Demo: IBM Big Data and Analytics at work in Banking

Demo: IBM Big Data and Analytics at work in Banking

banks face many challenges as they
strive to return to pre-2008 profit margins these challenges include reduced
interest rates instability in financial markets tighter
regulations and lower performing assets. Fortunately banks taking advantage of big data and
analytics can generate new revenue streams with personalized offers targeted cross-sell and improved
customer service big data and analytics provide more
insight by analyzing a higher volume and variety
of data types more sources than ever before. Deeper
insight by digging deeper into customer information and behavior enabling segment of one marketing and
faster in sight by performing real time analysis of
customer information to deliver offers at the point of
decision. Big data and analytics can analyze many types of customer information
including: spending patterns behavior, channel usage, product portfolio bank interactions, credit information,
social media and customer profitability. Here’s a day
in the life customer scenario as an example of big data and analytics in action. Peter is a customer of leading bank with a mortgage, checking and savings
accounts and a line of credit peter is remodeling his kitchen and
decides to buy a new set of chef knives the bank recognizes that peter has made
a number of household purchases lately and analyzes his financial and
transactional data including spending patterns, income, savings balance available credit, loans, credit score and
level of risk the bank also analyzes his related
activity on social media and learns that Peter loves to cook
enjoys gourmet restaurants he blogs about his dining experiences
and indicates he likes a new restaurant style gas stove. Using big data capabilities and
predictive analytics the bank anticipates similar home
purchases knows that peter is nearing his credit limit. The bank wants to seize
this business opportunity before peter is offered a credit card from a retailer the bank sends Peter an offer to extend
his line of credit He uses the additional credit to buy the
professional style stole for his kitchen the banking system also identifies this
is a large purchase and props Peter to take and archival
photo of the receipt and warranty as well the system recognizes this is a
home appliance purchase and offers an extended warranty to Peter
based upon his zip code. it’s now 11:30 a.m. analyzing Peters
regular lunchtime purchase behavior and preferences the bank sends him a personalize offer
from one of Leading banks nearby merchants Chefwich. The system prompts Peter share
the offer with his friends through social media as Peter pays his bill bank sends an
alert to verify that he is authorized the purchase is made today preventing fraudulent charges to his
account. Later Peter logs into his account with his
tablet computer. He looks in my offers to find his personalized offers. After
analysis of his spending patterns The bank suggests that Peter sign up for
their Smart Sweep service. Peter also sees a home equity line of
credit offer based on an analysis of his financial
condition as well as information on his home from third party sources. Finally the bank recommends that Peter
sign up for Overdraft Protection to avoid the frustration of any future
fees. While peter is logged into his account he also views the spending manager
feature to gain insight into how his spending changes from month to month. Peter
can compare his spending to financial peers in his geographic location income an age
bracket. With new capabilities provided by big data and analytics banks can develop new products and
services that help customers manage their finances and save them money; deliver relevant
services and offers that fit seamlessly with customers daily lives improve the customer experience and
promote customer satisfaction and retention and at the same time generate new
streams of revenue for the bank

15 thoughts on “Demo: IBM Big Data and Analytics at work in Banking

  1. This is hot is many areas right now.  I hear about big data analytics being used by online retailers as well in an effort to maximize their profitability while meeting the dynamic needs of consumers.

  2. Hey everyone, interesting video! can someone tell me how to perform a presentation like this? where find graphics used in there ? 

  3. Those bank scenarios will not work on me. I never hunt for discounts, I almost always turned down offerings from my cellphone. I love knowledge and technology but not this one.

  4. Are you looking for #BigData Analytics Case Study? Contact us to receive the Case Study @

  5. Digital transformations requires banks to be more nimble, predictive analytics finds a way to make it happen

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