Intraday Liquidity – Data Sampling, Modelling & Analysis

 

Purpose – to take a representative sample of a client Banks intraday liquidity data and, using the Intraday Insights Liquidity Simulator to model data flows and key decisions, analyse the areas of peak liquidity risk and inefficient use of liquidity, highlight areas of vulnerability re Basel III reporting requirements and build a commercial case for change

Pre-Requirements:

• Usually follows on from initial client dialogue re intraday liquidity challenges faced
• Can be a direct outcome from participation in an Awareness Workshop
• Based on a recognition that early insight can be gained from a rapid sampling, simulation and modelling on selective liquidity data

Process:

• Requires access to sample of Bank’s anonymous data
• We work on ratio that 5% of big flow data will reveal 95% of the issues
• Intraday Insights input data into Simulator and model current vs potential scenarios
• Data analysed and made available to client to build business case for change

Outcomes:
This process will produce the following:

• Assessment of how well Bank is managing current intraday liquidity
• Identification of pools of under-utilised liquidity where savings can be made
• Evaluation of regulatory and reporting issues arising from data

Next Steps:

• Data sampling is ideal preliminary step prior to wider strategic engagement
• Will provide actual data and results upon which to base a wider business case for change
• More detailed and focused data sampling may follow to provide deeper analysis of key issues