In recent years and in many industries, artificial intelligence (AI) has transformed organizational strategies and outlooks in ways unthinkable just a generation ago. Now businesses must grapple with how to leverage this next-generation technology alongside a human workforce to drive even greater business value. But what does the mean, specifically, for the financial services industry?
Well, that depends. While AI-related applications already power aspects of retail banking, adoption has proven slower in the commercial and corporate banking sectors.
AI in retail banking has obvious potential. Digitally savvy consumers expect personalized, seamless experiences they’ve gotten used to from the Amazons and Ubers of the world. And as FinTech competitors enjoy disruptive success in mobile banking and payments, retail banks have an immediate impetus to embrace AI than their commercial and corporate counterparts—at least on the surface.
The truth is this: AI boasts immense potential to improve on the status quo across any sector of the vast financial services industry—with enhancing one-to-one client relationships at the core.
Clever leverage: AI facilitates and builds connections
Being a successful salesperson in any industry requires excellent interpersonal skills and a strong grasp of the target audience—whether that means a corporate executive at a Fortune 500 behemoth or a mid-level procurement officer at a regional organization. But relying on memory and note-taking based on past interactions with prospects or manual research proves inefficient to provide a clear, comprehensive 360-degree view of the person and situation.
Enter AI. Today’s AI and analytics tools can create a well-rounded image of the prospect by aggregating diverse background information that ranges from purchase history to date of birth. For example, the system can alert a corporate banking salesperson that a prospect successfully filed its articles of incorporation 10 years ago, prompting the salesperson to take the next best action of sending champagne to the business owner.
The simplest gestures can make the most impact—especially personalized ones that differ from mass marketing or sales giveaways. This one-to-one connection can help a corporate salesperson get their foot in the door, where a welcome mat waits on the other side.
First-class coach: How to model top performers
Traditional sales coaching revolves around routines and quotas: making a certain number of calls, emails or in-person visits per week to reach target goals to populate the pipeline and close deals. It’s a common-sense strategy, but a batch sales and marketing approach fails on two levels. First it treats clients as one-dimensional figures; and second, it neglects to account for the best practices of top sales performers.
As to the former, a salesperson who counts only on their research, communications with contacts, and knowledge of the account or prospect can miss the additional insights AI, big data or machine learning can provide—or at least benefit from the speed robotic process automation (RBA) provides. That means more time with clients—and with more time and more insight, they can refine those key products, services and solutions as well as the pitch, which helps them win more business. Not every action is about the next sale but rather understanding where clients find themselves on their journeys: about taking the appropriate next step at the right time.
Best practices like these often surface when we analyze the day-to-day activities and successes of top sales performers. By unifying AI and robotic automation tools to aggregate the actions salespeople take, commercial banks can unlock the full potential of the organization’s people, processes and technology. Previously unseen opportunities come to light that improve productivity and reinforce new behaviors that boost the bottom line. So follows a centralized decisioning platform that identifies common denominators of best behaviors—even as trends develop that lead to success—and thus empowers leaders to coach lower- and middle-tier performers who need help to secure better results.
Assess the success forecast
Operating a successful sales organization requires not only knowing how to engage with clients and prospects, but also understanding the chances a client or prospect will accept an offer. Today’s technology can feature personalized dashboards that offer a real-time view into pipelines, leads and forecasts, while clearly communicating changes and action items. With AI-based forecasting, banking sales managers can capture the most accurate, updated forecasting information to more precisely predict a probable sales win.
AI-enhanced forecasting can take numerous forms. For example, a salesperson makes an offer to a client, then sees a flurry of additional web traffic that inquires into specific capabilities of the proposed solution. Armed with this information, the salesperson gets a better grasp on whether the client is leaning toward signing the deal or moving elsewhere. Forecasting even works on a broader, industry-wide scale. By leveraging AI to analyze a market segment a bank can detect shifts around transaction patterns or renewed interest in particular investment solutions, salespeople can have these insights at hand when they advise a client on strategy. Some have even considered AI forecasting to guide capital adequacy planning well in advance.
With the right systems in place, corporate banks can obtain accurate forecasting and give personalized advice to their sales representatives so they can generate more revenue and deepen relationships.
An eye on the AI revolution
Commercial banks deal with constant headaches: from increased customer demands as FinTech and RegTech disrupt the industry, to eliminating silos and streamlining inefficiencies, and much more. But tech innovation in financial services is no longer limited to retail banking—nor should it be. Commercial banking salespeople must embrace the real intelligence of AI or risk alienating clientele and becoming obsolete. We don’t need robots or machines to tell us this, though we can certainly teach them how to make better sales leaders of us all.
Ron Wellman is a global director and industry principal for the financial services business line at Pegasystems. He has more than 16 years of commercial and retail banking experience, having previously held executive roles at The Royal Bank of Scotland Group/Citizens Bank, N.A.
Jeannette Kescenovitz, who leads development of banking-as-a-service at Finastra, joins us on the BAI Banking Strategies podcast to share her views on how BaaS might grow its presence at U.S. banks and credit unions this year.
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