Challenge:

Volumes of data are increasing rapidly due to cash flow orientation and banks are struggling to perform finance and risk management in real time.  This is especially acute for liquidity risk management where the current spread sheet applications perform slowly due to the massive amounts of data.  Compliance with new liquidity rules under Basel III is a must and especially critical given the current unstable market conditions.  Furthermore, fast changing market conditions and increasing frequency of regulatory reporting demands quick turnaround on liquidity risk reports.  Current report capabilities restrict analysis to aggregated data sets and make meaningful ad hoc analysis very challenging.

Solution:

fraXses will enable banks to provide assessment of assets in order to identify risks in real time and support Basel III compliance monitoring.  Deep dive analysis into intra-day risk positions can now be performed in real time allowing banks to react with data driven liquidity procurement measures.  Liquidity needs can be predicted on the basis of varied scenarios, simulations and stress testing that are more accurately aligned with current conditions.  fraXses allows flexible consumption by promoting real time reporting anytime / anywhere and providing seamless drill down from group level results to individual cash flows.  The reporting needs of the whole organisation can be supported, from business analysts to the CRO.

Benefit:

Liquidity Risk Management powered by fraXses, can enable banks to perform real time, high-speed liquidity reporting and risk management on large volumes of individual cash flows and granular assets and liabilities.  This allows for pooling all types of cash flows, including operative, simulated, and stressed data from various source systems.  fraXses can provide a framework to calculate risk management key figures and out-of-the box calculation for a representative set of regulatory key figures such as the Basel III ratios.  Examples of basic stress factors that can be applied to the data are to gauge the effect of varying haircut and run-off rates or the re-classification of certain assets.