Managing Liquidity in Covid Times – The Cash Flow Story - A Segmented approach for the “New Normal”

“Never take your eyes off the cash flow because it is the life blood of business” Richard Branson.

I had, in my earlier blogs spoken of Margin compression- the P&L Story and Capital compression- the Balance Sheet Story. In this blog am exploring the Liquidity Story against the Pandemic backdrop. It is not a story of less or more liquidity but of its unpredictability.

One might say there is enough liquidity now – all-important word here is “Now”. A quick look at early 2020 events point to the fact that spreads spiked in capital markets, short term funding markets experienced severe crunch leading to higher liquidity funding costs. Commitment drawdowns, particularly from low rated corporates in combination with repayment defaults aggravated the liquidity situation.

Quick, proactive steps by regulators through release of buffers (both capital & liquidity) and loan repayment concessions by policy makers stabilized the situation. Banks are aware that these initiatives are for a finite time, and they need to rebuild buffers while ensuring stability. Liquidity management becomes core here. There are many aspects of Liquidity that deserve attention. In this blog I will focus on Cashflows and the nuances of its forecasting in a crisis environment - Pandemic or any other crisis.

Typical forecasts cover -

• Contractual Cash Flows – Projected based on contracts – not very realistic even in normal times.
• Business As Usual Cash Flows – A refined version of the above where behavioral aspects of business, like prepayments, defaults, roll overs, core & volatile portions of non-maturing deposits & loans etc. are factored in thus coming up with a more realistic projection.
• What If cash flows – Positive and negative scenarios of interest rate movements, changes in macro-economic drivers or internal factors that impact at an overall portfolio or bucket level are assessed, using BAU flows as the base.

But these are not normal times and therefore typical behavior will not be true for now. Both sides of the bank books will behave differently to known patterns. Credit side, be it drawdowns, defaults on the one side or foreclosures on the other will be nuanced. Deposits may move differently too, particularly corporates who may park their surplus cash till they have other profitable options or draw their deposits to meet expenses (Salaries and other maintenance requirements) It needs to be appreciated that the Liquidity Flux is a reality for the Bank’s customers too. Fact is that the crisis is still “Unfolding” - who envisaged a second wave?

A strong cashflow forecasting ability is always important but now, in the “New Normal”, it is downright critical. How the Inflows and outflows, will behave in the evolving situation is difficult to estimate by the traditional approach. More so when the pandemic is impacting different industries, sectors, and geographies differently. It is these differences that need to be factored into the forecasts and then stressed to arrive at realistic picture.

New risk factors like, possible elongation of pandemic duration, slower economic recovery in some sectors/ Industries need to be considered along with view on shape of recovery.  While the optimists root for a “V” shaped recovery, realists tend to think “U” shaped, and the doomsday predictors fear an “L” shaped recovery!!  Be it as may, the capability to model each of these scenes will be needed. Structuring, modeling, and stressing at a more granular level, especially for the short term will help banks get closer to reality. 

Ability to understand and correctly model the cashflow characteristic of the entire range of products is challenging at the best of times. It becomes even more difficult during a crisis. How do we get there – well The Devil (or God, as I call it) is in the detail (Instrument level and attributes rich data). Below is a brief outline of “segmented cashflow projection Model” that helps identify “insolvent buckets/ pockets” more accurately during crisis times, thus prompting a quick proactive response.

Approach –   Done for short term (90 days to a year based on the Bank’s strategy) on an ongoing basis.

A “segment”, as I am referring here, is a sub portfolio grouped along the dimensions of industries, sectors, customer groups & geographies.

• Identify/ flag “Segments’ as pandemic/crisis sensitive or neutral, based on dimensional combination referred above.
• Group them into three segments.
  • Crisis sensitive  
    • Positively impacted.
    • Negatively impacted.
• Crisis neutral
• Model cashflows at segment + currency level with plausible assumptions of deferred / defaulted payments, loss of principal/ interest, change in market value, roll over, prepayments etc. to get crisis relatable behavioral flows. 
• Stress the flows. Given the nature, Stress Scenarios for each of these three segments will be different.
• In parallel, club the cashflows (Both behavioral & stressed) by buckets at organizational level, for identifying cash “Cliffs and Craters” to plan funding & lending decisions. 

The idea is not paralysis by analysis but to build intelligent forecasts that serve the fundamental purpose of crafting actions/ strategies that help organizations manage adverse situations smoothly while seizing opportunities that situations present!! The output would help banks to execute different strategies both at segment level and other levels of aggregation.

The other aspect to consider is balance sheet basis of forecasts- static vs dynamic. The latter is in the realm of Balance Sheet Planning, a topic by itself - subject for another blog. 

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