How AI is Changing Front Office Trading & Sales Trading 

AI in the finance sector is nothing new. Most of the big investment and large financial services firms have been talking about incorporating automation and artificial intelligence into their existing services and products for some time. However, only very recently have firms understood the power of AI to radically rethink and reinvent front office trading and sales trading products and services. Even more importantly, only recently has AI become powerful enough and ubiquitous enough to make that goal a reality for firms of all sizes. 

Benefits of AI Integration in Banking

Automation and AI has the potential to significantly improve productivity. A Deloitte study found that AI could boost front office productivity by 27%–35%, and generate revenue up to $3.5 million per employee.

Considered use of AI and automation could have other benefits for front office trading and sales trading too, including:

• Enhanced efficiency and speed in decision-making.
• Mitigation of human biases in trading and sales strategies.
• Improved accuracy in market analysis and risk assessment.
• Cost reduction through automation of repetitive tasks.

 

The Role of AI in Front Office Trading

Let’s look at how some banking firms are using AI currently in front office trading, as well as some potential use cases.

Since the mid-2010’s, AI has been used to automate trading, particularly high-volume trades. J.P. Morgan for example developed their pioneering LOXM programme that uses data analytics and machine learning to predict and execute equities trade in 2017.

More recently other front office trading activities such as pricing have benefitted from the use of artificial intelligence. ING have developed an AI powered tool that uses both historical and real-time market data to help traders make faster, more effective trading decisions, seeing a faster decision making 90% of the time, and better pricing up to four times more frequently. 

Other companies are exploring how to use AI to gather and analyse alternative data, everything from satellite imagery to shipping traffic, to spot trends and make more informed trading decisions.

In the future it’s likely that we’ll see AI and automation used as default for:

• Predictive analytics for market trends.
• Algorithmic sales and trading automation for rapid decision-making.
• Risk management and portfolio optimisation.
  

AI's Influence on Sales Trading

In sales trading, AI has revolutionised aspects of client interaction and market analysis. The integration of AI in client relationship management has enabled firms to improve their customer engagement and satisfaction through data-driven insights. Companies like Goldman Sachs have developed AI-powered platforms to analyse client interactions, predict their needs, and tailor communication strategies accordingly.

AI-has also allowed companies to hyper-personalise their client services by analysing historical trading patterns, preferences, and risk profiles to deliver customised investment recommendations and portfolio insights based on each client's financial goals and risk tolerance.

Finally, natural language processing (NLP) has proven useful in extracting valuable market insights from unstructured data sources such as news articles, social media, and analyst reports. For instance, Deutsche Bank uses NLP algorithms to sift through vast amounts of textual data and identify market trends, sentiment shifts, and emerging risks in real-time.

Attracting and Retaining Executive Talent

As AI becomes more central to companies front office trading activities sourcing executives with the skills and expertise to develop, implement and manage increasingly sophisticated tools is a critical concern.

Key strategies for companies hoping to attract and retain such talent include:

• Offering competitive compensation packages
  Benchmarking your benefits and compensation packages to accurately reflect the value of AI expertise is crucial for attracting and retaining driven and innovative professionals. Look at what others in your field are offering and ask your current team what benefits they value.
  
• Providing opportunities for continuous learning and development
  By demonstrating a commitment to the professional growth of your team through continuous learning, you’ll attract professionals looking to expand their knowledge and stay ahead in their field.
  
• Cultivating a culture of innovation and collaboration
  Create an environment where your team members can contribute ideas, and engage in meaningful projects, to attracted those who are driven by innovation and teamwork.
  
• Fostering a supportive work environment for experimentation and creativity
  Encourage your employees to explore new ideas and approaches without fear of failure, to attract talent that values autonomy and creative expression.
  
• Offer leadership roles in AI projects
  Empower professionals to take ownership of initiatives and drive meaningful change. This will appeal to those who seek opportunities to lead and make a significant impact.
  
• Partnering with a specialist recruitment agency
  A specialist agency like Kin Search provides access to an exclusive network of talent and are experts in identifying and attracting high level professionals, ensuring that you find the right individuals for your business.
  

The use of generative AI in banking and financial services is only going to continue to evolve. Staying ahead requires businesses to prioritise innovation and develop talent acquisition strategies that work to attract talent with the right skills, knowledge and vision.

Here at Kin Search, we are experts at connecting global businesses with the technology sales and business development executives they need to achieve success. Find the talent you need by contacting us today.