Banking transactions

Banking

© 2012 Ideal Analytics Limited.

Banking – the gamut of all monetary transactions Banking these days engages in every kind of monetary transactions between parties Pension Funds

Monitoring Transactions Share Market Insurance

International Trade

International Funding

Loans Guarantees

Investments

Secondary Market Underwrite Trusts

Foreign Exchange

Venture Capitalist Funding

Mergers & Acquisitions Share Market Public Offerings for Corporates

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Mutual Funds

Banking transactions- generator of data in various sets and formats  Every transaction in a bank generates many sets of data that range from identity data to details of transactions and linked transactions.  Managing these data has gone through an evolution of approaches.  It was once account oriented and now the approach is customer oriented

 Banking now has to deal with data for activities that have been registered as well as those that is a prospect.  Marketing for future products and banking instruments as well as service is integral to present day banking.  Studying the trends of transactions, its aggregate, average and forecasting is essential.  Predictive analysis becomes extremely important for future growth of banks and the banking operations in uncharted markets and necessary for new market capturing.

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Data calculation and presentation more important than management Calculation and derivation through known and innovative formulae has taken more importance than mere data storing, management and retrieval.  Calculation and derivation through known and innovative formulae has taken more importance than mere data storing, management and retrieval.

 Fast calculation, fast change of alternative hypotheses, smart presentation of alternative scenarios, without getting embroiled in fixed and in-flexible models, is the demand of the industry.  End-user driven analysis, self-serving view of the mathematical derivations, without the need to handle any intermediate data store other than the transactional data base was being sought by business analysts.  Presentation and calculation of data should be directly from the transaction data store reflecting the currency of data and at the same time not disturbing the point-in-creation transaction data was specifically demanded.  Very high security of data with respect to different access privileges and still not compromising the data authenticity is very important in banking operation.

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Limitations of usual OLAP based BI approach

 The data is huge, the sets are varied, the formats are different, BUT the structure needed are complex even more.  The need of complex calculations instantly and changes of that also instantly demands fast dismantling and re-mantling of the formulae and transience of the data.  OLAP based solutions have pre-fixed models that require special skills to build and to dismantle  OLAP based solutions require intermediate data stores that loses the currency of data  OLAP tools store the data of every data cube or presentation artefact.

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Data Analytics Approach Data analytic approach is a specialized form with built-in slickness, smartness, flexibility and fast manipulations with very advanced techniques BUT we do not store the data, we store the queries, that can be formed without skill and prior training  The transience in data secures the data rendered and keeps the currency of data intact every time any data is changed.  Each transaction data set does not require to hold more time stamp than is exigent by the transaction dataset.  No special time or signature needed to load the data in any special data store.  YET the entire complexity is translucent to the end-user. The solution does it for the end-user.

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Data Analytics Approach Applying analytics on transactional data enables quick decision making thereby generating good returns

Banking Transactions

Return on Investment

Business Users

Transactional Data Generated

Reduce Costs

Revenue Increase

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Quick Decisions

Ideal-Analytics – a solution well researched to suit the special requirement

 After a long research and development IDEAL-ANALYTICS is used to handle these conditions with remarkable ease and is very handy and slick.  The speed of huge matrix manipulations is phenomenal and yet it purports to the end-user as just another sql-type data language.  The help provided is intuitive and yet fully documented and on-line.

 The skill needed does not require any prior knowledge.  User knows the algebra of her business and does not have to depend on any consultant any further or any extra help.  The encapsulation of the mathematical wizardry helps the user focus on the business need and presentation than on technology.  Huge data sets manipulated in minutes that took days to process.

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Thank you

© 2012 Ideal Analytics Limited.