In Customer Intelligence & Insights, Digital Transformation

The following is a guest blog post by Jerry Silva, Research Director for IDC Financial Insights.


The importance of the customer lifecycle is increasing with every new interaction consumers have with the enterprises that add value to their lives. Based on their experiences with companies like Amazon, Facebook, Google, and more, consumers are not only embracing a digital lifestyle, but demanding it. As is the case with many phenomenon, there are two sides to the success of these kinds of firms: the first is what happens at the customer end of the interaction, the convenience and availability of access to the services of digital enterprises through mobility and cloud-based infrastructures. The other side of the interaction is hidden from the consumer but affects every interaction in a profound way: the data and analytics that drive what the enterprise knows about the consumer, and how that information is used to further the relationship in the name of customer satisfaction and company revenues.

In the financial services industry, PayPal has learned to take the payments data it has aggregated over the years from buyers and sellers, and used analytics to create new product offerings. For example, using receivables and payables data and creating analytics-based risk management models allowed PayPal to offer small business lending, and expanded the value they can provide to their customers. However, this use of data and advanced analytics is something that most banks have still not accomplished, much less mastered.

There are many reasons why banks are falling behind other digital-native enterprises in their use of data and analytics: legacy technologies, siloed systems, organizational models that don’t reward enterprise-wide views of the customer, and policies based on the institution’s appetite for risk and regulatory pressures. But rather than let those things preclude the possibility of a powerful, data/analytics based customer strategy, successful banks are embracing the need to transform in order to overcome those, and other, constraints. IDC Financial Insights believes that data and analytics are foundational technologies that will drive digital transformation at the institution. As such, strategies must be created, from data quality and governance to analytics and omni-experience, that will guide the bank on a long-term path to earn the same place in the customer lifecycle already enjoyed by firms like Amazon and Apple.

This road is not an easy one, and one that will be made more difficult as consumer-centric regulations like the General Data Protection Regulation (GDPR) and the Revised Payment Services Directive (PSD2) make their way into the North American market, regulating how data is shared and protected. But banks must look at these kinds of regulations as guideposts that will help them determine their own strategies going forward. This is a movement that will not stop, and will only slow at the cost of customer discontent.

Financial institutions already have a wealth of information about their customers – from personal data like age, geography, and income, to lifestyle data like spending habits and preferences. This is information that can be gathered and mined to support customers through their financial lives. Beginning a financial relationship with a bank for the first time, paying for college, opening a credit account, buying a home or automobile, planning for retirement. These are all important milestones in a customer’s life that require financial support. If banks aren’t prepared to help, recent history has shown that new entrants are more than willing to step in and fill the gaps.  Knowing where the bank can play a role in the financial lives of its customers is the easy part. The hard part is committing to a data strategy that runs across the enterprise and survives executive sponsorship that seems to shorten every year as executive churn increases.

Commitment is the first step on the journey. Auditing the bank’s existing data and creating governance around it is another vital step. Determining use cases and priorities will help guide the tactical implementation of an analytics strategy, solving real life problems and taking advantage of market opportunities today while building on success. One critical aspect that many banks miss is the use of external data to fill out information that may prove successful in an analytics-based approach to customer relationships. Finally, very few financial institutions have the in-house resources they need to establish a robust and fruitful data and analytics environment. The good news is that 3rd party technology partners have a variety of analytics solutions and best practices – specific to financial services – that address many of the uses cases that banks can deploy and begin to build a robust data and analytics program.

Ultimately, every bank will go down a different road to achieve mastery in analytics-driven transformation. But for all banks, the destination is to be as embedded in their customer’s day-to-day lives as most of the digital-native enterprises have become.

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