Advanced Case Management with IBM Tooling - Part 2 (Entity Analytics)

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1 Advanced Case Management with IBM Tooling - Part 2 (Entity Analytics) Introduction and Architecture Overview Rishi S Balaji is an IBM accredited Application Architect with 11 years of experience in design and development of IT solutions. His area of expertise ranges from product development to consulting and asset development in areas such as SOA, Case Management and Business Intelligence using JEE and related technologies. Reach out to him at ribalaji@in.ibm.com Kamini K Katiyar is an IBM certified FileNet Application Developer with over 3.5 years of experience in FileNet suite of products and over 5.5 years of experience in IT. Area of expertise lies in Enterprise Content Management and Content Analytics. Reach out to her at kakatiya@in.ibm.com Ramya Prasad is a business intelligence professional at IBM GBS with over six years of experience in the IT industry. She has extensive experience working with BI solutions such as DataStage, Abinitio, Cognos and Case Manager. with deep database skills on Oracle and DB2. Her domain of experience includes the financial and industrial sectors. As an accomplished innovator, she has one filed patent and five published disclosures. Reach out to her at ramypras@in.ibm.com I B M 6 / 1 3 / By Rishi S Balaji, Kamini K Katiyar, & Ramya H Prasad [This article is the second in the three part series of articles on developing an advanced case management solution using IBM products. The first article provides an introduction and architectural overview of an advanced case management solution. The second article shows how to enrich case data by integrating entity analytics, to the case management solution.] Link to first part: rworks/groups/service/html/communityview?com munityuuid=e8206aad-10e2-4c49-b00cfee #fullpagewidgetid=wf2c4e43b120c _4ac7_80ae_2695b8e6d46d&file=730a263f-6424-

2 2 Advanced Case Management with IBM Tooling - Part 2 (Entity Analytics) Introduction to Entity Analytics in Case Management Entity Analytics deals with identification of individuals and relating them through the data that has been collected about their attributes. Entity analytics is primarily used in government and financial case management solutions for the purpose of fraud detection. This part of the series on advanced case management shows how to use the results of analytics in a case management solution. Cases are typically created for entities specific to the industry. For example, in the banking industry, cases are created for customer entities. Entity analytics plays a key role in case management solutions in the following ways: It helps in screening entities against known lists based on culture-specific name data and linguistic rules. The results of the match can be used to decide whether or not a case needs to be created for further investigation. It helps in the unique identification of entities in the case management system. This in turn is used to avoid duplication of cases by merging similar cases. It maintains relationships between entities. This information is used as part of case data to enable case workers in assessing a specific entity based on the other entities related to it. For example if a customer A is related to a blacklisted customer B, the case worker may decide to escalate the case to a senior analyst for further action. It helps in linking cases to each other based on the relationship of the entities for which the case has been created. The primary IBM products which will be used for entity analytics are IBM InfoSphere Identity Insight (here after referred to as II) and IBM Global Name Recognition (here after referred to GNR). The following figure summarizes the above mentioned points and illustrates the functional integration of entity analytics and case management. Figure 1: Case Management and Entity Analytics 2

3 3 Advanced Case Management with IBM Tooling - Part 2 (Entity Analytics) Figure 1 will be used as reference for the rest of the sections in the article. List Screening and Case Management In industries such as banking, government and insurance where there is a high chance of fraudulent transactions, it is essential to screen the customer records against watch lists to prevent blacklisted and suspicious customers from transacting with the organization. The result of screening can be used to either create a case for further investigation. For example if a new account is being opened in a bank and the customer name matches with a record in the terrorist watch list, a case may be created for further investigation. On the other hand, if a customer name is found in a good guys list, it may be concluded that no further investigation is required. IBM GNR helps in performing list screening. The process of setting the lists and searching for the customer record in GNR is beyond the scope of this article. Figure 1 shows how list screening and case management integrate in a work flow. The following steps describe the flow: 1. The input customer record is passed through GNR for screening. 2. Assuming the screening result is positive and the work flow decision is to create a case, the next step would be to resolve the customer to a unique entity in the system. (The benefits of doing this are described in the introductory section of this document) 3. Based on the entity id it is decided whether the current case can be merged with an existing case. 4. If no merging happens, a new case is created to investigate the customer. 5. The list screening scores are updated as properties in the case data. 6. Case linking is performed if a new case has been created in step The case is assigned to a case worker and eventually processed in IBM Case Manager. Steps 3, 4 and 6 are further elaborated in the following sections of this article. Using Identity Resolution in Case Management This section describes how Identity Insight (II) can be leveraged in a case management solution. This section assumes that Identity Insight product is installed and resolution rules have been configured as per the requirements of the application. The Basic Concept The basic concept is that II will resolve a customer record to a unique entity. Multiple customer records may map to the same entity, based on the attribute values. For example if a bank s customer has two accounts with the bank, the two customer records representing the same person may map to a single entity in II. II performs this resolution and returns the entity ID to the case management system. The ID of this entity will be used by the case management system in the following way: 3

4 4 Advanced Case Management with IBM Tooling - Part 2 (Entity Analytics) For a given entity, if an unassigned case of the same type exists in the system, a new case is not created. Rather, the current customer data is merged with the existing case. The history of the changes made to the case data is maintained as a case property. For a given entity if there are cases existing in the system, those case ids may be linked to the current case that is being created. This is done by holding the case ids as a property in the case data. In order to implement this concept, the case design should include the following properties: Entity Id : This is a unique id that is provided by II to identify individuals. Merge History: This holds the history of the case data when a merge (s described above) happens. Linked Cases: This holds the IDs of the cases which are linked to the current case. Steps for integrating entity resolution in Case Management For every case creation request that is made to the case management system: Pass the input customer record to II and receive an entity id in return. Search case repository, for existing cases created for this entity If an unassigned case of the same type exists, then merge the current customer data with the existing case data and skip the rest of the steps. Create a case with the entity id and customer data received in the input Link all related cases returned in step 2, to the new case. This way, the case analyst can view all the cases created for an entity across different accounts. Figure 2, shows an example of how case linking can be implemented using entity analytics: Figure 2: Case linking 4

5 5 Advanced Case Management with IBM Tooling - Part 2 (Entity Analytics) In figure 2, a bank customer by name Oliver Mc Milan has been performing suspicious transactions which the bank has been investigating through the case management system. In the mean time, the same customer tries to create another account with a slightly different name (Oliver Mac Milan). The bank's fraud system maps the new customer account to the same entity by mapping the customer's attributes such as SSN, , address and so on. The system finds that this entity has suspicious transaction cases on him and hence tags the new customer account as a high risk customer and creates a case for investigation. This new case is linked to all the existing cases on this entity. This enables the case worker to know the case history of the customer thus helping the case worker in taking an appropriate decision as per the bank's policies. In this way entity analytics can be used to reduce the number of cases created in the system by merging case data, and also to enrich the case data with linked case information that may be used by case workers for better decision making. Using Relationship Analysis in Case Management The basic concept As described in the previous section, II resolves every customer to a unique entity. It also maintains the relationships between entities based on the attribute values provided during the creation of an entity. Also, relationships between entities can be created manually in II using the visualizer tool or may be created through II APIs. This relationship information can be leveraged by case management systems to provide additional insight to case workers. There are two possible levels of showing relationship information in Case Manager. 1. Use a case property to store the related entity information along with the relationship type 2. Provide a web URL to the link analysis web application that is part of II. Steps for integrating relationship information in Case Management 1. Resolve the input customer record to an entity using II. 2. Use the entity ID returned by II in step 1, to query the entity relationships stored in II 3. Store the relationship information returned by II in a case property. 4. Use the case property to display the relationship information that is viewed by case workers. 5. Provide the URL for link analysis tool in the eform. This will enable the case worker to perform detailed analysis of the relationships which are displayed in step 4. 5

6 6 Advanced Case Management with IBM Tooling - Part 2 (Entity Analytics) Figure 3: Link Analysis in Identity Insight Figure 3 shows a screen shot of the link analysis provided by II for the example customer Oliver that was mentioned in the previous section of this article. In this figure we can see that Oliver Mc Milan and Oliver Mac Milan are related through a common address. It also shows that Oliver is and John share a joint account with the bank and that Oliver has been transacting with Dominic. A case worker can use this information to further investigate the history of John and Dominic. It may so happen that John has cases of being blacklisted (created by the list screening application, using GNR). This will help the case worker conclude that Oliver has been transacting with a blacklisted entity and hence may be performing fraudulent transactions. Summary: This article described how entity analytics can be used to perform advanced case management. It showed how IBM GNR and Identity Insight products can be leveraged to perform entity analytics and thus optimize the number of cases in the case management system on one hand and enhance case data with additional information on the other. The forthcoming articles in this series will show how to content analytics and business rules can be used in a case management solution. 6

7 7 Advanced Case Management with IBM Tooling - Part 2 (Entity Analytics) Resources IBM Enterprise Content Management home page IBM InfoSphere Identity Insight product home page IBM ILOG home page IBM SPSS Predictive Analytics Software and Solutions product home page 7