Published By: OutSystems
Published Date: Apr 10, 2014
The webinar features a complex-made-simple, real-world example from Don Griest at FICO, the leading predictive analytics and decision management software company. Don discusses how the OutSystems Platform is helping FICO rapidly deliver solutions with superior quality and unprecedented time to value, thus opening up new markets for the company.
Published By: Aon Hewitt
Published Date: Aug 02, 2016
As the trend of moving to the Cloud continues to flow from business function to business function, other trends are emerging. As organizations transform to eliminate complex functions, standardize and integrate systems to reduce costs, and minimize nonvalue add activities, they are challenging themselves to get the most from their investment. The shift from transactional to strategic, and from reporting to actionable and predictive analytics, positions companies for growth like never before. Many organizations look to break down silos, not only within their company but also within their industries, to share lessons and leverage efficiencies from others’ learnings. Our recommendation is to start by breaking down any silos that exist between finance, HR, and IT within your organization today—and discover what moving to cloud and truly adopting the SaaS lifestyle can do for your organization.
Download this free e-guide to gain an understanding of predictive analytics concepts, how to align your data sources to unlock the value of the data in your organization, analyze the correlations, and reap the benefits of analytics in optimizing sales performance.
This paper from IBM describes how to build a proactive threat and risk strategy based on predictive analytics; examples of how organizations used predictive analytics to minimize the negative impact of risk and maximize positive results; and steps to advance your organization's use of predictive analytics to combat threat and risk.
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.
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.
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.
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.
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.
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.
Published By: Mintigo
Published Date: Sep 05, 2018
One of the most common use cases for AI in B2B is to make predictions about which accounts are most likely to buy and which leads are most likely to convert. However, use cases for AI are being extended beyond predictive account and lead scoring to include decision-making and process automation as well. Download this SiriusDecisions technology perspective on Predictive Analytics and Artificial Intelligence Technology to learn more.
This paper will cover:
• The benefits, evolution and capabilities of AI technology solutions for B2B organizations
• The core and extended capability groups of AI
• The business priorities supported by AI
Fill out the form to get your free copy!
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.
This paper will outline the value and methods involved in data mining across both quantitative and qualitative data. In addition, it will describe the data transformations necessary before doing such work, and the tools that are particularly valuable for mining mixed data types.
Learn what criteria distinguished certain companies as top performers within the SMB sector, the factors to consider when assessing your organization's BI competency and the required actions to achieve best-in-class performance.
This paper defines predictive analytics, then details ways this type of analytics can be applied to marketing, risk, operations and more. It also includes information relevant to a wide variety of industries - from manufacturing to hospitals.