Showing posts with label Social Media. Show all posts
Showing posts with label Social Media. Show all posts

Saturday, February 18, 2012

Social Media Intelligence – A Disaster?


Just read this piece on Bloomberg about how retailers are shutting down their Facebook shops.  I have written in the past about how many companies are using social media to glean actionable intelligence about customers. Very specifically I had discussed how social media has the potential to provide risk intelligence to credit risk managers in banks and financial institutions. While there was flicker of interest, it has not actually picked up for several reasons.

For starters, social media sites like Face book are more an online venting of personal idiosyncrasies and little nonsense we all like to indulge ourselves when our guards are down. Personally I think it is more akin to street corner gathering of teenagers who hangout more for social companionship rather than any serious discussion. Of course, there are serious discussions at these hangouts, but they are heavily outnumbered by the day-to-day sharing of simple trivialities. That is the nature of Facebook transactions.

The most obvious reason seems to be the inability of many leading companies / brands to monetize their huge followings or “likes” on Face book. Many companies opened Facebook stores because they did not want to lose out. However, these initiatives have not provided the expected return on investments and many leading brands -  JC Penny, Gamestop, Gap, Nordstrom, just to name a few – have shut down their Facebook stores. See article for more details.

Banks and financial services, on the other hand, have been more cautious in their social media strategy. Credit Risk Managers were not blown off their feet by Facebook’s ability to provide risk intelligence. While collection agencies are using Facebook to locate delinquent customers, it is a far cry from replacing Credit bureaus as a primary source of customer data. I think we have to wait and see how this evolves in the coming months.

Current social media strategy has hurt companies in other ways too. Many companies that bet on Facebook and have invested heavily are already seeing negative returns. Poor revenue streams from these strategic decisions will show up in the balance sheets of many software companies as early as 1Q of 2012. It will be interesting to see how the markets respond to the poor results.

I am not prognosticating a complete failure of social media strategy. Rather, it is a time for introspection and realignment for future course of action, given what we are learning. As always, I believe failure is a great educator and leads to innovation; innovation is the key distinguisher in a competitive business environment. I believe when the dust settles, it will lead companies to engender a more compatible and sustainable social media strategy.  Definitely, the current social media strategy a.k.a “Facebook Strategy” of many companies does not seem to be working.  Stay tuned folks.

Monday, January 16, 2012

Power of Analytics


I was reading this book “Competing on Analytics –The new science of winning”; It is a must-read for number crunchers and ambitious bankers in particular. The authors (Davenport & Harris) have delightfully brought out how analytics can turn a company into a winner. According to the authors (Davenport & Harris) the following four factors are vital for successful “analytical companies”
Supports a strategic capability
Enterprise wide
Commitment of senior management
Company makes a strategic bet on analytics

Analytics – as any number-cruncher knows – has always played a key role in decision making in banks and financial services. It is not something new. However, more and more companies are leveraging this today to propel themselves into big league.

The obvious example of use of analytics in banks and financial services is in the development of custom scorecards to predict default. The larger banks have dedicated “decision sciences” teams to handle this. While smaller banks buy credit scores from the credit bureaus, the larger banks develop and deploy a  wide array of  score cards that are designed to serve specific business purposes.

But the larger more prevalent deployment of analytics is in performing ad-hoc analytics to find answers to specific business problems. These vary in complexity and the type of problems they are trying to address.
For example credit risk departments in retail banks have used the power of analytics in approving/providing lines of credit to customers.  In making these loan decisions, banks usually compute debt to income ratios, number of other loans, regularity of repayments, any unpaid and past due loans,  membership on rewards databases, loyalty to the bank etc.  to help make prudent credit decisions.

Marketing also is a key user of analytics. An example is how banks monitor existing customers who shop to refinance their mortgage or auto loans. This is helped by “triggers” from credit bureaus. So if you have your home mortgage financed by bank A but would like to shop for better rates, Bank A will get a trigger from the credit bureaus that your credit was pulled by Bank B;  Now Bank A , using analytics can and provide a counter offer to you.

Technology impact on analytics
Analytics is now helped in a big way by new developments in IT and Business Intelligence. The new buzz words in technology - Big Data, Cloud, Social media & Mobility have greatly impacted analytics.  For example new BI tools that leverage the 64-bit architecture can help process huge volumes of data in-memory that has not been possible earlier. This enhances the speed and depth of analytics.  

Mobility adds a key dimension to delivery of analytics. It can now reach top management 24/7. The iPad is rapidly changing board meetings by providing depth and ease to business leaders. New visual analytical tools can help managers perform scenario analysis during meeting and provide useful insights almost instantaneously.

Social media analytics is now emerging as a new discipline by itself. For example bankers are finding out that people with similar credit risk “like” similar friends on Facebook.  While this definitely needs more empirical data to be broadly accepted, it is making significant inroads and will be closely watched in the coming months.
The US economy is slowly emerging from recession.  I think analytics will be a key player in helping Banks to find their way back to profitability.

Wednesday, September 28, 2011

Monday, September 26, 2011

Social Media and Banks


Banks all over the world are slowly waking up to the potential of Social Media in everyday banking. With every passing day, they seem to discover new and ingenious ways of putting it to use.   Here are some of the ways banks are using Social Network Intelligence.

New Accounts: Targeting prospective customers is a challenge faced by marketers.  Now Citi and American Express have used Facebook data to target prospects of a specific age demographic. For example CitiForward and Zync cards have relied on social network intelligence to target young adult prospects.

Rural Expansion: Community Banks in Australia have built a strong customer base in rural Australia using social media to build “virtual communities”. 

Credit Risk: When processing loan applications, check on Facebook friends provides insights into applicant.   A California based company, Rapleaf (Rapleaf.com) claims that its studies have shown that if friends in the network are responsible borrowers, then the applicant is more likely to be a responsible borrower. On the other hand if Facebook friends of an applicant has  quite a few who have foreclosed on their homes, then more than likely the applicant will also default  / foreclose on the mortgage.  In other words,  “like follows like”.  If there is no legal or regulatory hurdle, many banks are likely to adopt this insight from Facebook.

Fraud Detection: Lenders are now matching application data with social media data to detect fraudulent applications.   For example, if the address provided on the loan application does not match Facebook location, then application is subject to further checks.  Secondly, if applicant has large number of “Friends” on Facebook, then the email ID is treated as “safe / reliable” email ID.

The coming months will tell us more about how banks and financial services are using Social Network Intelligence.

Wednesday, June 22, 2011

Enhancing Social Network Intelligence



I was browsing the internet to see how companies have come up with several strategies to make their social media presence felt. I had already written about how social networks are beings used by debt collection companies to track delinquent customers.

My insurance company (auto & home) is pestering me to add it as a friend on Face book – which is really annoying.  There are definitely better, more subtle less annoying ways to befriend the right customer or prospect.  I want to discuss one such methodology.

We can extract useful insights from social media data by combining it with what we already know about the customer from other databases such as credit bureau, rewards and loyalty programs, public records, credit card authorization data, etc.  A smart coupling of any of these databases with social media data enhances quality of social network intelligence (SNI).

Let me walk you through a hypothetical example to elaborate my viewpoint.  Mr John is a Marriott rewards member with a Marriott rewards credit card. He has accumulated significant reward points over the years.  He is active on Facebook where his posts include several dinner outings he has enjoyed with his significant other. Let us examine how we can convert this social media post into actionable intelligence or Social Network Intelligence (SNI).

Data on John’s stay at the Marriott as well as rewards card usage is captured by Marriott and Chase Cards and mutually shared.  When we combine transaction level data i.e. card authorization data with John’s Facebook posts, we have an intelligence multiplier. We can authenticate or validate his favorite cuisines by cross matching social media posts with credit card authorization data with the following information:

a)    how many times in a given period did John eat out
b)    how much did he spend 
c)    the restaurant  and (hence the cuisine) he frequents

Here two important points have to be noted

1)    Social Media posts is tracked for actual willingness and the ability to pay for choice of product  / service – cuisine in our example
2)    By this validation , we have converted a social media posts into social network intelligence -  euphemism for  actionable intelligence

Social networks provide a wealth of information, but often in its raw data. For example John’s posting about his favorite dinner outings viewed in isolation may not be as powerful as when we know if he has actually spent money and how much on his dinners.  When combined with other databases, social media posts enhance its commercial usability.

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