The Top Challenges in Financial Data Management
Three challenges currently frustrate banks’ efforts to better manage data: a lack of knowledge, talent and consistency.
- Lack of knowledge: Banks struggle to understand where their data is, where it’s going and where it’s coming from. This isn’t a new challenge: Recent survey data found that 89 percent of small and medium businesses feel underserved by their current banks and are considering a switch to fintech options. In large part, the dissatisfaction stems from how traditional banks handle data and deliver services; as more than 25 percent of banks still deal with monolithic and inflexible legacy infrastructure, this is no surprise.
- Lack of talent: Great data strategies demand employees with the appropriate skill sets. But banks are struggling to both keep existing experts and find new talent. According to American Banker, the turnover rate for banks reached 23 percent in 2022, significantly higher than 2021’s 16 percent. Finding skilled workers is also a challenge, with bigger banks now hiring 800 to 1,000 college students each year, widening the talent gap with small to midsized institutions.
- Lack of consistency: Even if banks know where their data is and have the talent to manage it, they still need to ensure that data collection, storage and use align with regulatory expectations. From the Payment Card Industry Data Security Standard to the European Union’s General Data Protection Regulation — plus the recent updates to the Federal Trade Commission’s Safeguards Rule, which significantly expands the type and number of businesses required to implement data protections — there’s no shortage of regulatory requirements for banks to meet.
However, as banks look to manage customer data across cloud services, local stacks and remote work connections, it’s easy for expediency to outweigh compliance efforts, putting banks at risk of costly violations that could lead to monetary fines or reputational damage.
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How Can Banks Build Better Data Strategies?
It’s one thing to know what a great strategy looks like; it’s another to put these strategies into practice at scale.
For example, a large financial institution might recognize the value of capturing and curating client data to both boost user satisfaction with its services and increase C-suite decision-making confidence. But recognition doesn’t automatically lead to action, especially if financial firms already struggle to find talent, manage their data and ensure regulatory compliance.
To bridge the gap, banks are best served by expert assistance. In the same way that they rely on expertise in their field to provide investment advice or financial services tailored to their clientele, banks can partner with full-service technology and consulting firms to help them create strategies that align with their current goals and set the stage for future growth.
Bringing in expert help — such as CDW’s banking services — can set banks on a path to achieve their specific goals. For example, a small local bank may require help in setting up and managing financial cloud services while a larger, enterprise-level financial services firm may need strategic insights to help them monitor and integrate multiple clouds.
Regardless of a bank’s size, data can yield big benefits — if the bank can create and implement in-depth strategies to monitor, manage and apply its data at scale.
This article is part of BizTech's EquITy blog series. Please join the discussion on Twitter by using the #FinanceTech hashtag.