Technology

1.0 Introduction
According to World Congress on Software Engineering, if companies are to withstand fierce competition, they must do more to satisfy their customers by utilizing the enterprise data at their disposal (Wang, Ming, and You 2009). Today, enterprises have a challenge in managing and utilizing their data resulting to unnecessary duplication of information and inefficient customer service. This is because of disorganized data and management practices. Data belonging to one company is scattered in different locations of the enterprises database hence resulting into lack of coordination among the companys departments in carrying out business with their clients

2.0 Background and Problem Statement
The major problem being faced by most financial institutions today is the capability of merging and centralization of customer details. This is to find out the investments base of an individual customer in their institution in order to reward them with discount benefits (Butler 2002). This is a scheme that is possible when a customers multiple investments are analyzed and discount benefits rewarded in relation to total investment into the companys growth. An individual may be a share holder and a holder of multiple active accounts in the same company. This may qualify them to some discount benefits offered by the institution. This is a problem observed by the author in an organization they are linked to.

Customers have the responsibility of informing the institution regarding all eligible investments in the institution such as account holdings and share holding. This is so as to get sales charge discount at the time of purchase or transaction. The company is also required through their systems in operation to recognize the total value of the customers investments in the company and determine the level of sales charge and service discount the customer qualifies for. This is where the author proposes the implementation of a Master Data Management (MDM) to be a solution to the above problem.

3.0 Research Objectives
This research paper focuses on the capabilities of a Master Data Management system to become a solution to the data management problem. The research objective uses the following questions to analyze the topic.

What is an MDM

What are the functions of an MDM and how are they capable of integrating and implementing a solution to the problem

What are the effects of implementing an MDM to the enterprise

Research on a Master Data Management System
In order to understand what a Master Data Management system is, we need to clearly understand what master data is. Master Data is the core data required for operations in a business venture (Mahmood 2009). Information that is treated as master data varies from different industries. Master data management can be defined as a system that encompasses the whole organization in order to integrate, manage and harmonize Master Data to make information useful in business decisions-making (Buffer and Stackowisk 2009). This is to enhance the organizations value (BIPM ENCYCLOPEDIA 2010).

It is observed that in the current business circles, connectivity between organizations has risen and amount of information has become extremely large resulting into a challenge in the method of handling it. With the information sharing environment growing fast, we also encounter the challenge of having packets or bundles of information scattered all over yet this information is mandatory for particular business operations for a particular organization (Sumner 2009).  Thus, an organization capable of coordinating its information sharing and collaboration of its various departments in using the information is extremely successful.

The Current Architecture
The existing infrastructure has been designed to cater for specific area of focus and the business application architectures here meet departmental organizational needs or particular processes. This has resulted into significant duplication of work. For example, a financial institution has been having customer details being handled by one system and sometimes updating from another branch becomes a problem or takes very long (Berson, Dubov and Dubov 2007). The costs of the institution are dispersed around the organizations units and tracking all of it is a problem. This results into hidden costs which bring imbalances in auditing. Loan processing is also a tiresome process because of heavily customized, disparate technology systems (Loshin 2008). Customers are also affected because their account holdings are in different record hence it is hard to establish the value of investment of an individual.

Berson, Dubov and Dubov (2007) explain about the sources of data which come from classical data warehouse. The latter provides data view for customers but do not support operational applications that need to access real time transactional data associated with a given customer. As a result, it does not provide a timely systems record for customer information. The Extract, Transform and Load tools are the ones that extract data from multiple data sources and transform them from the source formats to the target formats and load the transformed and formatted data into target database such as the CDI hub (Open Text Corporation 2010).

The Functions of Master Data Management
The Master Data Management is integrated across the system that contains the packets of master data. By merging, re-duplication standardizing, cleansing and other transformations, the integrated data is placed in a central repository called the Master Data Management hub (Loshin 2008). Master Data Management helps make Master Data to work at enterprise level instead of small units assets. Customer Data Integration (CDI) is important to achieve Master Data Management. A CDI is a special customer-data- focused type of MDM. It collects customer information and transforms it into a customer view from which one can analyze customers details from different sources into one single reference point while ensuring quality and consistency (Wang et al 2009). Master Data Management has significant operational functions and involves business decisions in implementing the MDM (Berson, Dubov and Dubov 2007).

In financial institutions, the master data represents the business objects that are shared across more than one transactional application. It is the business objects around which transactions are executed. In financial institutions, master data is for example customer personal information, their assets and account numbers, human resource, assets and products. In collecting master data from different departments, different processes and application systems are under different processes and formats. This will develop master data for a financial institution able to give customer details and all the investments in the company (Buffer and Stackowisk 2009).

Attributes of the Master Records

Master Data Management is a combination of several processes,

Applications and technologies consolidate, clean and augment the corporate master data and synchronize it with all applications, business processes and analytical tools. This results in significant improvements in operational efficiency, reporting and fact based decision- making (Buffer and Stackowisk 2009).

Oracle specialists suggest that to manage the master data system and make it updated, one needs to keep the MDM system current with high quality data. To maintain high quality MDM. One has to ensure they understand all possible sources and current state of quality data in each source. The data is to be put in one central repository and link it to all participating applications (Berson et al 2007).

The data should be managed according to business rules. Synchronization of central master data with enterprise business processes and existing connected applications is also called for. One should ensure the data stays in-sync across the information technology landscape. Leverage that a single version exists for all master data objects by supporting business intelligence systems and reporting.  In MDM implementation, the first step is to profile data, meaning that each master data business entity must be managed centrally in a master data repository and all existing systems that create or update the master data must be assessed as to their quality (Buffer and Stackowisk 2009).

Conclusion
With evidence from scholars and experts, it is deemed true that the Master Data Management is a solution to the information silo problem where there is duplication and inefficiency. Hence I propose that this system be adopted by financial institutions.