How to Leverage the LIBOR Transition to Improve your Data Management Game

Presented by

Michael King, BNY Mellon; Sue Laine, ASG Technologies & William Knapik, Accenture

About this talk

The transition away from LIBOR (London Interbank Offered Rate) is well underway, but there remains considerable ambiguity around how the final stages will be executed – especially with regards to benchmark replacements in markets outside the UK. What are the options, where are the uncertainties and what stage have firms reached in their preparations? The data management challenges for the LIBOR transition are immense and can seem overwhelming, but a change in perspective has the potential to shed light on the subject. Instead of viewing the LIBOR transition as just another costly, resource-consuming exercise, why not approach it as a platform through which to improve your data management game, better understand your data and reorganize your approach to gain competitive advantage? To deal with this transition, organizations must first execute a comprehensive inventory of data – where are the data assets and how will they be affected? Next, that data must be contextualized – what lines of business do they fall under and how much exposure will they incur? Finally, it must be evaluated – how do you calculate that risk, how is it modelled, how will a new offering rate alter that risk calculation and how can that data be transformed into the correct format? But there are other considerations too. How will the LIBOR transition interact with other regulations such as FRTB? LIBOR is not just a cost, but an opportunity – and that opportunity lies in the enhancement of your data management process to improve data quality and leverage data intelligence. This webinar will help you to: - Learn about the LIBOR-related data management challenges and what gaps need to be filled - Evaluate the stages in the process to total transition and compare where you are with your peers - Explore which regulations will be impacted by the transition and how you should be dealing with them - Identify potential solutions for data intelligence

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