Start Your Data-Centric Transformation Before It’s Too Late

There is a buzz in the air. In every office, boardroom and conference, there is talk of artificial intelligence (AI), blockchain, the internet of things (IoT) and other technologies that influence our lives. Technologies driven by data have incredible power to transform our lives and impact the decisions we make every day. According to a recent article in Harvard Business Review, many companies are embracing these technologies because they’re scared to death of being disrupted by digital companies that use data and digital technologies to remake entire industries.

Data is the fuel for transformation and analytics is the engine driving the execution of new strategies.
– Adam Craig

To take advantage of the power of its data, an organization must become data centric. It must be able to optimize the value from existing data, provide enhanced security and access controls, deploy performant and scalable analytics; combine data from a variety of data sources; and create a single source of truth.

Ultimately, the goal of a data-centric organization is to make intuitive and actionable data readily available to drive deeper and more profitable relationships, to attain true customer intimacy, and to enhance customer service. Data should be so accessible that it natively drives every decision within the institution, because, the only thing worse than not having data is having data and not knowing how best to leverage it. Up until now, this critical asset of the institution…data…is locked down in organizational silos and legacy systems, making it difficult for this transformation to occur.

Financial institutions have been facing this challenge for years, but with disruption by fintech startups and tech giants like Apple and Amazon, customer expectations have been raised and it’s time for financial institutions to respond and transform. These organizations have learned the value of unlocking the data at their disposal, and using it to create best-in-class service and experiences. In order to compete and to survive, financial institutions must respond and offer the same level of service and experience consumers have come to expect from the other organizations they have relationships with.

According to Harvard Business Review, in order to shift to data-centricity, financial institutions must prioritize analytics, innovate new technologies and build core competencies around data within their resource pool. The most effective way to do this is with the support and backing of key stakeholders. When this is effectively accomplished, the institution can realize goals that are inherent in any strategic growth plan – obtaining better insight into customer needs and expectations, enabling faster and more effective decision making, and improving processing and cost efficiency.

The alarming news is that the more financial institutions learn about what it takes to be data-centric, the more they realize how far off the mark they are. Based on results from this Winterberry report, fewer organizations self-identified as at least “fairly data‐centric” in 2017 (40.3%) than they did the previous year (54.3%), proving that the more educated we become, the more we learn what we don’t know. Even worse, the implication is that the growing divide between those organizations who are data-centric and those who are not, will leave an incredibly large number of organizations sitting on the sideline and falling farther behind at an alarming rate.

To the close the gap, let’s dive into why this transformation is important and review the roadmap to get there – not just from a technology standpoint, but from an organizational perspective as well. It will take people, process, technology, and the right partner to get the job done.

Where cleansed, organized, and analyzed data can add value

Data should never be confined to the IT department alone. When cleansed, organized, and analyzed appropriately, data provides insights to all functional areas of the organization, driving strategic decision-making and improved customer experiences. A data-centric financial institution will have the ability to extract new value and insight from existing data – data that may have been undecipherable in the past – and deploy both statistical and predictive analytics with high performance and scalability. By aggregating and centralizing data from multiple sources, the institution will create a single source of truth to deliver intelligence throughout the organization. Let’s explore how:

Starting at the top, Executives should lead the way by informing all decisions with data retrieved and aggregated from as many sources as possible. Understanding customer needs and expectations as a result of analyzing data will drive better informed and personalized customer engagements, and yield faster decision making regarding strategic growth opportunities. For example, with access to cleansed bill pay data, executives can evaluate the ability to achieve the bank’s new product growth strategy by assessing the volume of payment activity for held-away products. Using cleansed and classified POS transaction data, executives can gain a better understanding of customer demographics, lifestyles, life events, and the profitability of each segment to paint a clear picture of their customer base and build plans to target the audiences that will result in the highest growth potential.

The financial institution’s Product group can also use data to gain important insights to better understand the financial needs of customers currently being met by competing institutions. Product managers can evaluate the top competing institutions customers are choosing for borrowing and investment needs, and use this customer behavior intelligence to modify or build products to address prime opportunities; such as short-term loan products to compete with fintech companies and online savings products to compete with digital banks.

Marketing is a key function where data can enrich the personalized engagements a financial institution has with its customers. From identifying share-of-wallet opportunities based on understanding the market opportunity related to a product area, to micro-targeting campaign messages based on the lifestyles and life events of customers, data is a critical tool in the marketer’s toolbox.

Operations can use customer data to back many decisions. Whether it is analyzing the number of debit card swipes to ensure performant transaction processing, evaluating the number of transactions to display in an online bill pay portal to ensure performance of the app, or ensuring scalability as the customer base grows, data feeds the decisions that drive operational growth of the institution.

Additionally, thinking outside the box, the operations team can evaluate customer’s shopping brand preferences to evaluate new and existing branch and ATM locations to make customer errand running more efficient…that’s a game changer!. When access to clean, organized, actionable data is right in your hands, there’s no limit to the benefits the financial institution can realize.

There is so much potential to realize value from the mass amounts of data residing within a financial institution. Simply acquiring as much data as possible is not going to result in a successful transformation to a data-centric organization.

How to transform into a data-centric organization

Financial institutions can’t become data-centric overnight, and generally, not on their own. Data centricity is transformative, and transformation that rests upon complex datasets and analysis requires planning and expertise. Financial institutions must create a roadmap for their journey to being data centric—complete with data-oriented goals, technology changes, culture adjustments, and more. Transformation also requires a collection of data-related skills, technology, and talent. No single financial institution has all of these within their walls, which is why it’s important to identify a partner who can help bridge the gap between an organization’s current state and a data-centric environment.

Segmint’s proprietary technology, extensive analytical toolkit, and expert team of library scientists addresses this need with speed and accuracy. Its analytics platform cleanses, categorizes, and contextualizes billions of inconsistently labeled transactions to produce the actionable insights financial institutions need to empower functional areas and key stakeholders.