ibm data warehouse banking model

7/18/2019 Ibm Data Warehouse Banking Model

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DATA WAREHOUSE BANKING MODEL - IBM DATA WAREHOUSE BANKING MODELBy using the IBM Banking Data Warehouse (BDW) Bank obtain a flexible data warehouse solution. The method used is to start from the parts of the data mart to theenterprise data warehouse.Banking Data Warehouse (BDW) consists of more than 80 components Business Solution Templates (BST). BST is used to support skoping and development required to report data warehousing and analytic needs such as Customer Profitability, WalletShare Analysis, Customer Attrition Analysis, Liquidity Analysis, and so forth.

IBM Banking Data Warehouse (BDW) covers the following areas:No. Area Features

1 Risk- Economic equivalence of a product- Loans and securities investments- Limit monitoring- Collateral valuation and review- Consolidated exposure- Inter-customer relationship- Subsidiaries / cross holdings- Relationship between Employee and Employer

2 Compliance- Provides a basic foundation for compliance requirements

- Basel II, IFRS / IAS, Sarbanes Oxley, Anti-Money Laundering Regulations- Flexible architecture that makes an organization more concentration on compliance requirements- Reporting template for the design of data warehouse- data requirements for applications and report to the specific needs of the regulator can be stored and mapped to the Banking Data Warehouse

3 Relationship Marketing- Consolidated view of a customer- Single view of an organization- Customer behavior / loyalty indicators- Demographic information- Transaction Analysis

- Spending Patterns- Spatial analysis- Segmentation- householding- Inquiries / complaints

4 Profitability- Flexible Structures: hold the components necessary for profitability- Treat every relationship / product as a business- Available to the General Ledger for the Involved Party, Products, etc.- the "Account" as Assets, Liabilities, Income, Features contingencies, and Expenses- Predefined Profitability summarizations

- Standard for Profitability Aggregations- Encourage standardized across the organization profitability- summarizations at different levels: Account, Customer, Org Unit,Product

5 Asset and Liability- Mismatch in liquidity- Mismatch in Interest rate structure- Optimization of funds- Pooling



- Hedging- Capital adequacy- Change in balance sheet over time- Analysis of historic trends- Projection of future events

Advantage of the IBM Banking Data Warehouse include:

- Meng-encapsulation extension of the IBM Data Warehouse effectively and is a solution to a financial organization like a bank.- Bringing a competitive opportunity in providing data consolidation and data cleaning.- Support the implementation of data warehouse solutions quickly with banking data means.- Provides a combination of sound engineering infra-structural, a proven data management in terms of products and functional.- Facilitate the customization and extension of the data warehouse.- Support business users to better control the terms of the definition and skoping of data warehouse solutions.

- Provides a solid base for the development of management applications and to integrate decision making and application information for executives- Reduce the risk of failure by taking the approach of integrated information management

The architecture of the BDW is described as follows:

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COLLATERAL_KEY

COLLATERAL_HELDQ8B8R-7XJMW-7T2H2-CVKCR-27BJJ

COLLATERAL_PERF_STATUS

COLLATERAL_TYPE

COLLATERAL_SRC

DW_FACILITY_KEY

ACCT_NUM

FACILITY_NAMEFACILITY_TYPE



REL_DEF_EVENT

UNDRWN_COMM_COMMl

OTHER_SRC_DTL

ESTIMATED_LGDEXPOSURE_BALANCESUSPENCE_INTERESTPENAL_CHARGESDEFAULT_DAYSCOLLATERAL_VALUECOLLATERAL_LAST_VALUECOLLATERAL_COVERAGE_RATIOBANK_COST_RECOVERYCUSTOMER_COST_RECOVERYAMOUNT_OTHERS_RECOVERED

RECOVERED_TOTAL_AMOUNTCOST_FUNDING_LOSSEXPOSURE_DEFAULT

LOSS_GIVEN_DEFAULT

ibm data warehouse banking model

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