Business Intelligence in Banking  Yesika Kristina  Dea Pradana Darmawan  Sukianti  Merianti  Meshiya Caterlee  06 PLM

Outline  Business Intelligence Definition  Business Intelligence in Banking  Problems of BI Implementation  Storage of BI Implementation  BI Architecture  BI and Data Warehouse  BI Application and Users

Business Intelligence Definition a variety of software application Raw data analysis

Business Intelligence in Banking Business Intelligence Solutions Quickly and efficiently detect and reduce incidents of fraudulent activity. Calculate the probability of customers will default of loan and estimate the cost of recovery. Accurately estimate the risk of customers loan based on:  The financial assets and earning capacity of borrower.  The prevailing economic climate. Analyse credit portfolios, enable banks to quickly identify potential delinquency cases and act early as preventative measure. Ensure compliance with statutory and regulatory requirements.

Problems of BI Implementation − Strategic Alignment − Process Improvement − System Implementation − Change Management − Data Usage − Data Definition and Management − Data Visualisation − Vendor Issues

 Storage Area Network (SAN)  Network Attached Storage (NAS)  Hierarchical Storage Management (HSM) Storages of BI Implementation

BI Architecture Five- layered BI Architecture Data source layer ETL (Extract-Transform-Load) layer Data warehouse layer End use layer Metadata layer

BI & Data Warehouse Business Intelligence Data Warehouse

BI Applications & Users BI Applications  Spreadsheet.  Reporting and querying software.  OLAP (Online Analytical Processing).  Digital dashboards.  Data mining.  Data warehousing.  Decision engineering.  Process mining.  Business performance management.  Local information system. BI Users  IT user  Power user  Casual user  Enterprise user  Business user  Extra-enterprise users

Conclusions and Suggestions BI Benefit Problem Application Banking

Q & A

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