Big Data in Financial Services

Consumers of financial services have more options and are less tolerant of poor customer service. They expect self-service options and social media engagement. They reward personalized and responsive service. And they are increasingly switching from financial service institutions (FSIs) who fail to deliver. For many FSIs, satisfying more empowered customers requires a shift in financial services strategy.

In a research report titled Breakthrough Banking, the IBM Institute for Business Value identified that most banks struggle to understand their customers apart from their immediate banking transactions. The report quantified what banking customers want from their banks.

Financial Services Customer Expectations

Contact centers are pivotal points in the effort to retain customers. Equipping contact  and call centers with big data tools and technologies is a proven method to detect early signs of customer churn, escalate at-risk customers for intervention, and increase customer retention.

Call center data has historically been used to aid agent training, staffing and performance reviews. Extending the data and analytics to include unstructured data and social channels can aid improved customer retention and real-time sale opportunity identification.

One method is to apply sentiment analysis to unstructured data types such as IVR, real-time speech, voice recordings, free form customer comments left on self-service applications and other systems of customer engagement.

Using techniques such as text analytics, speech analytics and Natural Language Processing, FSIs can mine and filter large volumes of customer content in order to highlight and escalate those that suggest a problem or opportunity. Workflow automation in the CRM system or call center application can display alerts in real-time to Customer Service Agents or route notifications to the right people.

Identifying scenarios where negative sentiment is closely linked with customer churn permits prioritized actions. For example, negative sentiment calls or correspondence near a renewal date could prompt intervention before losing the renewal and the customer. Customer sentiment combined with transaction history can also detect potential financial services compliance risks.

Streaming sentiment analysis can be used to interpret relevant product sale opportunities and deliver real-time suggestions to the call center agent or financial advisor based on the customer’s words and existing product portfolio.

This concept can add even more specificity if the client profile record is integrated with their social profile and website browsing history (i.e., their digital footprints).

This blending of unstructured and structured data combines to deliver personalized and highly relevant up-sell and cross-sell recommendations. Technology investments are normally required to achieve this level of sophistication, but the effort can effectively convert the call center from a cost center to a profit center.

It can also provide a tremendous payback as measured in incremental revenues from cross-sell and up-sell, and increased referrals from more satisfied customers. Even better, it's proven to increase customer lifetime value lower customer churn.

Shifting Market Forces Require Business Transformation

The financial services industry is in transition. Markets are converging, new FinTech competitors are emerging, boundaries are disappearing and customers are reassessing their needs for banks, insurance companies and capital market companies.

For example, Viacom's "Millennial Disruption Index" identifies banking as the industry most vulnerable to disruption by Millennials. One third of this generational cohort say they won't even need a bank in five years.

As customers become more emboldened, competitors more innovative and margins harder to come by, customer insights and business intelligence deliver an information advantage that helps capitalize on market movements.

Data is the source for competitive advantage in shifting markets. Analytics unearth data to provide the insights which create more customer value, deliver unique value to different customers and make better business decisions.

According to a report by Microsoft and Celent, titled How Big is Big Data, 60 percent of financial institution executives believe that more and better data analytics offer a significant competitive advantage and 90 percent say that successful big data initiatives will define the industry winners.

More types of data, better analytics and financial services CRM business intelligence offer unique opportunities for FSIs to better understand customers, products, markets, competitors and themselves. A complete view of the business enhances every part of the business and enables financial service companies to react to market threats, identify new market opportunities and act swiftly.

Every FSI is going to adopt Big Data sooner or later. The question that looms is will they adopt while they can leverage the technology to get ahead of their competitors and grow customer share, market share, revenues and profits; or will they delay, take a wait and see attitude, permit more forward looking competitors to take some of their business and then eventually embrace the technology once it becomes table stakes?