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You are viewing ARCHIVED CONTENT released online between 1 April 2010 and 24 August 2018 or content that has been selectively archived and is no longer active. Content in this archive is NOT UPDATED, and links may not function.By Mike Lines
In today’s connected world, the sheer volume of unstructured data being created is reaching exorbitant heights. This, coupled with the stringent regulations encroaching on the banking sector such as Dodd-Frank, EMIR and Basel III, makes it imperative for banks to control collateral costs and optimize capital allocation.
Investment banks now hold more Over-the-Counter (OTC) International Swaps and Derivatives Association (ISDA) agreements than at any time in history, and managing them is only getting more difficult given each OTC derivatives contract now has hundreds of data points. In some cases, banks have lost between $5 million and $25 million in a single trade after using the wrong interest rates, posting the wrong type of collateral or being arbitraged by counterparties. To mitigate these risks, banks are beginning to rely on solutions that automatically sift through tens of thousands of counterparty agreements and identify relevant data that traders need to drive profits — eligible collateral, interest rates, termination events, netting, thresholds and independent amounts.
Read the complete article at: Information Overload: Banks Automate in the Era of Big Data