Solving the Challenges of Big Data in Finance with an Adaptive Analytics Fabric

Adaptive Analytics Fabric

introBanking isn’t exactly a sexy industry. Thus, customer ‘delight’ seems to be something that would be completely out of their element—customers aren’t excitedly lining up to go to the bank like they do at the store the morning of an iPhone release. So it comes as no surprise that Forrester’s 2018 Banking Customer Experience Index found that banks don’t stack up with other industries in making customers feel respected.

Yet, Accenture’s 2018 North America Banking Operations Survey found that three-quarters (74%) of bank operations leaders’ top strategic priority is improving CX, and making customers feel valued. But financial institutions are faced with the reality of siloed data across a legacy infrastructure, costing them the opportunity to truly understand their customers and personalize the customer experience.

Big Data in Finance: The challenges of siloes, compliance, and costs 

Migrating to the cloud would solve siloed data woes, but cloud migration presents specific challenges for financial institutions. Beyond the overall complexity involved, concerns regarding data privacy and security (important for compliance laws such as GDPR), impact to business continuity, a perceived lack of control, and costs are holding back the industry from making the move. 

Additionally, many organizations have legacy systems that can’t be moved, but contain data that needs to be integrated with other data, and thus, take a hybrid cloud approach versus an all-out plunge into the cloud.

An Adaptive Analytics Fabric brings it all together

By introducing intelligent data virtualization through an adaptive analytics fabric, financial institutions can easily integrate data, in all formats, no matter where it is located, and bring it together in one view connected to all enterprise applications and analysis tools. This shared data intellect brings all organizational departments together to have a unified and consistent view of the data for making customer-centric decisions, making these institutions more competitive in the following areas:

  1. Customer Service and Customer Experience
  2. Risk and Compliance
  3. Profitability

Customer Service and Customer Experience

When your financial industry employees are empowered with one 360-degree view into a customer’s account history, at the point of contact, they can truly understand what customers want and tailor the right products, personalized pricing, and services to them.

For example, with intelligent data virtualization, data regarding customers’ social media activity can be integrated with the company’s own customer profile data, allowing financial institutions to more accurately gauge a fuller picture of a customer, and their sentiment toward your organization.

Risk and Compliance 

Financial institutions have many separate areas of risk, such as credit, market, and Basel III compliance. With data virtualization, all of the data from these areas can be seamlessly turned into a unified view of risk across the entire organization. 

Additionally, when all data is consolidated and readily available for analysis, patterns and suspicious activity that previously might have gone undetected can now be seen. Superior audit and compliance reports can also better detail which individuals in the organization have access to specific data, and look out for activity against company policy.


By combining internal data and external information via intelligent data virtualization, financial institutions have more timely financial intelligence to make better, more informed decisions, and more accurately detect market trends.

Additionally, each department’s siloed holdings and liabilities can be combined into a simplified and unified view, which can be monitored and analyzed for developments and potential risks. 

Bridging the CX gap

Data virtualization will significantly increase finance institutions’ customer service and experience capabilities while making them more agile, more competitive and more profitable, without increased security or compliance risks. In other words, banks actually can be sexy to their customers by delivering a personalized experience and the services they need.

For more information on how data virtualization can bridge the CX gap and empower financial institutions to meet customer needs, see the full paper here.

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