Today’s post-trade process is a fragmented flow that spreads across several business units and external entities like brokers, clearinghouses, exchanges, institutional investors, and various settlement agents. Each trade encompasses numerous different interfaces, processes, data, and reconciliation efforts. All these steps result in delays, inefficiencies, and cost. The global push to reduce settlement cycles, increasing electronification of markets (which may lead to increased volumes and velocity of data), and the interest in new financial products such as tokenized/smart contract enabled assets, cash-on-chain, is creating an imperative around technology change.

Advancements in new technology such as cloud, distributed ledger technology (DLT), various strands of artificial intelligence (AI) such as machine learning (ML), and generative artificial intelligence (GenAI), and advanced data analytics, offer immense opportunities for improving operational efficiency, but also for reimagining post-trade operations in the capital markets.This presents the potential for technology to help create new revenues streams for the firm, therefore changing the status of post trade from merely a cost center.