Technology innovation of the year: Scotiabank
Derivatives clients of Scotiabank may have noticed the bank’s pricing has been tighter of late. They may not know this is due to its new risk engine, which was built to calculate valuation adjustments (XVAs) faster and more accurately. XVAs reflect the credit, funding and capital costs associated with trading over-the-counter derivatives. Dealers typically incorporate these adjustments into the price of a new trade. But calculating XVAs is one of the largest computational challenges banks face on a daily basis. Scotiabank’s risk engine combines a mathematical technique known as adjoint algorithmic differentiation, or AAD, with deep neural networks, a branch of artificial intelligence – a mashup the bank claims is a first. The system is powered by graphics processing units (GPUs) running in the cloud – another first. The result is a tool that allows traders and risk managers to better understand exposure across asset classes, including rates, credit, foreign exchange and commodities. This insight proved invaluable for Scotiabank during the coronavirus chaos earlier in 2020, particularly as liquidity dried up in some markets. When markets started to dislocate at the end of March and into April, the risk engine enabled the bank to run multiple scenario analyses to calculate, on-the fly, the impact to its book. “We tested different flavours of correlation and used these to guide our hedging strategy as we saw which scenario unfolded in the markets on any given day. The migration to this new platform has given us greater visibility into our risk,” says Karin Bergeron, head of XVA trading at Scotiabank.
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