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.
Published By: TeamQuest
Published Date: Jul 11, 2014
In this whitepaper you will learn about the following:
• Analytics and today’s optimization challenges
• What REALLY matters
• Desired state and results
• Methodology and ideation examples
– Business and service aligned
– Automated and predictive IT analytics
Download to learn more!
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.
Companies using predictive analytics enjoyed a 75 percent higher click through rate and a 73 percent higher sales lift, according to a 2011 Aberdeen Group report. Download this report to see how companies are implementing predictive analytics to get these amazing results.
Faced with a downturn in funding due to the global economic recession, nonprofit organizations need to improve their donor management capabilities so they can compensate for the reduction of government funding and diminishing level of donor contributions. Predictive analytics provides an effective way to understand and anticipate donor needs in order to increase the success of fundraising and marketing campaigns. Using this technology, nonprofits can gain a significant return on investment by increasing donor contributions, reducing costs and building stronger donor relationships over time. In this white paper, you'll learn how predictive analytics can help nonprofits achieve their funding goals by significantly improving the way they identify, manage and build relationships with donors.
Join fundraising consultant and author Joshua Birkholz and IBM for an overview of the impact predictive analytics can have on your fundraising programs. We'll explore how this data-based approach can help you
Discover how using predictive analytics can help your company convert prospects and cross-sell to existing customers. The campaign optimization capabilities provided with predictive analytics offer an unprecedented level of targeting and coordination across all channels - quickly resulting in decreased costs and increased revenue.
Most CRM systems rely on historical analytics that provide a "rear-view mirror" of your customer relationships, offering little support for the decisions that shape the future. With predictive analytics, you can meet your customers' evolving needs with forward-looking insights that anticipate changes in customer attitudes, preferences, and actions. This white paper from IBM describes how a set of five predictive imperatives can help ensure that your company maximizes the value of its customer relationships and sustains higher levels of revenues and profits.
With customer analytics-including predictive analytics, social analytics, business intelligence, and decision management-companies are empowered to improve the customer experience and maximize business outcomes by being proactive, rather than reactive. Comments made in social channels about a perceived problem with a checkout tool on a company's website, for example, can alert company decision-makers about a potential issue before it hits the contact center.
Databases and information management systems let you describe, categorize, store, modify and analyze data. What if you could do the same with decisions? Your systems could learn from previous choices and manipulate them to fit new parameters to intelligently mold future decisions made by executives, everyday business users and even your systems to optimize outcomes. Read this a specially selected excerpt from James Taylor's new book, "Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics" to discover the guiding principles for building decision management systems that can help your organization differentiate itself from the competition at virtually every decision point.
View this demo to find out how IBM SPSS® solutions for predictive customer analytics can deliver deep customer insights that help you tune your marketing efforts-effectively and efficiently attracting new customers, nurturing customer relationships and retaining ideal customers. Watch how IBM SPSS software uses existing customer information to help you do the following: Identify your best customers for targeted marketing programs with customer segmentation, cluster and profiling techniques; confidently predict which customers will respond to your offers with powerful predictive models; get more out of every customer interaction by delivering real-time, predictive intelligence to front-line decision makers; and enrich and deepen your customer insight with social media analytics.
As a claims management professional, you have to deal daily with formidable - and sometimes competing - challenges: provide superior customer experience; achieve operational excellence and cost containment; and effectively manage risk. Predictive analytics can help you improve each of these three outcomes, but more importantly, it helps strike the right balance among these three objectives for each new claim received. Read this white paper from IBM to learn about applying predictive analytics to claims management, including the typical ROI achieved, how embedded analytics improves decision making, and technology components of a predictive analytics solution.
Every day, people in your organization are struggling to make the right decisions - working with customers, partners, and each other - because they simply can't use all available data. There's too much of it for humans to internalize, understand, and apply in real time. That's why organizations that automate and optimize decisions informed by predictive analytics have a significant advantage over competitors. Read this IBM white paper and discover how decision management can help you effectively leverage your business data to support faster, more-accurate real-time decisions in virtually every area of your business. You can learn the following: the common types of business decisions and how decision management affects them; why most decisions today aren't based on any real business insight; benefits of decision management-what it is and how to adopt it; and the role of predictive analytics in effective decision management.
While economic recovery is clearly in process, your capital and operational budgets are still extremely tight. At the same time, your maintenance organization is being pressured to take a stance of zero tolerance toward safety incidents while reducing maintenance costs and minimizing asset downtime. Read this in-depth Aberdeen Group report, based on responses from 117 executives of successful companies, to find out how best-in-class businesses are proactively managing these challenges. You'll learn these techniques for optimizing maintenance and operations-and more: creating a culture of collaboration among teams across your enterprise; empowering decision makers with appropriate, highly accurate metrics; and leveraging predictive management and analytics to manage assets throughout their life cycle.
Your goal is clear-produce high-quality goods while optimizing resources at every step of production. And in today's uncertain economy, cost-control efforts may never have been more important. Unscheduled downtime because of equipment failure can have a serious impact on your organization's bottom line. Download this white paper from IBM, and learn the basics of predictive maintenance, the benefits it provides manufacturing operations and the underlying technologies that make it possible. Predictive analytics helps you in a number of ways: identify when equipment is likely to fail or need maintenance and take action to maximize uptime and reduce future warranty claims costs; optimize allocated labor resources and spare part inventories, helping eliminate undue maintenance, prevent downtime and reduce inventory costs; and determine why certain production runs fail more often than others, identify the cause and analyze whether those runs warrant a recall.
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.
Read this excerpt from James Taylor's new book, "Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics" to discover the guiding principles for building decision management systems.
This paper discusses the challenges of managing applications in highly dynamic IT environments such as public and private Clouds. Modern enterprise applications are engineered for agility and are frequently deployed over flexible IT infrastructures.
With the advanced analytics capabilities in Adobe Analytics and the testing and targeting capacity of Adobe Target, it’s easier than ever to realise the potential of data-driven marketing. From creating a complete view of each customer across touchpoints and along their journey, to using predictive analytics, advanced anomaly detection and machine learning to understand behaviours and needs, you can use data to plan, create and optimise the experiences that matter to you and your customers.