How NGA’s system uses Predictive Analytics to increase customer value
Artificial Intelligence in the Financial Sector
Predictive Analytics in the Financial Sector using RiskSecure
NGA is the leading provider of AI and Data Insightful systems that enable businesses to intelligently automate their back and front-office processes. The basic objective of the NGA platform is to have a hub exclusive centralized decision making and housing two complementary components to the banking customers.
A predictive analytics engine that ingests and analyzes diverse data types—including unstructured “big data”—to develop predictions about the likely behaviors of individual customers. In the case of predictive analytics in banking, this may mean projections about a particular customer’s receptiveness to different marketing offers, or about their propensity to repay outstanding debt. For example, together with this predictive analysis, the engine also supports adaptive analysis whereby projections are continually updated and adjusted in response to a customer’s interactions with the business.
There is a decision engine that is fully automated and it helps to configure business rules into analytics and contextual information for determining the next course of action at a given moment to make the customer interaction more feasible. The engine supports a range of Decisioning methods including declarative rules, decision trees, decision tables, and more.
The arrival of Big Data has resulted in many organizations unable to stay ahead of the market and analyze their data resulting in their sheer inability to remain competitive.
Big Data challenges demand a brand new approach to analytics in order to handle the increasing volume, velocity, and variety of Big Data.
NGA has developed its own internal methods and processes over the past few years to address big data issues and risks faced for both structured and unstructured data processing requirements.
Innovative Approaches to Supplier and 3rd Party Risk Monitoring
Today’s marketplace is highly competitive and it’s critical for companies to think of innovative new ways to streamline their operations, increase efficiencies, and optimize productivity in order to stay ahead of the competition.
One such aspect of business that is often overlooked when attempting to achieve greater efficiency in supply chain management. Many organizations only pay attention to what is going on within their facilities and don’t manage the entire chain of activities that are being completed by outside organizations to get a product to the end-user.
Social media analytics can improve your organization’s 3rd party risk monitoring. When you have a more efficient and stable supply chain, you can enhance your customer satisfaction. The ripple effect of using social media to improve your supply chain management can expand outwardly across virtually your entire organization, which is great for business.
With visibility of risks across the supply chain, and a good understanding of the companies involved, it’s impossible to fully assess the likely consequences of disruptions or target mitigation efforts. NGA uses visual risk mapping, data mining, and NLP techniques, monitor near real-time data and social media, and use predictive analytics to forecast future outcomes
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