business intelligence in banking n.
Skip this Video
Loading SlideShow in 5 Seconds..
Business Intelligence in Banking PowerPoint Presentation
Download Presentation
Business Intelligence in Banking

Loading in 2 Seconds...

play fullscreen
1 / 27

Business Intelligence in Banking - PowerPoint PPT Presentation

  • Uploaded on

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

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

Business Intelligence in Banking

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
    Presentation Transcript
    business intelligence in banking

    Business Intelligence in Banking

    Kevin – 1501147113

    Steven EkaPutranto – 1501148362

    RendyWinarta– 1501149226

    Gladys Natalia – 1501165476

    Stefani Trifosa - 1501158893

    • BI Benefit in Banking
    • BI Implementation problem
    • Storage needed for BI implementation
    • BI Architecture
    • Usage Data warehouse in BI
    • BI Applications
    • User of BI
    • Example of BI in screen shoot and explanation
    considering and analyzing the total client

    Considering and analyzing the total client relationships is vital for successful bank operations in the conditions of growing competition.

    • Most software solutions in the business intelligence domain are focused on market segmentation, defining a clear picture of the clients and their relationships with banks, defining a clear picture of the market potential and the bank’s ability to use this potential
    segmentation a customer segment is a group

    Segmentation :

    a customer segment is a group of client composed based on specific shared characteristics

    • Customer profitability : profitability analysis is the analysis of clients in accordance with the expected impact on the bank’s profit, and thus the total return on equity (ROE)
    cross selling and up selling these types analysis

    Cross-selling and up-selling :

    these types analysis enable assessing clients in terms of the ability to use several products and services simultaneously (loans, deposits, cards, e-banking, etc.)

    • Channel effectiveness :

    enables the identification and analysis of various channels for communication with clients and delivery of products through these channels

    campaign management the main objective

    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.

    cross organizational collaboration to succeed

    Cross-Organizational Collaboration

    To succeed at BI, an enterprise must nurture a cross-organizational collaborative culture in which everyone grasps and works toward the strategic vision.

    • Business Sponsor

    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

    dedicated business representation more often than

    Dedicated Business Representation

    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.

    • Availability of Skilled Team Members

    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.

    business analysis and data standardization some

    Business Analysis and Data Standardization

    • Some of these issues are :
    • Identifying Information Needs

    Indentify the business issue, address it well after issues are identified , can provide better business analysts.

    • Data Merge and Standardization

    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

    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

    Data warehouse are responsible to tore all the data, and also facilitate reporting and analysis needed for business intelligence.

    • Data Mart

    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

    The architecture of a bank’s business intelligence system is very heterogeneous and comprises several layers:

    • Operational database and external data
    • The data integration and transformation layers
    • The data warehouse layer
    • The data access layer (applications, OLAP, data mining, etc.)
    • The front end (layer for access to information).
    the data warehouse is the significant component

    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

    the following are some examples of bi applications
    The following are some examples of BI applications:
    • A company that provides natural gas to homes created a dashboard that supports operational performance metric management and allows real time decision making. In one application of the dashboard, the number of repeat repair calls was reduced, resulting in a saving of $1.3 million.
    • At a large member-owned distributor to hardware stores, use of a dashboard reduced theamount of inventory that must be liquidated or sold as a loss leader from $60 million to$10 million. Their BI system also allowed their member stores to see their ownperformance relative to similar stores.
    it user they are those who use bi for development

    IT User

    They are those who use BI for development purposes, report generation, presentation and delivery.

    • Power User

    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.

    • Business User

    The managers who review the analyses presented by the power users and create their own reports and presentations.

    casual user decision makers they usually

    Casual User

    Decision makers. They usually use BI to help with their presentation and delivery of information.

    • Extra-Enterprise User

    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

    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.

    • OLAP (on-line analytical processing) is a major task of data warehouse system, data analysis and decision making, aims at efficient multidimensional processing of large data volumes (fast, interactive answer to large aggregate queries.