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Harnessing the power of predictive analytics

How does your company use Data to gain competitive advantage in the market? Leading Financial Services companies deploy predictive analytics to digest, study, and review business trends of the future. Yet many come up short on making use of its capabilities to drive business value.

Predictive applications help Financial Services companies achieve and exceed objectives such as providing top-rated customer experiences or transactions, achieving a healthy ROI, optimize pricing and earning increased revenues. At their full potential, they have the capacity to influence decision-making at the transactional and strategic levels.

Organizations utilize predictive models to add value in many areas, including:

  • Extracting, gleaning, and manipulating patterns embedded within historical and transactional data to highlight present and future risks, threats, and opportunities
  • Collect relationships among multiple factors to enable risk assessment or evaluation of potential outcomes
  • Utilizing internal and external data to attract and retain the most-profitable customers, identify issues and concerns in real-time, and elevate the customer’s overall experience and satisfaction

The promise of generating profitable results from predictive analytics hinges on integrating a strong analytics operating model throughout your organization.

Understanding customer behavior is vital to creating strategies and plans to define desired outcomes. Predictive analytics offers the tools for the organization to anticipate customer needs before they surface.

Making the investment in predictive analytics
Predictive analytics enable companies to reap benefits beyond the capabilities of their existing business intelligence platforms. Companies that utilize advanced machine intelligence to draw upon valuable signals and patterns from enormous data flows and convert them into a source of analytically-enhanced instruction quickly distinguish themselves.

To most Financial Services organizations it’s not a question about “IF” to invest in Predictive Analytics but rather “HOW” and “WHEN”.

As predictive analytics evolves into a mainstream tool, users face a common challenge: How do you ensure your investment in predictive analytics will result in meaningful and direct impact on business outcomes and performance?

At the same time, data sources and capabilities continue to become wider and richer, making it harder for users to ferret out and determine useful data that holds value for the company’s bottom line. Predictive analytics offers clear value in performing this function. In-memory computing tools can collect large amounts of data, which were previously stored in relational databases, and make them available through an advance memory store. By embedding analytics into in-memory and interactive data visualization platforms, you can allow users access to complex data through interfaces that offer quick and easy navigation and development of individual models.

But to extract value from Analytics, you must expand your focus beyond technology, data storage or capture. How will you analyze that data? How will discovered knowledge inform business operations decisions and processes? To be successful, you must develop an operating model that begins with the end in mind.

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