How to Improve Banking Efficiency Ratios with AI

• The Investment Banking talent equation has traditionally focused on hiring the best and brightest and hoping they become revenue-generative. 
• With banks focused on improving efficiency ratios (cost over revenue), many are looking to AI as a tool to improve. 
• While early indications from industries such as tech suggest AI can reduce costs, we believe AI in Investment Banking is better suited to increase revenue generation. 
• ModuleQ’s Unprompted AI is specifically designed to improve the bank’s efficiency ratio. 

What is the talent equation for today’s investment bank? If you ask a bank’s human resources lead, they can walk you through a thoughtful strategy unpacking on-campus recruiting, industry-level competitive intelligence, and benchmarks for maturation. They can also give you detailed statistics on retention and work quality. But if you’re looking for a succinct (and somewhat glib) response, we like the following, paraphrased from a major banking executive: hire the smartest people you can and hope they make money. 

This approach aligns with a bank’s targeted “efficiency ratio,” where operating costs (more than half of which can be the bankers’ compensation) are divided by banker revenue generation. Traditionally, the approach towards an improved ratio was to hire the best and brightest, improve the firm’s brand, invest in efficiencies, and hope these individuals develop strong business generation acumen. 

The Investment Banking Talent Funnel 

For years, this approach has shaped the investment banking talent funnel. The result is a funnel that is extremely strict at the top, narrowing rapidly from college applicants to Managing Directors. That winnowing comes with significant turnover and its associated cost. While some turnover is inevitable in a competitive industry, some also result from the industry's inertia in adapting to change. 

Unpacking the Investment Banking Talent Funnel 

We all know that first-year analyst hiring is highly selective, focusing on high-achieving graduates from top universities. Even with this selective process, talent retention remains a challenge. Significant resources go into training and development, only for a large portion to walk out of the door. It’s no wonder many financial organizations look at Investment Banking as the finishing school for their own selection of young talent. 

While getting off the ground floor requires a high degree of attention to detail, conscientiousness, and teamwork, these skills are mere table stakes for being considered for senior roles. Market fluency, strong networks, and business development skills become increasingly important. Additionally, juggling various client relationships while keeping them happy and engaged is crucial. 

The Question Banks Need to Ask: Does the Hiring Strategy Translate to Revenue Generation? 

The critical question banks need to ask themselves is whether their initial hiring criteria translate efficiently into business development potential down the line. Is there a way to improve this efficiency by investing in tools that can boost revenue generation? In short, does the current talent funnel ultimately deliver an improved efficiency ratio for the firm? 

Improving Efficiency Ratios with AI: A Balancing Act 

Every investment bank is in part trying to improve that efficiency ratio, especially if they are publicly traded. This has been challenging in today’s interest rate environment with slower IPO and M&A activity. As the FT has rightly pointed out, many banks view AI as a tool to improve productivity. For example, there are early anecdotes from technology companies suggesting that junior developers are becoming less relevant now that more seasoned coders are equipped with AI coding tools like Copilot. These tools allow them to handle more introductory and repetitive coding tasks typically done by juniors. Banks might see this as a parallel way to improve the numerator (cost) part of their efficiency ratio. 

AI and Financial Services: A Different Approach is Needed 

While AI will undoubtedly change the cost structures of many firms, we believe the engineering analogy may be misguided when applied to financial institutions. Early indications from large language models (LLMs) performing specific tasks in legal and financial fields are less promising than coding Copilots. A recent study demonstrates that even LLMs trained on specific data sets in finance (e.g., LexisNexis legal data and Thomson Reuters financial data) struggle to maintain the high accuracy level required for analyst-level work. Diligent analysts will still be crucial to ensure error-free materials. 

ModuleQ's Unprompted AI for Revenue Acceleration 

At ModuleQ, we take a different approach. We believe in applying AI to the denominator of the efficiency ratio: revenue generation. Our Unprompted AI is designed to push information to bankers alleviating the burden of searching or prompting for relevant information, allowing them to pursue more revenue-generating opportunities. To achieve this, bankers need tools that can reduce repetitive tasks while understanding their workflows enough to help them win or retain business. ModuleQ delivers the right information from trusted internal data sources, enabling bankers to connect with clients and prospects using fine-tuned and accurate information.  

Traditionally, acquiring the necessary information to nurture opportunities and close deals meant navigating a complex set of internal and external data portals, along with sifting through vast amounts of email. ModuleQ stitches all of these data points and insights together using our patented Personal Data Fusion, delivering only relevant and timely insights to bankers directly within their workflows.  

Our user analysis across a large cohort of investment bankers demonstrates that bankers who use ModuleQ’s Unprompted AI engage more with their firm’s CRMs, driving a better understanding of clients and prospect interactions across the bank. This leads to better awareness and stronger touchpoints with their clients. 

Source - ModuleQ 

By empowering bankers with the right information at the right moment, we are freeing up their valuable time to expand pipelines and engage directly with clients. AI augmentation is what will drive revenue and allow bankers to come prepared for every engagement. 

In a follow-up post, we will walk through specific examples demonstrating how Unprompted AI allows bankers to be more productive and revenue-generative, improving the denominator of their bank’s efficiency ratio. 

Ready to Learn More? 

If you're interested in how Unprompted AI can help your investment banking team thrive, contact ModuleQ today to schedule a demo.