By Stuart Berwick, CEO and Co-Founder, single piece
Digitization is becoming increasingly critical, and while financial markets firms that have already digitized to some degree are seeing increased internal efficiencies and productivity gains, there is still a long way to go.
There are familiar and valuable concepts for the sell side that revolve around “Who do I call to get the deal?” or “Which of my clients is at risk?” “. Yet the answers are usually only found in a single spreadsheet that took a week to put together, or in a quarterly report. In the era of artificial intelligence and machine learning, it is striking that old customer relationship tools have not kept up with the times.
Imagine what companies could achieve, however, if they broke the boundaries of possibility? Not only by enabling employees to be more efficient, productive and better informed (which will ultimately increase and retain revenue and drive profitability), but also by providing a better customer experience. In these uncertain times, fast, data-driven decisions can have a positive effect on customer retention and acquisition.
Today’s legacy CRM systems, plagued by poor user experience and unreliability, stand in the way of improving employee productivity. Due to a lack of investment, these legacy tools have not progressed. They are also very rigid, which means they cannot be configured to meet the needs of a rapidly changing and volatile market.
In addition, a growing number of young “digital natives” are beginning to emerge from the industry, and with them a much more sophisticated expectation of the technological tools that facilitate their daily work.
Presentation of “ambient” and “guided” systems
However, changes are on the way with the introduction of new AI and ML based tools in CRM systems. Two important concepts in this area are ambient data collection and guided actions.
Ambient data collection is based on a “zero ambient” concept. This means that a user can sit down in front of a corporate computer system and simply go about their day-to-day work, without having to store or copy information to another system. In other words, the system may automatically, or “ambient” collect information about its environment.
An example of ambient CRM functionality is “data capture”. A virtuous circle is created in which the system can ambiently identify data from the environment (such as Instant Bloomberg (IB) chat, email, phone conversations, calendar events, etc.) and categorize and capture them intelligently. The result is used to guide the system in the future. By implementing feeds from financial markets messaging systems (such as IB chat), transcripts can be extracted using artificial intelligence to identify high-value conversations (e.g. ticker/sector mentioned or the directional comment). The user will confirm whether the relevant piece of data is indeed valuable, which in turn will teach the system to better recognize useful data. In this regard, the system will eventually become fully automated.
Guided actions, on the other hand, relate to where the system guides the user to certain actions or results to gain an advantage, for example, to increase and maintain revenue and profitability. It achieves this by using a large set of data and knowledge of previous results.
Guided actions don’t just tell users what the problem is, they also tell them what to do by using an array of data points and algorithms to form a prediction. For example, the system can tell an investment bank which of its institutional clients are at risk of ending their relationship or experiencing a significant drop in activity (such as event attendance) and revenue over the next six to next 12 months. Another example of guided functionality is a “Call Manager” application, where an institution’s salespeople and research analysts have dynamic customer lists that can be organized and prioritized by industry, buyer customer, or other segmentation. These lists are then easily prioritized, in seconds, by who to call when, based on what’s happening in the market, how traders are reacting, and even statistically determining when people are most likely to respond and to take a call.
Competitive advantage in good times and bad
The ability to ingest interaction data across all channels and identify meaningful interactions through natural language processing, and capture customer data in the environment that would otherwise be laborious and expensive to process, gives businesses an undeniable advantage.
In today’s fast-paced and unpredictable world, simply updating a CRM system is not enough – the only option now is to upgrade to nothing less than a CRM-based advisory system. the data, because it is what will give the information necessary to excel in all areas. market conditions. By thinking bigger and more ambitiously than current systems allow, new technologies can break down barriers and for the first time truly automate and systematize a customer strategy process.