Digital transformation – the “radical rethinking of how an organization uses people, technology, and process to fundamentally change business performance,” according to luminary George Westerman, as cited in CIO – is a major priority for the financial services sector.
Research from Gartner, for example, indicates that a staggering one-third of financial services CIOs identified digital transformation as their top priority in 2019. This is up from only 8% the previous year. If financial institutions plan to keep up, or better yet, outperform the competition, they will need to adapt to the digital age now. As a business strategy, and no longer just a technology strategy, moving to digital will lead to opportunities of faster, cost-effective operations, meeting regulatory deadlines, improved employee and customer experience, and remaining competitive.
But operational complexity, legacy systems, and a rigorous regulatory environment make it difficult for financial services leaders to pivot as nimbly as their counterparts in, say, the retail or travel and hospitality sectors. As one digital marketing leader at a retail bank recently told us: “Sometimes it feels like I’m fighting with one hand tied behind my back.”
That might help to explain the gulf between the industry’s aspirations and actual outcomes. Indeed, according to research from BDO, 68% of financial service organizations have developed a digital transformation strategy – but only 14% are actually in the process of implementation.
So what’s holding financial services organizations back from achieving the gains of digital transformation?
It’s worth acknowledging that digital transformation takes many forms: everything from more intelligent digital advertising, to launching more complete digital offerings (e.g., a mobile app), to entirely new digital products (e.g., the bulk of Fintech). I’d like to focus here on challenges that we often observe with our clients in the financial services sector: specifically, using customer data to power a more personalized journey across touchpoints and throughout the lifecycle.
With that in mind, here are three of the challenges that we observe most commonly with the companies we work with in the financial services sector:
Challenge 1: Data is distributed across systems that don’t communicate with one another. It’s hard for a bank to deliver a personalized credit card offer to a checking account holder (when that customer logs on to the mobile app or calls to make a balance inquiry) if credit card data is not unified with retail banking data. A vast number of financial services firms still have mainframe technology at their core. Many have evolved their technology stakes to include an Enterprise Data Warehouse (EDW), but we often observe challenges in gaining a “single view of the customer” when existing environments a) don’t co-locate data from different lines of business or b) don’t provide a mechanism for resolving records associated with the same customer (who might be assigned different identifiers as, say, a cardholder and a checking account customer).
Challenge 2: Relevant insights are buried in mounds of data. Even with relevant data unified in a single environment, it can be daunting to mine for insights in a massive ocean of consumer data. An analytics team working on a single credit card portfolio, for example, might be tasked with building dozens of models: response propensity, approval likelihood, balance consolidation affinity, reward sensitivity, early fraud detection, net credit loss prediction, and many more. Each of these models require sifting through a veritable mountain of data, comprising first-party consumer behavior and preference data along with second-party data (through data-sharing cooperatives like Argus) and licensed third-party data on demographics and affluence. Analytics teams are often strained, especially when the aperture is expanded to include a portfolio with many types of financial products.
Challenge 3: It’s hard to prioritize across all of the potential areas for growth. Many banks offer a complex portfolio of retail and commercial financial products. The number of potential customer journeys across checking and savings accounts, personal and business loans, credit card products, mortgages, and wealth management options can create “analysis paralysis” – both in figuring out where to dig into the data, and then in actually operationalizing these journeys. For example, think about a wealth management cross-sell campaign to existing mortgage customers. What channels should that campaign be launched on? How to train customer-facing branch employees and customer care agents appropriately?
Our advice to the financial services sector is to focus on building a comprehensive data foundation that delivers a true single view of the customer. But just having a single customer view isn’t enough. In order to provide tangible business values for teams, as the above challenges suggest, that view must be:
1. Tailored to concrete use cases – arrived at through rigorous cross-functional prioritization
2. Accessible to stakeholders throughout the organization
3. Flexible to grow over time as the business evolves
Ultimately, an accurate, accessible, action-oriented, and adaptable single customer view is a critical step on the path towards digital transformation.