AI can help amid industry consolidation, staffing shortages

While artificial intelligence is often seen as a job killer, the Great Resignation has spotlighted the limitations of support and integration operations reliant on traditional workforces and approaches.

AI is a job killer. That was the standard reaction I received whenever I spoke about the efficiencies of artificial intelligence-enabled solutions for the financial services and insurance industries. Critics accused me of favoring profits over people.

Then reality set in as forward-looking firms implemented technologies that generated opportunities for employees to focus their efforts on driving client engagement and satisfaction, and addressing complex service requests. Almost universally, early-adopting companies saw higher client and adviser satisfaction largely as a result of highly trained staff being free to respond to the most difficult service requests. However, the connotations persisted — the AI-enabled technologies were coming for people’s jobs.

But as the industry faces the compounding trends of M&A-based consolidation and staffing shortages during the largest generational wealth migration in history, the promise of AI-enabled technology has shed much of its negative perception. Today, decision-makers search for solutions that can enable them to navigate these uncharted waters with additional scale and ROI, and their search often leads them to AI-supported technologies.

The financial services sector has considerable further growth potential as firms continue to expand through M&A activity. But wealth management firms, insurance companies and other players must address their antiquated support structure and mindset. The Great Resignation of 2021 has spotlighted the limitations of support and integration operations reliant on traditional workforces and approaches.

It’s imperative to reimagine support functions more holistically. It’s now widely accepted that deploying contextual intelligence systems like natural language-driven knowledge assistants, guided decisions and next-best actions improves support KPIs.

But AI-enabled technology must also address the daily life of the support staff, including taking care of their learning needs, managing their calendars and understanding their needs. In short, the goal of the technology should be to enhance the job satisfaction of the support staff, thereby transforming the support function and making it a critical part of the customer satisfaction goals.

For this industry to capitalize on its potential, it must embrace a future supported by AI-enabled solutions that make smaller, more specialized back-office and home office staff better at their jobs. When correctly implemented, we have seen AI-enabled technology enhance the abilities of a firm’s support staff to deliver services to advisers and agents and, importantly, to its clients. AI-enabled tools allow well-trained, dedicated teams to provide better experiences faster and with fewer mistakes without investing in additional human resources.

Reimagined this way, the technology frees both support staff and client-facing personnel to focus on revenue-generating activities by automating critical workflows and cutting down on the tedious processes required to open or transition accounts while reducing costly “not in good order,” or NIGO, errors. The M&A-based expansion will more quickly yield organic growth opportunities for firms that implement AI-enabled solutions focused on these support functions.

Additionally, these technologies can help advisers and client-facing professionals reach better, more informed conclusions faster than traditional methods. Applying an AI-powered guided decision-making process that draws upon a client’s goals and current positions, potential products and market trends, among many other potential data points, can provide a personalized recommendation for future action through a common simplified front-end for advisers and clients alike.

This technology can unify disparate information sources through a system that shares the same information and knowledge. It will drive better solutions at a lower cost for all parties and yield better returns.

Perhaps most critically, as these tools are not designed to replace support staff, AI-enabled scenario-based learning solutions help firms train new back-office and call center staff to provide highly specialized services in less time and at a lower cost. By complementing traditional classroom training, these smart training programs offer both employers and new staff the opportunity to get real-time information about how best to further the training process and more quickly and effectively get people into the roles that desperately need filling.

The pressure to identify, scale and drive efficiencies in the face of staffing shortages, increasingly stringent compliance requirements and client demands requires a new way of doing business. Applying AI-enabled technology within the financial services and insurance spaces can address many of the most common problems found in today’s back office, freeing people to focus on relationships and drive value for all stakeholders.

There is no question that people remain an essential aspect of a support function within the highly regulated financial services and insurance sectors. But all the evidence points to the fact that reimagining the support staff’s experience with the use of AI-enabled solutions, especially within these complex industries, drives significant efficiencies and enables better outcomes across the spectrum of support.

Dr. Sindhu Joseph is co-founder and CEO of CogniCor, an AI-powered digital assistant platform for financial firms.