By Ron Wellman
New data shed light on commercial and consumer relationship-based banking.
With the rise of customer-savvy fintech disruptors and low consumer trust in the financial services industry, it’s no secret that banks feel the pressure to drive personalized customer experiences.
However, statistics show that banks are slow to accelerate this move from a focus on selling products to selling customer-centric relationships.
A recent study conducted by Forrester Consulting on behalf of Pegasystems found:
- Only one-third of the 250 banking professionals surveyed have successfully made the transition from product-based to relationship-based selling to remain competitive.
- Another 29% are still deeply stuck in product-based selling approaches that often prioritize booking revenue over the real needs of each customer.
However, the wide majority of firms surveyed realize they must make this shift—and soon.
While the survey focused primarily on retail and small and medium enterprise (SME) banking, similar principles apply to commercial banking as well. Businesses expect the same experiences as consumers. They want you to show up with value-added input on how to better manage their operations, and demonstrate a keen awareness of their unique needs and preferences for engagement.
In transforming operations to focus more on client needs and less on product sales, commercial banks should increasingly be leveraging the next-generation technology available—particularly artificial intelligence (AI).
Leverage AI to empower client centricity.
One way banks can successfully shift to relationship-based selling lies in the data these institutions have on their customers. Simply relying on memory from past customer interactions is inefficient and lacking when trying to deliver the full picture of the client and situation.
Customer data can provide a rich resource when used in an intelligent way—the question is how?
AI and analytics are key tools in intelligently interpreting data for more customer-centric practices. Of the survey respondents who have already implemented relationship-based selling, 92% leverage AI to some degree.
The focus on the customer goes hand in hand with AI. It’s facilitated by AI’s ability to aggregate vast amounts of client information—from past interactions to current context—and inform the next best actions to take with each individual client for optimal outcomes. Successfully managing the customer relationship requires a core understanding of the target audience and strong interpersonal skills. This holds true whether it’s working with a consumer to open up a credit card account or a relationship manager at a large corporate bank trying to navigate due diligence required to onboard a new client, including its entities and staff.
Turn relationship selling into business benefits.
While the transition to a greater focus on the customer is obviously a tremendous way to improve customer experiences, it also creates business opportunities for banks. Of the survey respondents who have shifted to this new selling model:
- 85% indicated their customers are more loyal.
- 81% reported increased customer satisfaction with products.
- 79% received more referrals from customers to friends and family.
This can likely be attributed to an increased ability to provide meaningful touchpoints to customers that ensure the bank has the customers’ best interests in mind.
For any bank, commercial or retail, the path to creating a customer-centric culture is built on deepening the human connection between bank and customer.
For example, a client’s incorporation date can be recorded and recognized by the AI system, which then presents the recommended action to the salesperson to send a bottle of champagne to celebrate a milestone anniversary. Banks that have used such tips to their advantage have created business opportunities because they strengthened the relationship with their clients on a personal level.
Statistical analysis and data provide greater accuracy than people’s memories of conversations. Particularly with the turnover of salespeople, that learned knowledge of an individual’s birthday or a company’s milestone anniversary goes out the window and the next salesperson has to start from scratch. Having a centralized way of collecting and analyzing data makes for a much more efficient and effective way to track customer events and information.
In addition, robotics can also play a role in automated data collection and aggregation. Whether it is used to collect and display corporate prospect, market, and industry data for a new client, or it helps pull together data and information for an annual relationship review session, robotics can add efficiency on top of AI’s efficacy.
The risks of ignoring the shift to relationship selling.
All indicators point to a relationship-based approach as the future of commercial banking. Fortunately, modern technology has made this a very achievable reality. AI and robotic automation tools can uncover the actions taken by customer-facing professionals and reveal previously unseen opportunities to coach new behaviors.
A centralized decisioning platform can identify—and recommend altering—salesperson practices that focus on product selling at the expense of what’s best for customers, and vice versa. Using automation and AI, companies can deduce the next best action for both commercial and consumer sales.
Given the change in customer expectations that will come along with these advances, you’ll increasingly risk alienating customers with a sales-centric approach.
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., including SVP of external strategies for small business, developing technology solutions for global corporate clients at RBS Global Transaction Services, Americas, and leading the retail e-Commerce channel for Citizens Bank. Email: firstname.lastname@example.org.