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Customer Data Management Challenges in Financial Services

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Previously, I discussed personalization’s future in financial services. Today, I will dive into the customer data management challenges financial companies might encounter when starting their personalization journey.

Data management in any financial services firm is complex. It needs to address integrating identifiers across available touchpoints and devices, customer preferences and interests, data sources that include first-, second-, and third-party data. Data management capabilities need to be capable of managing structured and unstructured data, preparing data for analytics, and, of course, protect personal data across the data supply chain.

To become more data-driven and personalize customer interactions, you need to address three key data management trends: volume, ubiquity, and user demands.


It’s a data-intensive business. Internally generated data like customer information, transactions, purchase histories, service inquiries, and claims information generate hundreds of millions of new data points on a daily basis. To add to this complexity, much of the data is unstructured.


Data is also everywhere. The number of data sources, coupled with the rapid growth in storage capacity, computational power, and connectivity, has led to data being created and processed on an unprecedented scale. The nature of the internet, the growing number of interconnected devices, and the rapid pace of automation mean that data creation will continue to rise at a rapid rate.

Not only is there an explosion in the volume of data being generated, but the velocity with which it is transmitted and the variety of forms that data may take are also multiplying. Structured and unstructured data sets can take a number of different forms, encompassing traditional data, alternative data, and big data. Each data type varies in its maturity and usage, with less-mature types requiring a degree of specialized or even novel techniques for effective processing.

User demands

Today, almost every employee in financial services is a data analytics user who needs the speed and information equivalent to what they experience with personal consumer technology. Users are demanding self-service access to data and easy-to-use tools for decision support and trend identification. And, of course, they need to trust the accuracy and security of that data.

It is no surprise that the current data management landscape is complex – in our client work we see multiple data lakes, data warehouses, operational applications, mobile apps, online apps, call centers, and analytics solutions. Data can be, and usually is, located in hybrid environments, on premises, and the cloud, making it challenging to connect it all to drive meaningful insight into customers, products, and sales channels.

To learn more about the state of personalization in financial services and how you can begin to leverage customer intelligence to champion personalization and win over customers, download our guide here.

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Scott Albahary, Chief Strategist, Financial Services

Scott Albahary applies his wide range of knowledge and skills to advise Perficient’s financial services clients on business and technical strategies and on defining, developing, and implementing these specific strategies.

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