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Why Oracle Intelligent Advisor?

Oracle Intelligent Advisor  

Oracle Intelligent Advisor (OIA) is a powerful rule engine that supports complex decision-making and calculations. The use-cases for OIA are endless. Whether you need to enable user-friendly self-service, improve personalized assistance through chatbots, reduce the workload of customer service agents, provide decision analytics, or fully automate decision-making OIA comes to the rescue.  

 

Why OIA? 

Consistent decision-making 

OIA ensures consistent decision-making across various communicational channels and reduces the possibility of human error. All the above-mentioned use cases may be combined in a project and OIA guarantees that end-users receive the same result through different channels.  

For instance, a user may get assistance from a chatbot or fill-in an Interview to determine eligibility for a certain bank loan. Once he is reassured by the decision and explanation, he receives through these self-service channels he hands in his application.  The agent handling his case at the bank utilizes the automated decision-making process and at the push of a button he is presented with the exact same decision and explanation the client had received.  

Consistency is a guarantee because the core of the rule engine is the same, regardless of the end user or the channel: the rules. 

 

Personalized service 

OIA allows customers to get personalized advice by completing an OIA Interview on a self-service portal. The client can pick what benefit they are applying for on a user-friendly interview screen. 

The interview changes dynamically based on what data the customer provides. For instance, once the customer selects whether they are applying for a house loan or a car loan, the interview will only ask for the input data that is relevant for the chosen loan type. 

In case the client provides data that rules out eligibility – for instance the client is not employed when applying for the loan – the interview immediately returns the negative decision with the relevant explanation. 

Dynamic interviews ensure that the customer receives the decision in the shortest amount of time with the minimum number of clicks.  

 

Reduced workload for agents 

OIA interviews may also be designed for the use of call-center agents. Supporting the work of agents by OIA can significantly decrease the time required to process a case. By making use of OIA’s input validation, consistent decision-making, and detailed explanation on how a decision was reached the likelihood of human error can also be reduced.  

 

Automating complex decision-making 

Depending on the purpose of the project OIA may run in the background without a surface. OIA does not have its own database. It collects the data from other services and returns the answer. The rule engine is able to make a decision using thousands of input values within milliseconds and send back the result and the relevant explanation. 

 

Rules written in natural language 

OIA rules are written in Microsoft Word and Excel. OIA stands out from other rule engines because in OIA rules can be written in natural language. As a result, no serious IT background is necessary in order to build an effective decision-making system. 

The fact that the rules are written in easily understandable language greatly promotes the cooperation between the clients and developers. OIA supports various custom languages in addition to English. 

 

Built-in functions 

Built-in functions enable complex calculations and logic in the rules. The main types of built in functions are numerical functions, date and time functions, text functions, entity and relationship functions and temporal reasoning functions. 

Temporal variables 

A specialty of OIA is handling temporal variables, that is variables the value of which change over time. Therefore, it’s easy to handle past changes in the rule engine and calculate the margin that results from these changes. 

Built-in regressive testing  

OIA allows for saving test cases and running them at a click of a button, guaranteeing that during a new development no bugs can hide among the rules.  

The test cases are created in excel files, using color-coded input, expected and actual values. The user-friendly surface enables close cooperation with the client while creating test cases. 

The test cases can range from unit tests written to guarantee that small parts of the rules work as expected to complex test cases that cover all the rules and the whole decision-making process. 

 

Conclusion 

Oracle Intelligent Advisor is a powerful rule engine that can be implemented in various business scenarios. OIA ensures quick and consistent decision-making across multiple channels. It can speed up the decision-making process, reduce the workload of agents and consequently reduce costs. 

The fact that OIA can read rules from documents written in natural language simplifies the development process, allows for easier communication between developers and customers and strengthens cooperation. 

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