Abstract: At a time of growing market turbulence and a strong
shifts towards increasingly complex risk models and more stringent audit requirements, it is more critical than ever to maintain the highest quality of financial and credit information. IFC implemented
an approach that helps increase data integrity and quality significantly. This approach is called “Screening". Screening is based on linking information from different sources to identify potential
inconsistencies in key financial and credit data. That, in turn, can help
to ease the trials of portfolio supervision, and improve overall company global reporting and assessment systems. IFC experience
showed that when used regularly, Screening led to improved information.
Abstract: The policies governing the business of any
organization are well reflected in her business rules. The business
rules are implemented by data validation techniques, coded during
the software development process. Any change in business
policies results in change in the code written for data validation
used to enforce the business policies. Implementing the change in
business rules without changing the code is the objective of this
paper. The proposed approach enables users to create rule sets at
run time once the software has been developed. The newly defined
rule sets by end users are associated with the data variables for
which the validation is required. The proposed approach facilitates
the users to define business rules using all the comparison
operators and Boolean operators. Multithreading is used to
validate the data entered by end user against the business rules
applied. The evaluation of the data is performed by a newly
created thread using an enhanced form of the RPN (Reverse Polish
Notation) algorithm.
Abstract: Business rules and data warehouse are concepts and
technologies that impact a wide variety of organizational tasks. In
general, each area has evolved independently, impacting application
development and decision-making. Generating knowledge from data
warehouse is a complex process. This paper outlines an approach to
ease import of information and knowledge from a data warehouse
star schema through an inference class of business rules. The paper
utilizes the Oracle database for illustrating the working of the
concepts. The star schema structure and the business rules are stored
within a relational database. The approach is explained through a
prototype in Oracle-s PL/SQL Server Pages.
Abstract: Business rules are widely used within the services
sector. They provide consistency and allow relatively unskilled staff
to process complex transactions correctly. But there are many
examples where the rules themselves have an impact on the costs and
profits of an organisation. Financial services, transport and human
services are areas where the rules themselves can impact the bottom
line in a predictable way. If this is the case, how can we find that set
of rules that maximise profit, performance or customer service, or
any other key performance indicators? The manufacturing, energy
and process industries have embraced mathematical optimisation
techniques to improve efficiency, increase production and so on. This
paper explores several real world (but simplified) problems in the
services sector and shows how business rules can be optimised. It
also examines the similarities and differences between the service
and other sectors, and how optimisation techniques could be used to
deliver similar benefits.