By Neill Vanlint, Global Head of Sales at GoldenSource

As cognitive scientist Gary Marcus once put it, “there are known knowns, and known unknowns, but we should be worried about the most is the unknown unknowns.” COVID-19 unquestionably falls into the latter and as the wider population waits with bated breadth for the peak to hit, the banking sector is bracing itself for the economic aftermath. The trouble is that there is simply no telling, at this stage, exactly what shape the economy will be in.

For every economist predicting a sharp but brief period of pain there are others saying that GDP will be on the downward slide for several quarters. But for banks to consistently be speculating over exactly what shape the downturn may or may not take is to miss the point somewhat. First things first, they need to focus on addressing issues within their control. Recent unprecedented bouts of market volatility has caused wholesale price tolerance breaks – making it much harder to correlate significant market swings. Even if an index goes down by 5%, everything gets thrown as an exception if it breaches a 2% drop. Often, not being able to see wood for trees, financial institutions just wholesale accept the prices regardless. The trouble is that in the midst of all this market turmoil, some genuine bad prices and outliers get approved which causes a whole raft of issues.

As volatility increases, so too do the daily price movements used in making profit and loss (P&L) calculations. The issue is that as the speed and complexity of investing has changed, the valuation practices that underpin those all-important calculations remain too simplistic, and overly reliant on inaccurate information.

One of the known knowns is that poor, or a lack of quality information affects numerous daily calculations from net asset valuation to portfolio weightings and trading risk exposures. With this being the case, surely now has to be the time for banks to adopt healthier pricing practices including collating, ranking, and defining those prices centrally to detect the potential unknowns before they occur.