How Big Data Can Enable Better Banking Experience
The whole concept of Big Data has generated a lot of hype in the market, and slowly as the noise settles, banks have started asking the big data gurus in the market to answer one simple question – How do we make it work?
The answer is not very simple, but let me try to address it using the diagram below:
The figure tries to show how a bank should approach the various “additional” sources of data, which would constitute the big data ecosystem.
First and foremost, the banks have to realize that big data analytics is not synonymous with “Social Media Analytics”. Items in the ’start’quadrant are available todaywith almost all banks. These data sources if sourced well and then analyzed by new age big data analytics tools will reveal a lot of insights, which will sure enough pave the way for other tougher data analytics. Some use cases, which can be unlocked by looking at this easily sourceabledata are:
- Marketing for cross-sell, up-sell: Understand customer purchase behaviors and make targeted offers
- Churn analysis: Understand patterns and changes of customer behavior and predict their churn
- Fraud – online, retail, corporate: Understand fraud patterns which go undetected
- Voice of the Customer: Understand what customers are speaking about the products and services of the bank accordingly
- Customer wealth estimation using notes data, payee etc.
- Debt estimation using bill pay data, taxes, standing instructions info etc.
- Better credit scoring by combining “quantitative” and “qualitative” parameters
Once a bank can establish ROI using the above use cases they should look at substantiating that by ’sourcing’additional data, which is high on verifiability and relatively easy to procure. This is where they might look at content aggregation from mobile operators and utility firms to further strengthen the “quantitative” profiling of the customer. Case in point is Safaricom, Kenya’s largest mobile operator,which studies how often its customers top up their airtime, how regularly they use the voice service, and how frequently they use the mobile money function. Once their trustworthiness has been established, Safaricom would gladly lend them money.
Once the maturity level of applying big data analytical methodologies to the above data types is established, the banks should start ’observing’the data sources, which are low on verifiability and are relatively complicated to source. But, by tackling this type of data later, gives the bank enough headroom to increase the insights generated for its customer once the benefits of big data analytics is well established. This is due to the fact that such data usually requires a lot of heuristic approaches and iterations to cull out any substantial and meaningful insight.
I would also recommend banks to steer clear of data which is easilysourceable but difficult to associate with their customers.
So once the correct data sources are established, the ROI has started kicking in, the endeavor of the bank should be to use these additional insights to enhance the overall customer experience. This would involve:
Service/product personalization: Tailor the look and feel of all the channels and communication as per the customer’s preferences. All his products should be tailored to his needs and the bank should become a trusted advisor
Website optimization: Optimize content on the website based on the top things the customer is interested in as told by him and as deduced by the bank
Voice of the customer: Listen to and analyze everything that your key customers are saying about you on all platforms and make it a mission to give them what they want as far as it makes business sense. Protect your customer base from churn with timely goodies, freebies and gifts to enrich the customer experience and value
Once the above elements fall in place, banks will realize the true potential of analyzing ‘all’ their data generated inside as well as outside the organization. The true litmus test would be additional smiles on their customer’s faces when they see the bank truly understands them and is willing to do the best it can to pump up their experience around a critical activity they engage in – Banking.
- CXOs Still Wary Of Cloud Data Security: Study
- PNB Scam: Some Tech Lessons For Indian Banks
- Embracing Technology For HR Innovation
- IBM Steps Up Its Skills Development Efforts In India
- Weekly Rewind: Top 10 Stories On CXOToday (Feb 5-9)
- AI, Machine Learning Are Top CIO Priorities: Experts
- What's The Future of Digital Payment Industry?
- Top CRM Features To Ensure Data Security
- City Union Bank India's First Banking Robot
- Cloud Computing Powering India’s Digital Economy