Artificial Intelligence

How to Get the Edge on Data & Analytics in Banking

Bankers need personalized analytics tools in order to deliver their clients global industry knowledge.

Data & analytics play a crucial role in many industries, especially in commercial, corporate, and investment banking. Corporate and commercial banking clients are now looking for personalized offerings from a wide array of services. A one-size-fits-all approach is no longer satisfactory for these clients. Relationship managers (RMs) have the greatest responsibility to meet clients' complex demands for a more personalized client experience and are already some of the busiest employees at a bank. Time is extremely limited for these bankers, and having a competitive edge is becoming increasingly challenging. 

According to a McKinsey interview with executives at more than 15 banks, many reported that they struggle with client acquisition, and most of their RMs acquire less than five new clients a year. This leaves considerable revenue on the table, both from new opportunities and from untapped value propositions that could benefit existing customers.

Bankers are looking for personalized offerings drawn from a wider array of services.  Clients expect the banks to have industry-specific knowledge and expertise to work with them across their global supply chains and help them tackle new challenges. The need for advanced analytics tools has increased based on the evolving needs of both bankers and clients. At the forefront is the need for personalization in their workflows so they can provide their clients with the most current and relevant knowledge. 

Advanced Analytics Tools

With the evolution of AI solutions like ChatGPT, bankers are getting some relief with the ability to automate workflows and tasks. However, many of these tools still lack personalization and context which is a vital part of being successful with their clients. 

AI tools can give bankers a significant edge in surfacing relevant data and analytics insights in banking. With ChatGPT, data insights are easier to grab. And with ModuleQ's People-Facing AI, relevant insights are delivered effortlessly. Leading corporate and commercial banks are using advanced analytics to empower relationship managers in key areas.

Cost-cutting is easy to measure, but growth and productivity are harder to measure. "The study done by McKinsey is really powerful in that they were able to do a controlled experiment, and you can attribute the improved performance to the analytics," said David Brunner, PhD, Co-founder & CEO of ModuleQ. "This is exactly the kind of insights ModuleQ can help with. Dashboards are great, but they can be out of sight out of mind, and you may miss something that creates an opportunity. ModuleQ is proactive, right there in Microsoft Teams. Even the busiest professionals see it."

ModuleQ

According to McKinsey's study, 75% of banks are still getting started or experimenting with their advanced analytics efforts. ModuleQ is not a controlled experiment, but we do see professionals that use it the most frequently have 32% more client interactions. Tools like ModuleQ are easy to implement and deliver personalized, relevant research and data directly from your CRM.

As noted by McKinsey, there is a large need for pre-client meeting preparation. ModuleQ can deliver a pre-meeting briefing that does relevant client research for you. Surfacing insights from trusted news sources, and internal CRM systems, and scanning your proprietary research briefings, ModuleQ can deliver what bankers need to know, all in a platform they already use: Microsoft Teams.