Executive Summary:
This blog describes the pain points that we encountered at a specific insurance customer in Netherlands and along, the solution that we implemented and which we’re ready to offer as service to our insurance customers.
The main driver for building such a functionality was to generate a similar volume of data with the one customer possesses or expects to have. The attention of this exercise draws towards business content and structure analysis.
Our investigations reveal that such an approach improves communication with customers, delivery times of services and reduces the cost for our customers
The need to analyze our customer’s insurance product complexity in regards to structure and entities (from Business Object Model), together with the idea of keeping costs to a minimum edge, drove us in the direction to conclude such a functionality, that is supposed to offer us a comprehensive sandbox environment in which we can further analyze and find solutions for current and future problems.
The blog evaluates these pain points and concludes that it would be an ideal candidate to meet the challenge presented by our insurance customer and could satisfy the new service demand in regards to safeguarding of insurance portfolio, since it significantly reduces delivery time and increases accuracy of a comprehensive solution proposal, as well as can open the doors to forecasting your insurance solution data growth and future strategies to follow in order to run with a lower TCO.
Benefits:
When to use:
Suggestion is to use such a report during the run phase of your sap implementation when the prerequisites are easily available.
Prerequisites:
How it works:
The mass creation of business partners and insurance policies functions by the described behavior:
It generates copies of existing insurance policies and business partners under a certain range of numbers by using random business partners like:
Initial screen mass policy creation screen shot:

Business partner mass partner creation screen shot:

What is generated:
Insurance policies and corresponding random generated business partners based on initial reference data.
For each created policy, the business partner is picked from a business partner selection range (only from the ones which were generated) on the initial screen of the report.
Current Limitations:
The policy processing status is not altered, the journal entries will have an indicator of change due to the generation and behavior of custom entities content is currently not evaluated.
Future plans:
Contact:
Active Global Support:
Florin Niculescu (florin.niculescu@sap.com) – Insurance Safeguarding Portfolio
Vamsi Mohana Mamillapalli (m.mamillapalli@sap.com) - Delivery Factory for Financial Services
Logical Flow:

Design view:
There are two design approaches to achieve the purpose of the blog:
Description | Function module | |
Standard Interface | To transfer an application in FS-PM and process the input data with a remote-enabled function module | /PM0/ABT_PROP_RELEASE |
FS-PM mass migration interface | Policy Migration: (FS-PM) Migration of In-Force Business(Restricted Release for Migration) | /PM0/ABQ_POL_MASSMIGR |
This solution is based on report /PM0/ABQ_MIGRATION_TEST, which is to read the data of a policy in FS-PM and formats it for data migration. It simulates data migration by creating one or more copies of an existing policy.
Steps for mass generation of policies:
Steps for mass generation of business partners:
Code:
Mass generation of policies: Z_COPY_POLICY
Mass generation of business partners: Z_CREATE_BP