Co authors:
Alex Mohelsky, Partner, Advanced Analytics & AI Leader, EY Canada
Tijil Dewan, Manager, Customer Strategy & Transformation, EY Canada
Amisha Khatri, Senior Consultant, Business Strategy & Transformation, EY Canada
Tannor Pilatzke, Manager, Business Strategy & Transformation, EY Canada
Next best action capabilities present a big opportunity for wealth managers to have highly engaging conversations with their clients at scale.
Next best action (NBA) has been around for quite some time. However, its full potential has yet to be tapped. You can read more about how NBA can be a competitive advantage here.
NBA capabilities present a big opportunity for wealth managers to have highly engaging conversations with their clients at scale. But the actual execution of this capability is impeded by a few challenges, such as the availability of data and the requirement of a cultural shift. But these challenges can be overcome if the right approach is taken in embedding NBA in advisors’ and clients’ day-to-days. It starts with identifying the outcome that NBA is trying to achieve to how the model is built and delivered to users.
Let’s dive into strategy, technology and channel considerations when implementing an NBA offering.
1. Defining the right strategy
Define what NBA means for you: Even before thinking about implementing NBA, an organization needs to know what business outcomes and value it’s trying to derive from it. This can be anything from enriching the client experience to improving advisor productivity. The end goal will always determine how data is ultimately used and presented to its end users.
For instance, if the target outcome is improving advisor productivity, then presenting data in a way that saves manual effort for the advisor will be key. However, if the goal is to enrich the client experience, then understanding what data is important for customers and arming advisors with this information should be the approach. Sometimes the approach for various outcomes may overlap, but it’s still imperative to define the objective.
This flow chart illustrates learnings from client actions and outcomes that should be used to enrich the data catalogue, the predictive model, its recommendations, and the delivery channel.1
Identify key stages in the customer journey: Each interaction point between the client and the advisor is a new journey that the client undertakes. Therefore, identifying high-impact journeys will help increase the value of NBA implementation. For instance, during a market downturn, certain clients may reach out to their advisors. NBA can identify this situation and help advisors prepare for these interactions. From the implementation perspective, these interaction points will clearly demonstrate NBA’s value to leadership and identify quick wins that can be enabled with relative ease.
Develop and promote the concept of “empowered advisor”: Advisors traditionally conduct manual research about their clients — effective, yes, but very time consuming. NBA technology empowers them to accomplish the same research efficiently and at scale. This empowerment also comes with the advantage of arming advisors with the right information at the right time to drive trust, engagement, and growth. It keeps advisors engaged more frequently with clients at micro moments that matter. Therefore, it’s vital that this concept of the empowered advisor is promoted to ensure that the teams come back to it when answering key questions and making decisions during implementation.
2. Defining the right model and technology
Once the strategy is aligned, you should start to assess the technology that will enable this NBA capability. This will involve assessing the technology ecosystem that will sit around the capability and building the model itself.
Set up a strong data foundation: Availability of accurate and strong data will play a major role in obtaining trust and buy-in from stakeholders around the organization. Therefore, it’s critical that a strong data foundation is set up before the NBA model is implemented and shared broadly.
That means setting up a data catalogue and identifying data sources that will feed the model. It also means assessing the data accuracy and adoption levels of these sources. For instance, systems such as CRM, sales and marketing platforms and customer book of record capture customer information that may feed into the NBA model. So if there are issues with these systems, such as low usage or data inaccuracy, it's likely that the same issues will present themselves when NBA is rolled out. To prevent this, it is pertinent to address any foundational data issues in the ecosystem up front.
Building and training the model: Organizations typically look at one of two approaches when building out the NBA model — recommendation engine or end optimization.
The recommendation engine approach enables the model to recommend actions and offer insights based on how a subset of clients will act in a specific situation. The model learns from a large client data set, groups them and offers recommendations based on groupings of those clients.
On the other hand, the end optimization approach would enable the model to focus on a customer’s lifetime value. For instance, based on a customer’s situation, if there are five different actions the organization can take, the model would recommend the action that’s best suited to extract the most value from the customer.
Either of the two approaches can be selected to build the model. Data availability and the organization’s strategic objectives will dictate which option is better suited.
3. Defining the right delivery channel
One way NBA is delivered to clients is through their advisors who share personalized recommendations with them through their interactions. This works well for clients who prefer getting their advice delivered in a more personal way.
However, for clients who prefer digital advice, NBA can be delivered directly to their digital portals. For these clients, organizations could consider rolling out NBA along with their digital advice platforms. Given that worldwide digital advice AUM has grown from $0.2 trillion to $2.4 trillion in the last 5 years,1 it’s very apparent that more and more clients are incorporating it as part of their investment strategies.
Generative AI & Next best action (NBA): Recent investments in gen AI present another opportunity to take NBA offerings to the next level. AI-powered capabilities using machine learning and large language models have the potential to streamline advisor workflows when searching for client data and formulating/summarizing recommendations. These NBA recommendations can then be exposed on digital advice platforms for clients to view and action.
With budgets being reallocated and new capital being raised to develop various applications of gen AI, organizations can tap into this opportunity by exploring how AI can boost their NBA capability.2
Getting ready to deliver better experiences
Successful implementation of NBA must start with a well-defined strategy and then by answering questions about the technology, teams and delivery channel. A well-implemented NBA solution will not just enhance user experience, it will also improve the overall economics due to its scalable nature.
If your organization is ready to start the NBA journey, visit ey.com/ca/wam and reach out to one of our Wealth and Asset Management advisors to start a conversation.
