Page 40 - Monocle Quarterly Journal Vol 1 Issue 1 Q4

BANKING
“ e LaR Model
is derived from
a distribution of simulated economic factors, which drive simulations of the bank’s balance sheet and results in simulated net cumulative cash ow (NCCF) pro les over the funding horizon.”
behaviour of di erent client types. is will reduce reliance on the wholesale market, identify more ‘ideal’ loan-to-deposit ratios, and may well provide cheaper funding for the bank, a ording them the ability to improve pricing.
All that is needed is a commitment to carefully monitoring the metrics, to enhance their understanding of funding volatility and the speci c circumstances that could result in a sudden funding requirement. e bank will also be able to continuously monitor access to money markets as a function of evolving macroeconomic conditions.
is increased awareness will provide the breathing space needed to strategise alternative funding mechanisms – before any seizing up of liquidity markets. Ideally, it can also o er real-time identi cation of the order in which assets should be liquidated and made available for liquidation, depending on the expected duration and severity of liquidity strains.
So how does it work under each circumstance of contractual cash ows, behavioural cash ows, growth in asset and liability sizes, and interest rate re-pricing of each position?
Behavioural Modelling of Product Cash Flows
e LaR Model is derived from a distribution of simulated economic factors, which drive simulations of the bank’s balance sheet and results in simulated net cumulative cash ow (NCCF) pro les over the funding horizon. Distributions of the bank’s NCCF at di erent times are generated as the outcome of factors impacting the behaviouralisation of product cash ows over de ned intervals.
e framework simulates many versions (say, 100 000) of future cash ow pro les by replicating the entire cash ow process under each circumstance of contractual cash ows, behavioural cash ows, growth in asset / liability sizes, and interest rate re-pricing of each position. Asset Liability Management (ALM) is generally responsible for predicting the value and timing of daily cash in ows and out ows – both on a contractual and a behavioural basis.
Contractually, the cash ows of assets, liabilities, and o -balance sheet items are known with relative certainty. Term loans, which follow standard amortising schedules, stipulate a monthly payment from the term loan customer. ese cash ows can be disaggregated into interest
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