From insight to action: How a global bank expanded lead generation with Moody’s

A leading global financial institution, headquartered in Europe, provides a wide range of services including investment banking, wealth management, asset management, and retail banking.

With a strong presence in major financial centers worldwide, it serves private, corporate, and institutional clients, offering expertise in navigating complex regulatory environments and delivering tailored financial solutions.

The business case

Wealth management is an increasingly competitive market, with more banking actors shifting toward fee-based business models, necessitating differentiation as competition intensifies. To stay ahead, incumbents are adapting and automating their legacy infrastructure and automating workflows such as client profiling, opportunity detection, and lead qualification.

The bank is seeking competitive advantage in wealth management by being proactive when opportunities arise, gaining market share by targeting new client sources, and enhancing client profiling.

As organizations increase in size, agility can diminish; this bank is addressing the issue by investing heavily in artificial intelligence (AI), aiming to demonstrate that it can leverage data and AI to enhance efficiency, deliver return on investment (ROI), and improve client satisfaction.

The challenge

The bank wanted to enhance its agility and efficiency — particularly in relation to wealth management, to generate leads and improve client profiling.

Its main challenge was leveraging AI and data to achieve these goals while maintaining high levels of client satisfaction and delivering ROI. Relationship managers (RMs) relied on a manual process in which someone had to sit between systems and push leads to individuals — an approach that was neither flexible nor efficient. In essence, the problem was twofold: a lack of automation and insufficient data coverage — both of which were addressed through Moody’s entity and news data integration.

The solution

Using Moody’s data not only enhanced the bank’s efficiency but also paved the way for a more strategic approach to understanding client needs and preferences. By leveraging Moody’s Orbis ID and linking it to the bank’s internal client system, it was able to automate lead routing — making sure, for example, a lead from client X would be assigned directly to the appropriate RM. This automation removed a manual bottleneck, significantly improving operational efficiency.

Additionally, growth was a major focus for the global institution, and that required a more comprehensive global news solution, adding a substantial number of relevant news publications to its news event monitoring. These publications often help signal liquidity events—key moments when clients may be most receptive to engagement. By identifying such events in real time, the institution was able to generate more leads effectively and take timely action to initiate meaningful client conversations.

Through enriched customer profiles and integration of expanded news data, RMs could delve deeper into the intricacies of their clients’ financial landscapes, such as their corporate holdings, board memberships, and sources of wealth. This granular insight was crucial for tailoring personalized financial solutions, allowing for more targeted cross-selling of the bank’s extensive service offerings, particularly feeding valuable opportunities into the investment banking sector.

Moreover, the systematic centralization of curated leads meant that RMs could access high-quality prospects more swiftly, cutting down on the time-consuming and often inaccurate manual research processes. As a result, the lead generation process became more streamlined, and aligned closely with the bank's overarching goal to leverage technology, drive operational efficiency, and ultimately uphold client satisfaction.

The outcome

Implementing Moody’s entity and news data led to significant improvements in lead generation and client profiling for the bank. Relationship managers became more efficient, and the bank was able to enhance cross-selling targets. Using AI and data in wealth management demonstrated the bank's commitment to innovation and efficiency, improving client satisfaction, and delivering improved ROI.

The bank is now better equipped to anticipate client needs and has a better vision of its broad source of wealth.