Banks gain value out of big data focusing on the customer experience

Consumers are demanding greater financial flexibility and experiences. 2013 was the first time in the history of banking where the numbers of transactions from on-line banking trumped the number of retail banking transactions by 6:1. The younger generation prefers on-line banking vs. retail banking, and the older generation is adopting technology faster than ever before.

New sources of data are emerging from businesses, public data, phones, cars, social media, location data, health data and iBeacons. 

The older generation is very keen on retail banking and they are also demanding targeted experiences in the branch.

Consumers are becoming increasingly mobile, dynamic and are demanding their financial services organizations be woven into their lives in meaningful ways.

Mobile banking, and mobile payment options are disrupting banking operations and introducing competitive threats. 

Banks are struggling to find new sources of revenue with the above trends, regulations are becoming tighter and many new competitors are emerging providing greater experiences (on-line and mobile) than the classic financial institutions.


Contextual analytics is the key to unlocking innovative profit growth

Banking is on the verge of major transformation.  The new sources of data, competitive pressure, and the rise of on-line banking combined with the transformation of retail experiences and demand for segment of one services will provide the best possible consumer experience. 

Today retail banking employs multi-decade old practices for consumer experiences.  Existing clients of a bank walk up to a teller and the experience of the customers are very simple: balance inquiry, withdrawal, deposit, referral to a lender, move your account to a fee charging account and/or to a certificate of deposit.

The analytics which tellers, branch manager, customer service call center representatives, wealth managers, brokers and analysts have access to are extremely limited resulting in poor consumer experiences and revenue declines.

The consumer on-line experience, although built in the last decade, is purely a transactional experience with little value beyond convenience.

Banks need to focus on solutions that provide retail branch tellers, retail branch managers, banking call centers, and wealth managers with micro (hyper)-contextual segmentation analytics and real time sentiment insights.

These solutions must include, but should not be limited to the following data sources:

  • Social Media Data
    • Facebook
    • Twitter
    • LinkedIn
  • Transaction Data
    • Checking Account
    • Money Market
    • Credit Card
    • Certificate of Deposit
    • Home Mortgage Data
  • Call Center Data
    • Voice transcripts
    • Metadata about call data records
    • Call experience data
    • Phone location data
    • Phone device data
  • On-line Banking Data
    • Tracked cookies
    • Follow the customer with embedded pixels


Focus on developing front line employee solutions

The solutions should include a business intelligence visualization, and exploratory dashboard, and recommend next best action tools. These solutions should be utilized by retail branch managers, retail branch tellers, banking call centers and wealth managers, not just be built for analysts or data scientists.

To effectively create such dynamic access to data, and enable it to learn ongoing these solutions must support, but not be limited to, natural language processing as one of many inputs.

Intelligent digital agents (AI) should also be deployed that can simulate massive amounts of models simultaneously.  These agents will validate semantically both structured, unstructured and perpetually connected consumer data by the feedback provided from a front line employee.

The insights should be presented in a digestible form providing:

  • Insights on what that consumer values
    • Build rapport and trust first
  • Insights on what that consumers spends money on
    • What’s important to this consumer on a daily basis
  • Insights on the relationships that consumer has
    • Who influences that consumer’s thoughts and decisions
  • Recommendations that triangulate all the insights
    • What motivates that consumer
    • Why do they buy what they buy
    • Why would they need what you have to offer


Demand big data business applications 

The focus on a big data initiative for banks looking to improve the customer experience should be centered on understanding what consumers’ value, and orienting products, services, and segmentation around those values.

Today the consumer is shaped around the data, to effectively achieve a true customer-centric experience the banks need to turn the model upside down, and begin to shape products, offerings, and resource planning around the consumer.

Knowing that 70% of the calls going into a call center comes from customers that love sports, could make it easier to plan hiring, and training beyond the basic product, and service skills. 

People like to do business with people they like.

Banks who focus on understanding, and shaping their business around the consumer and shaping its offerings, and resources accordingly will become more likable. 

More likeable means more business. 

It’s not a complex formula!


Views: 1813

Tags: Analytics, BI, Banking-Big-Data, Banking-Technology, Big-Data, Branding, Branding-Strategies, Branding-Strategy, Business-Intelligence, Business-Planning, More…CIO, CMO, CMO/CIO, Consumer-Marketing, Consumer-Segmentation, Customer-Experience, Data, Data-Science, FinTech, Financial-Services-Big-Data, IT, Market-Research, Micro-Analytics, Micro-Segmentation, Social-Media, Strategic-IT, Strategic-Planning, UI, UX, UX/UI


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Comment by Alex J. Caffarini on January 28, 2014 at 10:29am

As margins on the banking industry's three income streams - interest on loans, returns on invested capital, and fees - continue to shrink, Big Data should be increasingly looked upon for targeting the best fit customers and reducing cost-to-serve. 

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