Personalization has become the watchword in financial services today. A 2021 PSCU consumer survey found that nearly eight in 10 respondents prefer working with a financial institution (FI) that knows them on a personal level — a relationship that appropriate data usage can facilitate. This is one reason why 11% of credit unions (CUs) surveyed said they were considering replacing or upgrading their data analysis systems during the 2021 calendar year.
Most CUs have realized the need for a data-driven strategy in decision-making, as efficient use of the data they already have can provide valuable insights into their members’ needs. Despite the importance of data in customizing products and services, lack of data was one of the innovation challenges that increased for CU executives this past year, from 18% in 2021 to 20% in 2022.
Legacy technology systems often hamper obtaining and leveraging the right data to develop relevant CU offerings. This is because traditionally siloed systems were never designed to operate in a way that can inform a tailor-made experience. Platforms and data analytics, however, can connect silos to deliver custom financial services that improve members’ lives. In addition, CUs are uniquely positioned to create these experiences because of the trust they have already built with members.
Data: The Key to Personalization
A study from Capgemini noted that banks have troves of data that they struggle to transform into actionable insights. Seventy percent of global banking executives said they lack sufficient data processing and analytical capabilities, and 43% reported problems with siloed data. 
Nearly all — 95% — said legacy systems and core banking platforms undermine the optimization of data and customer growth strategies.
With 75% of banking customers saying they are attracted to FinTechs’ seamless services, it is critical that CUs leverage data and technology solutions to fashion tailored experiences. Driving personalization with data requires powerful analytics, artificial intelligence (AI) and machine learning (ML), and the use of enhanced data governance models to maintain data security and privacy. AI and ML can sort through large amounts of data to help craft compelling, personalized journeys for specific members.
Legacy banks and CUs can embark on this process in a number of ways. Many FIs are turning to platform business models, partnering with third parties to enable data collection from larger ecosystems that can provide real-time insights. Banks still have difficulty executing these platforms, however, with just 22% of chief marketing officers saying they have access to the complete customer profiles needed to effectively customize their products or services. CUs may have to tap FinTech partnerships to create the curated experiences their members crave. It is only through personalization that CUs can upgrade the banking experience in a way that ensures effective consumer engagement and long-term member relationships.