Quantum computers process information using the laws of quantum mechanics. They are well suited for a number of tasks such as simulating quantum mechanical systems and factoring. Additionally, quantum computers can provide a quadratic speed-up over classical Monte-Carlo simulations which may be used to evaluate risk and price financial derivatives.
Another possible application area for quantum computers is optimization, particularly combinatorial optimization. It is not believed that quantum computers will be able to solve NP-hard problems in polynomial time. There is, however, a significant effort in designing quantum heuristics that could be practically useful by finding near-optimal solutions.
In this paper, researchers from IBM and Barclays introduce an approach to extend the existing quantum methods and test their algorithm on the Transaction Settlement problem by focusing on securities settlement in capital markets.
Here, transaction settlement is the process in which securities are delivered usually against a payment. This exchange between parties can be facilitated by a clearinghouse, which also mitigates the counterparty risk. Financial institutions submit the details of the trades (e.g. buy x shares of some company for an amount y of some currency) to the clearinghouse, which runs a complex optimization algorithm on the resulting batch of transactions while taking into account credit and collateral facilities.
The objective is typically to settle as many transactions as possible or to maximize the total value of the settled transactions. Transaction settlement is a difficult optimization problem due to a combination of both the legal constraints that must be satisfied when settling delivery-versus-payment transactions and the additional optionality introduced by collateralizing assets and utiltizing credit facilities.
A variety of approaches are currently employed, ranging in complexity from basic gross settlement systems (which settle on a simple transaction-by-transaction basis) to sophisticated probabilistic techniques such as simulated annealing (whereby an optimization process is performed to identify a sufficient subset of transactions that can settle and then that subset is actually settled). This is an industry process of systemic importance because of the volume and value of transactions settled, e.g. over $1.85 quadrillion of securities transactions were processed in 2018 by subsidiaries of the post-trade market infrastructure DTCC.