- In today’s emerging age of generative AI, to acquire, retain and grow engaged relationships, banks need to rely on three core tenets: knowing the customer, engaging with them with precision, and delivering experiences seamlessly across all human and digital interactions.
- To help, Curinos has developed a composable data architecture to enable customer-level decisioning quickly. It generates a central view of actionable data on deposits, marketing, lending and transactions data, allowing banks to measure the performance that will connect engaged customer relationships to enterprise value.
- This AI-fueled decision intelligence has helped reveal that mass market customers may be more valuable in the long term than initially perceived. And it’s amplified the power of the CRM by bringing the full view of customer behavior, including digital, to the branch setting.
The rate of change over the past few years of how consumers engage with their merchants and providers has been unprecedented, and it’s put considerable pressure on financial institutions as they compete to acquire and build valuable long-term relationships. During the pandemic, bite-sized content delivered through optimized feeds in what Curinos calls the Journey of Optimization gave way to the accelerating algorithmic content of the Overload Era. Since then, success has meant cutting through the clutter. Welcome to the Era of Resonance.
In this era, banking’s ability to acquire, retain and grow truly engaged relationships relies on three core tenets. First, institutions need to know the consumer, basing their decisions on insights that embrace the behaviors and preferences of each and on differentiated products and experiences that drive individual outcomes. Second, they need to engage with their customers with precision – at the right moment, in the right channel and with the right content. This means proactively serving up messaging in the context of where the customer is at that moment. Finally, they need warm, engaging experiences to be delivered seamlessly across all human and digital interactions.
All of this will require that providers dissolve the barriers to their silos and put the customer at the center of the action (Figure 1). Most of them have evolved from customer data based on product silos – or at least they’ve recognized that they need to – but too many now find themselves in the “messy middle.” That’s the twilight zone of decisions on one-off pricing, marketing and experience that are based on a fragmented, product-centric view of the customer’s current standing. Success going forward will require a 360-degree customer-centric view, to enable pricing and marketing decisions based on a line of sight into the customer’s current portfolio and where it may be in the future.
Figure 1: Evolution of Decision-Making Data
How Do You Make the Customer the Center of Gravity?
Banks sit on vast amounts of customer data, but systemic fragmentation and structural impediments impede visibility to the full view of each individual (Figure 2). Analytics capabilities are often underutilized for cross-portfolio insights, which means FIs have only a partial view of the customer’s deposits, lending and third-party non-financial data. And when business units operate by product instead of by customer journey, gaps in coordination and orchestration slow down action and lead to results that are either suboptimal or unintended. That, in turn, is reinforced by misaligned incentives that create short-term gains at the expense of longer-term sustainable profitability.
Figure 2: Impediments to Customer Visibility
To address these impediments and to help banks move toward more of a focus on the customer, Curinos has developed a composable data architecture to enable customer-level decisioning quickly. We start with standard product schemas that can provide a quick route to customer value potential and activation. (A single old-school deposit-centric dataset or marketing customer data platform (CDP) is enough to get started.) We then provide a customer-spine infrastructure that we apply to diverse data ingestion and enrichment (Figure 3). It can scale quickly to generate a central view of actionable data on deposits, marketing, lending and transactions, allowing banks to measure performance that will reveal meaningful opportunity.
Figure 3: Future State – 360-degree Customer View
By understanding each customer’s current and potential value, banks can engage with customers consistently across prospecting and relationship building. Supported by Curinos’ decision intelligence, they can execute across ecosystems with intuitive workflows that are informed by 360-degree customer insights, opportunity reports and peer benchmarks, scenario builders and performance reporting. These are the views Curinos uses to activate decision intelligence through our AI-driven Amplero Personalization Optimizer, which maximizes lifetime value for every customer according to each bank’s strategic objectives.
Actionable Decision Intelligence Explodes a Myth
Recently, many U.S.-based retail banking providers have turned their focus away from the mass market because it’s ostensibly too expensive to acquire and worth less to the bank’s deposit base than more affluent segments. But this strategy overlooks the fact that the mass market and mass affluent segments contribute value over different time horizons. It also misses the fact that a far larger proportion of less affluent consumers prefer to keep all their money with their primary bank while wealthier cohorts distribute their deposits with multiple providers.
Indeed, after five years, mass market balances that have been on the books for at least three months are 5.4 times greater than what they were when they were acquired. That’s almost eight times the relative value of mass affluent balances, which actually shrink after five years (Figure 4). The difference is stunning, if seemingly counterintuitive. Without the right intelligent decisioning in place, a bank pursuing more affluent customers would likely continue to ride the wave in the wrong direction.
Figure 4: Average Balance Change Over Time by Segment
1. Customer base established as those who are with the bank at three months on book (does not account for attrition in first three months) 2. Average balance indexed to customer balances at three months on book
Note: Based on consumer customers who entered through checking | Mass Market defined as <$10K deposit balances at M3, Mass Affluent >$10K deposit balances at M3
Source: Curinos Deposit Analyzer; Curinos Distribution Analyzer; Curinos Analysis
Drive Relationships, Not Transactions
Data reveal that the key to generating value with the mass market is to build for the long term, and to do so, many banks have learned that maintaining and deepening customer relationships requires personalized engagement. They’ve embedded next-best-action marketing platforms, which use some level of customer data to determine the most relevant action to take for a particular customer, and when. This relies on predictive modeling to suggest how to market to an individual in order to encourage them to engage in a way that is likely to drive immediate value through their next activity with the bank.
The problem with this approach is that banking isn’t transactional; it’s based on relationships that need to be nurtured over the lifetime of the relationship. Rather than recommending a single next best offer, the cannier optimization engines, such as Curinos’ Amplero, use AI to continuously weigh multiple objectives—such as deposit growth, cost of funds and long-term relationship potential—so the bank can invest in strategies that sustain profitable growth and deepen customer engagement. By doing so, they enable banks to find value in customers across segments.
For example, a $50-100bn FI sought new-to-FI growth for its premium checking and ongoing engagement and deposit growth across its back book, with an emphasis on checking and liquid accounts. It used Amplero to drive both acquisition targeting, post-acquisition onboarding and ongoing deposit growth both in branch and through digital channels. To date, it’s achieved a 300% increase in response to its acquisition marketing campaigns, and acquired customers have had an average of 250% higher funded deposit balances three months later. As an added bonus, digital engagement has increased on average 70%, resulting in a significant improvement to customer retention and long-term value (Figure 5).
Figure 5: Client Performance Impact
Key Metric | Uplift (vs. Control) | Comments |
Response Rate | +300% | Acquisition response rate |
Funded Balances | +250% (on average) | Average funded balances for accounts 3 months on book |
Digital Engagement | +70% | Digital transaction volume for new-to-bank accounts |
Source: Disguised client performance data
Bringing Data-Driven Insights into the Branch
Out of the rubble of the digital banking juggernaut and associated branch network withdrawals, institutions across the U.S. have started to rebuild physical channels, with investments being made across all sizes of provider. To differentiate themselves from the fintechs and direct banks, their multi-channel approach serves as an engagement effort across platforms. But to effectively advance any relationship in the physical space, bankers need the insights collected from each customer’s latest engagements. Many now use CRMs, but these tend to default to generic sales pitches that are informed by a few in-person signals and the branch’s own strategy rather than by the whole relationship. That’s because many of these relationship-tracking systems don’t record the most dominant channel, digital, so sales and cross-selling cues and suggestions are mismatched and out of date.
Modern CRMs need additional support and insights derived from the bank’s real-time interaction management (RTIM) tool. By doing so, the banker instantly knows that the customer’s wealth and debt is changing, their current cash situation and how they are digitally engaged. They’re provided with suggested products to offer and the potential value of each customer. Amplero CRM, for example, turns the CRM into a learning system through which bankers no longer see static fields and stale history, but momentum, signals and trends. Instead of guessing the next move, bankers are able to deliver specific, timely recommendations based on the customer’s entire recent history.
Actionable Decision Intelligence: Without It You’re Not With It
To succeed in today and tomorrow’s hypercompetitive environment, financial institutions need to change the way they acquire and build engaged relationships – those that ultimately lead to higher lifetime value and, in turn, value to the enterprise. To do so, they’ll need robust customer insights that are available only through decision intelligence that is continually enhanced by generative artificial intelligence.
Decision & Action Takeaways
Decision to be Made | How to increase and strengthen engaged, personalized customer relationships as a means to greater customer lifetime value. |
How It Affects Total Customer Value | Customer value emanates from engagement – when to touch customers at the right time with the right offer or message, or not touch them at all – rather than relying on a series of disconnected propositions. AI-fueled continuous learning informs a sequence of next best actions that ultimately leads to a stronger bond and accumulating lifetime value. |
Action Recipes |
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Guardrails | Marketing efficiencies, prospect conversion and deepening performance are benchmarked at competitor level, allowing institutions to monitor performance across acquisition and growth metrics, making tactical changes to optimize appropriately. |
Expected KPI Lift |
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Curinos can apply its AI-driven decision intelligence to help your institution view, model and act on a 360-degree understanding of each of your customers based on their holdings, behaviors and actions. Find out more about AI-empowered Decision Intelligence from Curinos
