Embracing Hyper-Personalization in Benelux Banking & Financial Services

In the drive to embrace digitization across internal and customer facing operations, leaders in the banking & financial services sector are finding that going digital is not enough. In light of growing competition from data-rich neobanks, fintechs and big tech companies, there is a need for data-driven digital transformation if they are to compete with and outpace emerging challengers for customer mindshare.

This demand is, albeit indirectly, coming from customers, who increasingly expect enhanced services and more contextually relevant interactions with their financial service providers. With a data-led approach, banking & financial services organizations can begin to put the customer at the center of their organization and build solutions around them - in effect, to hyper-personalize customer relationships.

Putting hyper-personalization into practice, and embedding it uniformly across services, requires a top-down approach as leadership needs to recognize its priority status and set the strategy for it to be built into the organization’s digital transformation.

Understanding Customers in Real-Time

While the blend of behavioral science and data science for deeper customer understanding has been adopted to great effect in other areas, such as e-commerce and digital services, there are distinct characteristics of the financial sector that make the hyper-personalization playbook difficult to port over.

The main reason is the nature of the services banks offer to customers. In areas like retail or consumer goods, for example, hyper-personalization strategies such as customized sales messages are used to generate and capitalize on latent demand for products and services that bring immediate gratification to a customer. In banking & financial services, the services being offered, such as loans, mortgages or saving products, can have significant lifetime effects that don’t produce immediate outcomes. While a consumer’s behavior may offer implicit clues on their preferences, identifying the most suitable financial products for a multi-year timeframe involves a far greater depth (internally) and breadth (externally) of data.

There’s also the issue of disjointed services. Banks may have had different product streams running for years in product silos without proper data collection. From the customer perspective, it’s not unusual to find that they’re using different services or (legal) entities within the same bank, yet their personal data does not flow or replicate between the services. This creates unnecessary frustrations that reflect poorly on the provider. As the services of banking remain critical in the digital economy, it’s imperative that institutions are able to adapt to a new generation of customer and provide the low-friction services they expect.

Bridging this gap is not simple, as banking & financial services companies need to make this longer-term transition while still dealing with immediate pressures. The margins on traditional banking services are getting tighter, bringing a need to drive new services. The data is the most valuable asset they have to define their services, as it reveals a lot about their customers’ needs and preferences. At the moment it’s not being properly monetized, creating a need for more data-driven banking if they are to gain control of the marketplace.

Reshaping For the Future

Building the foundation real-time for data-driven transformation is no easy task. There are several critical challenges banking & financial services companies typically face in making hyperpersonalization integral to how they operate.

The first is data. Banks have a lot of transactional and business data, but are typically lacking in behavioral data. This behavioral data is vital to hyper-personalization and understanding context. Financial decisions, along with risk appetites, vary greatly depending on factors such as the individual’s stage of life, their income bracket and current financial commitments such as mortgages or investments. Interacting with customers based on any single set of data points could miss the broader context and risk getting it wrong or biased, often to the customer’s dissatisfaction.

The second challenge is compliance. Banking is still coming to terms with the latest set of regulatory requirements and conscious of the risks - financial and reputational - of misusing customer data. Understandably, hyper-personalization is a large step into potentially hazardous territory. Taking too conservative an approach, however, risks missing the opportunity altogether. Banks therefore need to find the balance between innovating the customer experience and staying on the right side of regulation. Where the balance sits must be defined from the top-down.

The third challenge relates to legacy IT environments and processes. For data-driven customer strategies, technology is only part of the equation. While IT infrastructure and payment rails may require multi-year modernization strategies, it’s often the people and process parts that financial organizations struggle with most. Internal fragmentation is reflected in a poor customer experience as customers interface with different services without a common intelligence layer in place. Modernization of technology therefore needs to run in parallel with the realignment of processes and upskilling of people to make sure the customer experiences a united front.

Taking the Lead in Banking & Financial Services

How then can banking & financial services leaders plan for and advance in data-driven initiatives in their organization? There are five key areas of concern.

1.    Structure Around the Customer

In order to tailor the services and present consistent messages, banks need to be able to micro-segment their different customer groups, including retail, private banking and wealth management. Without this context, personalization of services is meaningless. The growth of chatbots and natural language processing capabilities is helping in this regard, reorienting communications from a one-way ‘broadcast’ towards an active dialogue, which helps support more accurate profiling as the relationship develops.

2.    Take a Customer Lifetime Value (CLV) Perspective

Banking & financial services regularly involves decisions that can have large consequences for the customer. If the messages they’re receiving from their bank pushes them towards decisions that ultimately prove unfavorable, the outcome can irreparably harm the relationship and drives them towards competitors that better understand their goals and time horizon.

The application of data helps to give a better understanding of CLV so that providers can align strategies more closely with customer needs. CLV requires a top-down approach as it involves upfront costs, and possibly even sacrificing short-term sales opportunities, for lifetime-value gains based on the CLV business case. This isn’t an easy decision, especially for smaller financial organizations, so it needs to be directed from senior decision makers.

3.    Bring Together Data and Analytics Under One Umbrella

Capturing and analyzing massive volumes of real-time data is vital to delivering hyper-personalized services to customers. However, a disconnect exists in many financial businesses between the data function and engineering, such as cloud architectures, and the analytics function, for example data science teams. These areas are becoming so intertwined that the divide naturally leads to fragmented approach. There needs to be convergence between the functions at a strategic level, feeding through to the tactical level, or else the organization will never be able to achieve customer understanding at scale.

4.    Address Data Risks

Senior management need to understand how their organization is using and applying data - or else there could be major systematic risks they’re overlooking. This can be addressed at a technical level, such as safeguards within software, but also requires human skills, such as critical thinking, to address issues such a bias in AI programs.

While the ethical side of data and hyper-personalization may be a major issue for a bank, the answer isn’t to shut it down but to address the risks. This necessitates new skills and even new roles, such as a Chief Hyper-Personalization Officer, within the organization to manage the organization’s risk level.

5.    Embrace Open Banking

Banks are having to change the way they approach product developments as they can no longer own the whole value chain. While they didn’t have to think about hyper-personalization before, the customer environment is now an ecosystem play - meaning banks need to focus on what value they can deliver to the ecosystem and integrate with third-party products and services into a seamless digital customer journey.

Decisions on what services and applications to provide need to be made on the strength of the organization’s data, focusing on what unique value they can bring to the customer. Otherwise, it’s not worth building products where they can be integrated from other sources such as APIs.

Getting Hyper-Personal

When it comes to money and financial decisions, there’s no substitute for trust. Trust is rarely attained overnight, but built over time through a high quality of service and a dedicated focus on customer understanding. Established banking & financial services companies often find themselves in the enviable position of decades - even centuries - of reliable service and large pools of relevant data, counter-weighted against pressures, a growing number of mobile-native competitors and an onerous regulatory landscape. Bridging the gap towards trust and understanding by offering hyper-personalized products and services is vital to staying relevant to new and existing customers.

There are no shortcuts to getting to this level of data-driven customer understanding. The only way to do it right is by putting it on the agenda of the strategic committee, managing risks and making it the key source for delivering outstanding experiences to customers.

Learn more about how AI can play an important role in staying relevant and seizing business opportunities in the future.