Improve operational decisions and business processes with real-time context
Ever wish you had a secret weapon, like Superman’s x-ray vision? Something that would give you an edge on the competition and help you detect opportunities they just don’t see so you can act before they do? Or spot risk and fraud from a few weak signals―not after the damage is done?
We recently introduced the latest version of IBM Operational Decision Manager Advanced (IBM ODM Advanced), which includes two high-performance, scalable capabilities that can help you differentiate in the marketplace. This version is enhanced with rules and insights and offers more control for business users, but the most innovative value comes from Decision Server Insights (DSI), the real-time actionable insight capability, making your Smarter Process that much smarter. You can make more accurate decisions by applying business rules to a wide array of data turned into insight.
Here’s how that works, using a fraud detection example. External events continuously enter the system, and then DSI kicks in to:
- Sense what is happening. These events are coming in from loosely connected systems of engagement (mobile, social or connected cars, for example), business processes, beacons and more. Big data, little data―it’s all bombarding the system.
- Build the context. In practice, when an event comes to the DSI runtime, it is routed to the entities that play a role in that event. A cash withdrawal event routes to the entity representing the customer and to the entity representing the ATM. Once there, it will be kept for further correlation as long as required.
- Decide what to do. This means applying the rules and the pattern that reacts on the triggering event, understands the underlying situation, identifies opportunities and risks and prescribes the next step.
- Act. As soon as a rule decides it is time to act, the DSI platform sends an outgoing notification. As a result, the external devices, ATMs, agents, mobiles block a card, call a customer, show a pop-up notification―whatever is required.
Decisions are made in real-time and in context. The context attached to each entity―whether it is the customer of a retail bank or a hospital―utilizes predictive analytics to provide insight into past events, the present state of the entity or future behavior. What products has the customer purchased before? How many emergency rooms are available in the hospital now? What is the propensity of the customer to buy this product?
You still need the more traditional rules capability when processing individual transactions and batches, because your organization has to deal with increasing regulation as well as outside competition. DSI helps you take things one step further to decide when it is time to act. For example, DSI is great at deciding the right time to propose a dress to the customer, but ODM rules helps build a rule service that actually selects the right dress. That decision service is stateless and is made of tens to thousands of decision tables and natural language rules sequenced by a rule flow.
DSI also plays well with existing business process management (BPM). It can trigger a new instance of a fraud management process, for example, when it detects a fraud. DSI can also detect business-relevant situations across multiple processes. For example, assume a bank client living in London is visiting the local branch to meet with his advisor. That process generates two time-stamped and geo-localized events: “Meeting Starts” and “Meeting Ends.” Now, if an identity thief attempts to withdraw money from an ATM in the US less than 10 hours after the meeting ends, an alert should be triggered.
So the point is this: You can get ahead of the competition by detecting opportunities and risks they don’t see, and you can make accurate, real-time decisions more quickly based on insight.
Next time, we’ll take a deeper look at the architecture of DSI.