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Automated decisions are at the heart of your business processes. Join us for a one hour tour of Sparkling Logic’s SMARTS end-end, low-code no-code Decision Management Platform.
In this webinar we’ll show you how you can use SMARTS to capture, automate, and evolve your critical business decisions using data, machine learning, and business rules.
Through live demonstrations, you will learn how to manage your interactions with customers, manage risk and fraud, ensure compliance, and dynamically configure and price your products and services, and much more.
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As part of the decision lifecycle, business analysts obviously start by authoring their decision logic. As they progress, testing rapidly comes to the forefront. How do you ensure that your decision logic is correct?
Decision logic is not software code. As a result, you can’t be satisfied with testing tools and techniques that software developers use. Testing decision requires a different approach, different techniques, and different tools. Granted, ensuring that your decision service can compile is useful. But, the end goal is really to ensure that your decision logic complies with your business objectives.
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Rating engines, just like scoring engines, pricing engines, compensation calculations, claims payment calculations, and many other types of calculation engines, aim to calculate fees or costs. Besides this commonality, they also share some complexity on the fine prints.
For example, insurance underwriters and lenders alike manage pricing sheets, often in the form of a spreadsheet. More often than not, these spreadsheets can contain thousands or tens of thousands of rows. While runtime performance may be a concern, maintainability is certainly a priority. Furthermore, the pace of change requires additional tracking and management to roll these rates over disparate geographies.
Over the years, the implementation of a rating engine has relied on different technologies. As of today, the debate still continues: can you use business rules for a rating engine? The definitive answer is yes. Read More »
You think that authoring business rules is difficult? If you attend a decision management show, you will likely hear many business analysts share their frustration while struggling with their first rules project. For instance, I remember vividly ever-lasting conversations aimed at defining what a rule is. As a consequence, I made it my personal mission to address this challenge. Business analysts should be able to log into their decision management tool and feel confident.
Clearly, authoring decision logic is not rocket science, but the tooling you use plays an important role. In other words, if that tool looks like a software development environment, it will only feel intuitive to software developers, which, as a business person, you might consider rocket science! Overall, look for advanced capabilities that support what you need, as a business analyst:
- Get started writing Business Rules intuitively in the context of data
- Adapt your view depending on the task at hand, switching from text to a decision table, tree or graph
- Combine business rules with very large MS Excel spreadsheets for efficient lookups
- Design a business app, for those that need to access the decision logic in their own terms
The Federal Reserve defines credit risk as the potential that a borrower or counterparty will fail to perform on an obligation. Under the umbrella of credit risk management comes the critical and sensitive origination decision.
In this webinar, we will illustrate specific use cases we encountered in credit origination. Read More »
All in all, the end goal in most industries is to increase business performance. In financial services, the objective is to increase the portfolio while keeping risk as low as possible. As another example, the general wellness of the members is paramount in the health care industry. Also, compliance is critical for flourishing operations of regulated industries.
Simulations can prepare you for what is to come, assuming that past behavior is a good prediction of the future. Yet, uncertainties might disrupt your expectations. At some point in time, tracking your business performance real-time becomes an imperative. Read More »
New to decision management? Or looking for best practices? Look no further. As a result of the constant request for tips and recommendations, we have compiled the essential Decision Management cheat sheet. With 12 design tips, your team will start their journey on the right track, saving time and energy. 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 »
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 »