Business Intelligence in Banking. Kevin – 1501147113 Steven Eka Putranto – 1501148362 Rendy Winarta – 1501149226 Gladys Natalia – 1501165476 Stefani Trifosa - 1501158893. Topics. BI Benefit in Banking BI Implementation problem Storage needed for BI implementation BI Architecture
Kevin – 1501147113
Steven EkaPutranto – 1501148362
Gladys Natalia – 1501165476
Stefani Trifosa - 1501158893
Considering and analyzing the total client relationships is vital for successful bank operations in the conditions of growing competition.
a customer segment is a group of client composed based on specific shared characteristics
these types analysis enable assessing clients in terms of the ability to use several products and services simultaneously (loans, deposits, cards, e-banking, etc.)
enables the identification and analysis of various channels for communication with clients and delivery of products through these channels
Campaign management : the main objective is to analyze and compare the effects of marketing campaign on the increase in clients numbers, increase in the numbers and level sold products, earnings, etc.
To succeed at BI, an enterprise must nurture a cross-organizational collaborative culture in which everyone grasps and works toward the strategic vision.
Strong business sponsors truly believe in the value of the BI project.
Business sponsors establish proper objectives for the BI applications, ensuring that they support the strategic vision. Sponsors also approve the business-case assessment and help set the project scope
More often than not, the primary focus of BI projects is technical rather than business-oriented. The reason for this shortcoming: most BI project share run by IT project managers with minimal business knowledge. These managers tend not to involve business communities.
the business and technical skills required to implement a BI application are quite different than other operational online transaction processing (OLTP) projects.
Skilled Team Members taking important role to help define the work of BI in an organization.
Indentify the business issue, address it well after issues are identified , can provide better business analysts.
The biggest challenge faced by every BI project is its team’s ability to understand the scope, effort and importance of making the required data available for knowledge workers. Therefore, datamerge and standardization activitiesmust be planned and started at thebeginningofthe BI project.
In Business Intelligent system, there are two main types of storage system that could provide historical current and predictive views of business operations. They are:
Data warehouse are responsible to tore all the data, and also facilitate reporting and analysis needed for business intelligence.
Data mart I a subset of an organizational data store oriented to specific purpose or major data subject that may be distributed to support business needs.
The architecture of a bank’s business intelligence system is very heterogeneous and comprises several layers:
The data warehouse is the significant component of business intelligence. It is subject oriented, integrated. The data warehouse supports the physical propagation of data by handling the numerous enterprise records for integration, cleansing, aggregation and query tasks
It can also contain the operational data which can be defined as an updateable set of integrated data used for enterprise wide tactical decision-making of a particular subject area. It contains live data, not snapshots, and retains minimal history
They are those who use BI for development purposes, report generation, presentation and delivery.
Professional analysts who are experienced in using complex tools, and are the individuals who often use BI tools to manipulate data to help decision-making.
The managers who review the analyses presented by the power users and create their own reports and presentations.
Decision makers. They usually use BI to help with their presentation and delivery of information.
including those external parties, customers, regulators, external business analysts, partners, suppliers, or anyone with a need for reported information for tactical decision-making.
OLTP (on-line transaction processing) is a major task of traditional relational DBMS. Day to day operations such as purchasing, inventory, banking, manufacturing, payroll, registration, accounting, etc. are done in OLTP. OLTP also aims at reliable and efficient processing of a large number of transactions and ensuring data consistency.