Many articles have been written about increasing front office productivity and profitability in capital markets. A McKinsey report from 2015, “Boosting Front-Office Productivity In Capital Markets,” is among the most popular, but its total lack of advice about applying technology to increase performance is telling. Despite being published only 3 years ago, there is not a single mention of artificial intelligence, big data, or any other disruptive technology.
The advice given to investment banks by this reputable firm is instead focused on increasing internal cooperation, improving account planning, and developing a better understanding of clients’ needs. All this is to be achieved through better quality meetings, more productive time spent within the bank, and improved gathering of client feedback. McKinsey advises that productivity gains of up to 30% can be achieved by making these changes.
This type of advice is hardly rocket science. From personal experience I believe that most managers in capital markets businesses are able to recognise these issues and, at the very least, will be working to remedy the most pressing ones. Slicker operations will always help, but the true obstacle to a significant jump in performance is a paucity of actionable data. The reality is that sales/traders are unable to capture what is needed given time constraints experienced on the trading floor.
That is why consulting firms have enjoyed such a large footprint in investment banking, until recently. They were paid to observe, collect, and analyze data that is often difficult to access and present it to leaders for better decision making. Now, the disruptive changes that new technologies have brought to other industries are being experienced in capital markets.
Unlocking the value in communication
In a data-rich business, the impact of AI-enabled analytics is very powerful indeed. The use of “smart machines” to find patterns in structured data, such as trades, is increasingly prevalent. The latest advance is the application of AI to unstructured data, which is primarily communications. Connected to the bank’s communication tools – email, phone, Bloomberg, chats, CRM platforms etc. – it is able to understand, extract, analyze what’s most relevant in communications and present those insights in near real-time.
As a former head of sales in capital markets businesses, here are some day-to-day applications for this technology that I would have found very helpful. Nowadays, using AI, someone with my role could have an exact breakdown of each salesperson’s time investment. You might be shocked to hear that capital markets salespeople communicate directly with their clients less than 35% of their time. The rest of the day they’re in meetings or doing non-productive administrative tasks. Having this insight would help managers and individual salespeople be more aware of how they achieve more client engagement. Management could even set up targets of, let’s say, 50% of weekly time spent on direct client interaction. More time spent with a client improves the sales/client relationship, it allows sales to gather more information, resulting in a deeper understanding of each client’s needs and, just to be a tad Machiavellian, it also helps to avoid the client spending time with competitors. A strong increase in the profitability of this client is highly probable.
I think it is obvious that the implementation of this form of AI will account for a significantly higher boost in performance than “just” the 30% envisaged by consulting firms.
The head of sales could also gain a complete overview of the amount of interactions with any of the bank’s clients. Questions such as “how long since sales last contacted a specific client” or “who are the neglected clients” allows the bank to redirect sales attention and resources, increasing interaction and ultimately increasing profitability. Imagine, as well, the enhanced service quality from a salesperson that devotes more time to clients: tailored market views, current hot topics, the bank’s most inquired financial instruments. This data can be extracted from thousands of chat messages and conversations that flow through the bank on a daily basis, with the AI transforming them into insights that can be put at a salesperson’s fingertips. Clients love to know what is going on in the market; banks leveraging AI on the trading floor would be their first call to get this market color.
There’s more. Soft performance indicators could be implemented into every salespersons’ and traders’ annual review, directly affecting their bonus payments. Until now, hard output numbers such as profit and loss were the only ones taken into consideration when reviewing individual performance. It was the only data that could be taken into consideration. AI-enabled analysis of communication has changed this forever. Today, a manager is able to set priorities through soft targets, such as the percentage of times a salesperson has tried to sell trading’s unwanted positions. This would have the double benefit of management being able to transmit values and guide the focus of the sales force while enhancing cooperation between internal desks. That results in a quicker turnaround of the bank’s positions, resulting in better risk management and improved profitability. An individual salesperson who maybe produced less profit but can show that he worked hard to put the bank’s interests first, beating these soft targets, could expect to be paid as well if not better than a more profitable colleague who disregards the employer’s priorities. This is a powerful tool for management to align the bank’s objectives and priorities to the actions of individual employees.
New insights are more potent than streamlined processes
These few examples highlight how insights from communication, made possible by AI, are triggering a new era in capital markets. The innovation is already happening and before long we can expect to see new kinds of data being used to accelerate decision making, facilitate steering on levels never before seen, and driving sustainably gains in each desk’s profitability. If better management and streamlined process can produce as much as a 30% improvement in productivity, how impactful would it be to tap into insights derived from every internal conversation or interaction with clients that is captured electronically?
I think it is obvious that the implementation of this form of AI will account for a significantly higher boost in performance than “just” the 30% envisaged by consulting firms. The underlying methods of capital markets might not change dramatically, but the scope and speed of data collection, sophisticated interpretation, and quick implementation of these new insights, will bring a potent competitive edge to the AI-boosted bank in a sector where profit margins shrink continuously.
More by Christhi Theiss
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