Bank plans gender parity for its UK dealmakers

French bank BNP Paribas is aiming for 50pc of new hires within its UK investment bank to be female. The bank has set a target of half of new hires in its UK global banking operation to be women, according to people familiar with the matter. It has already set a similar goal for those joining its ranks at the entry level.

BNP Paribas prime brokerage employee Stacey Macken successfully sued the bank two years ago for sexually discriminating on pay. It is now required to identify differences in compensation between men and women, as well as come up with a plan to change any gender pay gaps. The bank will focus first on the analyst and associate levels. However, it is aiming for gender parity across all levels of its business.

“Diversity is a core element of our business and HR strategy, as is the need to invest in identifying solutions to ensure the continued progress of our people at all levels of the firm beyond hiring,” said Emmanuelle Bury Lucas, UK country head at BNP Paribas.

“This includes talent and leadership programmes, the promotions process and the monitoring of metrics.” Many investment banks have long held a target to ensure at least 50pc of graduate recruits are women. But female representation in the upper ranks remains sparse. Exclusive research has shed light on the small proportion of female employees in key, revenue-generating roles.

It found that just 10pc of managing director and partner level dealmakers at top investment banks in Europe are women. The numbers were based on more than 1,300 senior dealmaking roles across Europe at companies including Citigroup, Goldman Sachs and JPMorgan.

UK gender pay gap figures are published annually at the behest of the government. However, despite a move to increase gender representation across the banking sector, those figures show there has been little change, with women still comprising a small proportion of banks’ highest earners.

BNP Paribas is also exploring another issue – using AI to collect data. It is looking at how large language models and generative AI can be used to gather data from text and unstructured sources. The bank could use the technology to digest information from analyst calls, quarterly results and company announcements – text-heavy documents where information is not always standardised.

“We are exploring use cases that include ingesting data from different sources such as public data,” said Andrei Serjantov, head of digital global markets at BNP Paribas. Where a LLM (a large language model, is a type of artificial intelligence programme that can recognise and generate text, among other tasks. LLMs are trained on large sets of date – hence the name “large”) is helpful, rather than some deep core issues like derivatives pricing models, it’s much more about getting the data into a set that can be used.”

BNP Paribas established an AI Lab in 2016 to develop tools for trading and sales. But it established another team in 2023 to look into use cases for LLMs, after interest in both models and generative AI exploded following the launch of ChatGPT by OpenAI in November 2022.

“A very simple way of comparing ‘traditional AI’ with large language models in the trading context is that the former predicts the next price and the latter predicts the next word. Hence, large language models can be useful for ingestion of, for example, unstructured historical data into trading, said Serjantov.” The investment bank said it has so far implemented 700 use cases for AI and is testing 26 more for generative AI. But the costs and data required needed to train AIs that LLMs make it unlikely that it will build one from the ground up.

“While developing large language models from scratch is expensive, we are evaluating the benefits and exploring the idea of fine tuning,” said Serjantov.