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.
collectd is an open source daemon that collects system and application performance metrics. With this data, collectd then has the ability to work alongside other tools to help identify trends, issues and relationships not easily observable.
Read this e-book to get a deep dive into what collectd is and how you can begin incorporating it into your organization’s environment.
From protecting customer experience to preserving lines of revenue, IT operations teams face increasingly complex responsibilities and are responsible for preventing outages that could harm the organization. As a Splunk customer, your machine data platform empowers you to utilize machine learning to reduce MTTR. Discover how six companies utilize machine learning and AI to predict outages, protect business revenue and deliver exceptional customer experiences.
Download the e-book to learn how:
Micron Technology reduced number of IT incidents by more than 50%
Econocom provides better customer service by centralizing once-siloed analytics, improving SLA performance and significantly reducing the number of events
TransUnion combines machine data from multiple applications to create an end-to-end transaction flow
Predictive IT is a powerful new approach that uses machine learning and artificial intelligence (AI) to predict incidents before they impact customers and end users. By using AI and predictive analytics, IT organizations are able to deliver seamless customer experiences that meet changing customer behavior and business demands. Discover the critical steps required to build your IT strategy, and learn how to harness predictive analytics to reduce operational inefficiencies and improve digital experiences.
Download this executive brief from CIO to learn:
5 steps to an effective predictive IT strategy
Where AI can help, and where it can’t
How to drive revenue and exceptional customer experiences with predictive analytics
Read this white paper to discover how predictive analytics and cognitive commerce make it possible to get instant access to integrated information and actionable insights so you can deliver superior—and profitable—interactions with customers.
Traditional business intelligence (BI) looks backward at what has happened. In today’s marketplace, enterprises need to look ahead. In this eGuide from TDWI, you'll discover how advances in predictive analytics are enabling organizations to use insights about the past and present to make accurate predictions about the future.
Learn why advanced analytics tools are essential to sustain a competitive advantage. This white paper reveals seven strategic objectives that can be attained to their full potential only by employing predictive analytics.
As your business transitions to a digital enterprise, you can start to give your employees, partners, and customers immediate, data-driven, and even predictive insight into what’s going on – in a way that’s relevant for them. Strategic use of on premise and cloud-based analytics accelerates this process. Read the solution brief to see how SAP is continuing to invest in on premise solutions as part of their effort to reimagine analytics.
New channels and cashless payment ecosystems have created greater risk for financial institutions; the increase in fraudulent activities has compounded the need for more rapid detection and counter measures.
Please view this webcast and learn:
- The key challenges financial institutions face in rapidly detecting, responding and countering new fraud schemes
- The value a cognitive computing approach offers an institution; enabling them to make swifter, more accurate decisions while providing more control and transparency
In this report you will learn how to enhance your customer relationships across all your channels and touch points, produce personalized customer offers and learn from real-world case studies across various industries.
Read this white paper to discover how predictive analytics and cognitive commerce make it possible to get instant access to integrated information and actionable insights so you can deliver superior-and profitable-interactions with customers. You'll learn: What it takes to uncover hidden trends and explore relationships across disparate data sources using natural language queries Ways to use in-depth insight to create highly relevant campaigns and content that's aligned with individual customer behaviors and preferences How to take product recommendations to new levels of accuracy with pinpoint prediction and targeting.
Read this white paper to discover how predictive analytics and cognitive commerce make it possible to get instant access to integrated information and actionable insights so you can deliver superior-and profitable-interactions with customers.
Learn how to create powerful analytic apps with IBM Cloudant, dashDB and Apache Spark. This presentation will contain demos of real-life use cases e.g. machine learning predictive analytics, Graph-parallel computation and more.
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.
See how you can turn data into actionable insights with predictive analytics. Take our brief assessment to learn which analytical capabilities will enable you to find the greatest value in your data and make confident, accurate business decisions.
IBM SPSS predictive analytics solutions help uncover key predictors that lead to online student success or failure. Identifying specific issues early, target intervention measures for at-risk students, and take the appropriate steps to help improve online student graduation rates.
In this on-demand webinar from the Institute of Management Accountants (IMA), Sherri Liao of The Hackett Group and Jim Collins of IBM discuss the steps your organization can take to link financial planning to operational decision making more effectively. You’ll hear about:
Simplifying and amplifying reporting
Optimizing decision-making: Predictive vs. historical analytics
Aligning finance and operations
Reporting beyond finance to include cross-functional measures of performance
The path to building a World-Class finance organization
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.
Tips and best practices for data analytics executives
Organizations today understand the value to be derived from arguably their greatest asset—data. When successfully aggregated and analyzed, data can unlock valuable insights, solve problems, improve products and services, and help companies gain a competitive edge. However, analytics executives face significant challenges in collecting, validating and analyzing data to deliver the right analytic insight to the right person at the right time.
This e-book is designed to help. First, we'll explore the growing expectations for data analytics and the rise of the analytics executive. Then we'll explore a range of specific challenges those executives face, including those around data blending, analytics, and the organization itself, and offer best practices and strategies for meeting them.
We'll also provide a short overview of TIBCO Statistica, an easy-to-use predictive analytics software solution designed to turn big data into your bigg
A perfect storm of legislation, market dynamics, and increasingly sophisticated fraud strategies requires you to be proactive in detecting fraud quicker and more effectively.
TIBCO’s Fraud Management Platform allows you to meet ever-increasing requirements faster than traditional in-house development, easier than off-the-shelf systems, and with more control because you’re in charge of priorities, not a vendor. All this is achieved using a single engine that can combine traditional rules with newer predictive analytics models.
In this webinar you will learn:
Why a fraud management platform is necessary
How to gain an understanding of the components of a fraud management platform
The benefits of implementing a fraud management platform
How the TIBCO platform has helped other companies
Unable to attend live? We got you. Register anyway and receive the recording after the event.
Today's energy, environment, and utility companies face an unfamiliar landscape in which they must integrate alternative energies, expand situational awareness across the system, and deepen their relationships with customers-all while continuing to deliver reliable, safe, and affordable electricity, gas and water to everyone.By combining predictive analytics with IoT, cloud and mobile technologies, utilities companies can Lower costs, improve operational efficiency and increase equipment reliability.
Moving Beyond Traditional Decision Support
Future-proofing a business has never been more challenging. Customer preferences turn on a dime, and their expectations for service and support continue to rise. At the same time, the data lifeblood that flows through a typical organization is more vast, diverse, and complex than ever before. More companies today are looking to expand beyond traditional means of decision support, and are exploring how AI can help them find and manage the “unknown unknowns” in our fast-paced business environment.
High-performing organizations leverage the power of analytics by channeling their efforts in four areas: focus, adopt, adapt, and activate. These companies have embraced a new paradigm that promotes agility, fast execution, and lasting organizational change.