball, mathematical models provide the next best thing. They alert, evaluate operational risk, and propose business and resourcing solutions. And now, the best of these models also determine expected experience delivery.
Tags : interactive intelligence, contact center, customer service, customer experience, cost, revenue, telecom
     Interactive Intelligence
By: Fiserv     Published Date: Nov 07, 2017
"In today’s ever-evolving lending landscape where loan quality and risk management challenge profitability and the customer experience, technology may be the key to thriving – both now and in the future. Winning financial services institutions will be the ones that transform their business models to place loan quality and risk management at the center of their operations. To facilitate continuous life-of-loan management, inclusive of the requisite data transparency and audit trails that support loan quality and loss mitigation, these institutions will implement and automate a loan completion process. Such a process will manage data quality and access to loan data and documents throughout origination, servicing and sale on the secondary market."
Tags : mortgage data quality, loan quality, loan data quality, mortgage quality, loan compliance, lending compliance, mortgage compliance, trid
     Fiserv
By: MarkLogic     Published Date: Nov 07, 2017
Business demands a single view of data, and IT strains to cobble together data from multiple data stores to present that view. Multi-model databases, however, can help you integrate data from multiple sources and formats in a simplified way. This eBook explains how organizations use multi-model databases to reduce complexity, save money, lessen risk, and shorten time to value, and includes practical examples. Read this eBook to discover how to: Get unified views across disparate data models and formats within a single database Learn how multi-model databases leverage the inherent structure of data being stored Load as is and harmonize unstructured and semi-structured data Provide agility in data access and delivery through APIs, interfaces, and indexes Learn how to scale a multi-model database, and provide ACID capabilities and security Examine how a multi-model database would fit into your existing architecture
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     MarkLogic
By: ServiceNow     Published Date: Jan 03, 2017
The scope and value that modern IT service delivery provides a business is increasing dramatically, according to a new research reportfrom Enterprise Management Associates (EMA). And yet in some organizations legacy ITSM systems contribute significantly to reduced credibility for IT departments who fail to integrate with and support important business concerns. This lack of modern IT service delivery creates multiple issues for the enterprise, including: Increasing divergence of IT and business performance Rising costs due to service delivery complexity Inability to measure and protect a business from potential risks Informed by extensive research and two compelling deployment narratives, this report examines what EMA calls “next-generation ITSM” and its contributions toward optimizing changing IT and business requirements. EMA contrasts these advances with the risks of staying with legacy ITSM models and then evaluates and itemizes the risks of “doing nothing” by allowing legacy ITS
Tags : it management, it automation, it ticketing, help desk, service desk, itsm, it service management
     ServiceNow
By: IBM     Published Date: Feb 05, 2015
Discovery Health ... Predictive analytics used to craft preventive programs that keep members healthier and costs lower.
Tags : predictive analytics, preventive programs, predictive risk management, clinical risk models, web analytics, business intelligence, market research, usability
     IBM
By: IBM     Published Date: Feb 02, 2009
A comprehensive solution for leveraging data in today's financial industry. Most organizations realize that the key to success lies in how well they manage data—and the banking industry is no exception. From customer statistics to strategic plans to employee communications, financial institutions are constantly juggling endless types of information.
Tags : ibm, information management software, leveraging data, dynamic warehousing, data management, improve customer service, real-time risk analysis, analytics capabilities
     IBM
By: IBM     Published Date: Aug 08, 2012
With tight budgets, it isn't easy to create the operational dexterity needed to thrive in a competitive marketplace. View this demo to find out how IBM® SPSS® solutions for predictive operational analytics help manage physical and virtual assets, maintain infrastructure and capital equipment, and improve the efficiency of people and processes. By using your existing business information, IBM SPSS software can help you: predict and prevent equipment failures that can lead to disruptive, costly downtime; quickly identify and resolve product quality issues to mitigate risks and reduce warranty costs; optimize product assortment planning to increase revenue, reduce working capital requirements and improve the return on inventory investments; and act to retain your best employees by developing predictive attrition models to identify the workers at greatest risk of leaving the organization.
Tags : ibm, technology, predictive operational analytics, spss
     IBM
By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes.
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     TIBCO Software
By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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     TIBCO Software
By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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     TIBCO Software
By: BMC Software     Published Date: Oct 23, 2014
In a first-of-its-kind study, IDC has docu­mented the costs of business risks cre­ated when business and IT teams fail to communicate effectively. Hear how enterprises are addressing the friction associated with IT needs and the gaps and opportunities that exist between business needs and IT service delivery models.
Tags : costs and risks, communication, enterprises, it service delivery models
     BMC Software
By: IBM     Published Date: Nov 19, 2014
Risk Management: General: Partially cloudy: the benefits of hybrid deployment models
Tags : ibm, risk management, big data, data management, operational risk, event data, risk aware, risk solutions
     IBM
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.
Tags : akamai, predictive, online advertising, tracking pixels, online shopping, in-market, site visitors, performance marketing
     Akamai
By: SAS     Published Date: Aug 04, 2016
Banks have been using credit scoring models for over five decades, so managing the life cycle of models is nothing new. Most have had some kind of process in place to ensure the models they develop are robust, validated and monitored from a performance perspective and that decision makers have confidence in them. In recent times, however - partly in response to the credit crisis in 2008 - the discipline of model risk management (MRM) has become more formalized and rigorous, driving the need for enterprise-level model information management systems. The regulatory scrutiny being applied to them is intensifying and spreading globally, with US and European regulators leading the charge. For example, whereas regulators were previously more interested in the numbers they were provided, now more regulators want to have a core understanding of the models banks used to generate these numbers.
Tags : best practices, risk management, finance, security, info systems
     SAS
By: Centrica Business Solutions     Published Date: Aug 14, 2018
It's demanding times for businesses. Facing risks as diverse as extreme weather and cyber-attacks, ?rms are focusing more intently on business continuity plans. At the same time, the digital revolution is changing lifestyles, disrupting business models and acting as a catalyst for change. Energy itself is undergoing a transformation, as generation moves towards renewables and decentralization, while technological advances present new opportunities. Energy now has the potential to deliver competitive advantage, to enhance sustainability and resilience, and to power innovative business models. But equally, the range of new options available is making the management of energy more complex. Read this thought leadership paper to find out how energy can drive your business strategy.
Tags : business, strategy, energy, efficiency, performance
     Centrica Business Solutions
By: Hewlett Packard Enterprise     Published Date: Jan 31, 2019
"Extracting value from data is central to the digital transformation required for businesses to succeed in the decades to come. Buried in data are insights that reveals what your customers need and how they want to receive it, how sales, manufacturing, distribution, and other aspects of business operations are functioning, what risks are arising to threaten the business, and more. That insight empowers your businesses to reach new customers, develop and deliver new products, to operate more efficiently and more effectively, and even to develop new business models. "
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     Hewlett Packard Enterprise
By: Lumension     Published Date: Mar 31, 2012
This whitepaper will take an in-depth look at virtualization technologies, security risks, and virtualization technology management models.
Tags : vulnerability management, patch management, vulnerability assessment, data protection, data loss, data theft, endpoint protection, compliance
     Lumension
By: Trillium Software     Published Date: May 19, 2011
Insurers must combine information from disparate systems, applications, and business units to create an enterprise view of risk. By developing a process to incorporate geocodes into location intelligence, insurers can build a more accurate assessment of risk.
Tags : trillium software, underwriting risk, insurers, location intelligence, geocodes, risk management, granularity, risk models
     Trillium Software
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