How Banks Are Missing the Mark With Data Management
The banking and financial services sector has been on the front line of digital transformation— and as a result, banks have an incredible amount of customer data and transactional data on-hand. Many banks have put that data to good use and readily embraced data-driven applications to keep up with consumer demand.
Still, many banks are completely missing the mark when it comes to how they’re managing that data.
A 2019 study from Accenture found that 50% of consumers want their banks to blend physical branches and digital services, and 86% of consumers trust their main bank to look after their data. Consumers expect good data management from their banking service providers.
The high volume of data, the constant threat of fraud and cyberattack, and heavy regulation make data management incredibly challenging for banks—but it’s critical that they put it at the forefront of their digital transformation strategy.
So where are banks going wrong, and how can they course correct?
Outdated Legacy Systems Make It Difficult to Handle Large Data Volumes Efficiently
Many banking organizations are still running on legacy systems that make it challenging to handle the increasing volume of data. These legacy systems prevent applications from accessing records and transaction data quickly enough to satisfy customer requirements. And these legacy systems also prevent the banking organization from accessing the insights they need to make data-driven decisions quickly.
A McKinsey survey found that one of the most common obstacles holding back financial institutions is inefficient data architecture with multiple legacy IT systems. Banks can experience cost savings of 30 to 40% by simply reducing the time it takes to respond to data requests from the supervisor. And those that simplify their data architecture, minimize data fragmentation, and decommission redundant systems can reduce IT costs by 20 to 30%.
Increasing Competition Makes Gaps in the Customer Journey More Obvious
The customer journey is increasingly digital, with frictionless, on-demand banking top-of-mind for many consumers when it comes to choosing their banking service provider. Customers are now able to manage their finances more easily, they have more access to loan applications and approval, and they expect loyalty rewards programs to pay off.
Banks that are too slow to reach customers at the new stops along the Right-Now Customer journey will succumb to competitors who can react faster and with a more targeted, personal response.
Accenture’s 2019 study found that 57% of consumers want alerts when they are close to overdrawing, and 49% want savings tips based on spending patterns. This requires rapid-fire response on the part of banks, which in turn requires instant access to data—and better data management all around.
Regulatory changes now allow user-provided data to be used for API integrations, and Fintechs are facing off with banks over who will use this data to help customers first. And customers are on-board with this process. That same Accenture study found that:
- 78% of consumers will share data for greater efficiency
- 83% will share data for more savings
- 72% will share data for personalized offers based on their current location
As banks use the data they collect about their customers to offer them more value, customers more willingly trust banks with their personal information.
Banks must do a better job with data management to provide an optimized and consistent customer experience at every step in the journey. To achieve this, an enterprise data layer is a key piece of the digital transformation puzzle
Customers Demand Instant, Secure Access—but Data Siloes Prevent That Agility
The changing face of the customer journey, and greater customer experience demands, come with the expectation that banking information is available instantly and securely.
Cloud applications have given banks the ability to provide personalized experiences, answer customer questions, and give customers access to their finances 24/7. But when response time is slow or security is compromised, consumers are quick to turn to competitors.
Siloed data is a huge contributor to this problem. When data is housed in multiple silos, more surface area is exposed to hackers, and security and compliance overall are more at risk. Experian reports that in 2018 there were 1,579 data breaches exposing nearly 179 million records—a 44% increase in breaches and a 389% increase in records exposed.
Data silos also affect application responsiveness, leaving bank customers using clunky solutions and eyeing competitors’ sleek alternatives.
However, with data distributed in more than one data center and often in more than one region, silos are inevitable without a data management solution that integrates and unifies that data.
A distributed database management platform can deliver the linear scalability, masterless architecture and end-to-end encryption banks need to provide customers with modern apps. It can also help banks meet regulatory requirements such as the European Union’s General Data Protection Regulation (GDPR).
Relational Databases Can’t Keep Up With Today’s Sophisticated Fraud Rings
For banks, security includes more than compliance, cybersecurity, and protection of customer data. It also includes fraud prevention.
Fraud rings are becoming more sophisticated, and fraud is on the increase. McKinsey estimated banks would lose more than $31 billion globally by 2018. Relational databases are just not equipped to handle modern fraud detection responsibilities. Real-time detection is critical for stopping fraud, and relational databases simply cannot analyze complex relationships in huge data volumes quickly enough.
To prevent fraud, banks must turn to a data management platform with real-time graph capabilities and enterprise-grade security. Nothing less will help them stop fraud before they and their customers are affected.
More so than any other industry, banks are held to the highest standards. Customer trust is hard-won and too easily lost. From handling increasing volumes of data, to meeting customers where they are, to preventing fraud, banks that aren’t using a distributed database platform are missing the mark.