Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1842
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dc.contributor.authorMahasivam, Pavithra-
dc.date.accessioned2022-04-01T07:28:09Z-
dc.date.available2022-04-01T07:28:09Z-
dc.date.issued2014-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1842-
dc.description.abstractThere is no doubt that data management is a critical component of any financial se 'vices firm's risk management strategy in the current market climate. As financial strategies have become more complex, new financial instruments are added and businesses continue the r expansion across the globe, the need for a coherent and streamlined approach to data nanagement potentially including the use of real-time data has never been greater. As today's decisions in the business world have become more real-time, the systems that support those decisions need to keep up. It is only natural that Business Intelligence BI systems quickly begin to incorporate real-time data in order to increase risk transparency to make better and faster busines s decisions, evaluate and predict broader spectrum of risk scenarios, confidentially answer qi arries from regulatory bodies and internal stakeholders. Thisresearch is mainly focusing on risk management of banking industry. The resea 'ch delivers advanced analytics and reporting capabilities to help strategic decision makers for ns vigate data to identify new opportunities, manage and mitigate risks, and make fact-based ecisions in ~- timely manner. Every bank measure and monitor their performance against characteri tics which is known as Key Performance Indicators (KPls). KPIs help an organization define t re progress . towards the organization goals. Important KPls of bank are identified in the literature that is used by financial regulators to keep track of how well-protected a bank is against risk.The real-time business intelligence framework is emulated for the banking industry in order to mitigate risk. The framework consists of changed data capture (eDq routine and rule-based engine. eDe routine is used to capture the changed data from the source database and load it to data mart online real-time. The rule base engines identify pattern changes in the data, based on the defined parameters and provide advanced analytics and reporting capabilities.en_US
dc.language.isoenen_US
dc.titleDevelopment of a Framework for Real- Time Business Intelligence for Managing Risk in Banking Industryen_US
dc.typeThesisen_US
Appears in Collections:2014
MSc. in IT

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