Register for one of Sparkling Logic’s upcoming webinars or watch on-demand webinars.
Watch On-Demand Webinars
When websites need to collect information for decision-making based on user responses people often think of using rules to drive the sequence of questions. Rules simplify the complex logic often required to drive these interactions however, they don’t have a mechanism for interacting directly with the application UI. In addition, most rule engines are stateless so the state of the conversation with the user has to be persisted in data and passed back to the rule engine for each interaction. Read More »
Learn how organizations are using decision management to make better decisions that more effectively manage risk and improve customer experience. Decision managmement has emerged as the key discipline to strategically manage automated business decisions. With decision management the code responsible for making decisions is treated as a separate asset. Decision management is to business decisions what process management is to business processes and database management is to business data. Read More »
The Insurance industry is an avid user of Decision Management technologies. When you think about it, the whole Insurance business revolves around decisions: Should I ensure this person? What premium should I offer? Is this claim justified? Furthermore, you can add levels of complexity due to the various lines of business. Clearly, underwriting a home policy does not compare to underwriting a life policy. In this webinar, we will illustrate specific use cases we encountered in the Insurance industry. Read More »
Certainly, business performance relies on consistent decision making. Decision Management technologies achieve just that. While Business Owners typically take responsibility for putting together strategies, data insight can add precision to these automated decisions. Indeed, Predictive Models like a credit score or willingness to repay constitute invaluable inputs to business rules in the Financial Services industry. On one hand, Business Analysts can collaborate with Data Scientists to brings these models to good use. On the other, Machine Learning ‘made easy’ can empower them. Read More »