BNP Paribas Securities Services launches trade processing artificial intelligence tool
BNP Paribas Securities Services is implementing Smart Chaser, a trade matching tool using AI and predictive analysis.
BNP Paribas Securities Services is implementing Smart Chaser, a trade matching tool using artificial intelligence and predictive analysis, to further automate the trade processing services it provides to investment managers.
Thomas Durif, Global Head of Middle Office Products at BNP Paribas Securities Services, said:"We estimate that up to 30% of the trades processed on behalf of asset managers require manual intervention in order to complete. This is an industry-wide challenge which is often caused by counterparties holding mismatching data for the same trade.
"Using predictive analysis, Smart Chaser will analyse historical data to identify patterns in trades that have required manual intervention in the past and proactively warn clients and their brokers on their live trading activity so they can take action promptly. We are already making good progress, having reached around 98% prediction accuracy."
Maxime Boyer-Chammard, Global Head of Investment Services and Analytics, at BNP Paribas Securities Services, said: "We are delighted to be working on this new tool. Smart Chaser is a great example of how we aim to transform our middle office technology and make straight through processing a reality thanks to big data and predictive analytics, to the ultimate benefit of our clients."
Trade matching – the comparison of trade details between the client and its broker – is a key part of the middle office service provided by BNP Paribas to its investment manager clients. Matching must be performed in a timely manner or there is a risk a trade may require manual intervention or, in some cases, fail. Intervention or failure is particularly likely if a trade is not settled on the day of execution.
Using machine learning and predictive analysis, Smart Chaser will predict the likelihood that a trade will not "match" automatically and will therefore require manual intervention. BNP Paribas aims to be able to predict the likelihood of a delayed "trade matching", ascertain the contributors to the delay and suggest a pre-designed email template to be sent by the middle office operational team to relevant clients.
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