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The future of smart banking

22 January 2014  |  1981 views  |  2

A recent article written on the Wall Street Journal indicated that banks, such as Barclays, are investing efforts into data and analytics in order to boost customer service satisfaction. Much like retailers, banks want to offer bespoke recommendations by surfing against the data tsunami and using analytics to their advantage.  By offering customers smart suggestions, they can help them meet their financial objectives and use information like the individual’s salary, spending behaviour and other activity happening in their account to make recommendations. But data’s growth is expanding rapidly and many financial organisations don’t have a grasp on the data they have already. So is it really possible to sail through the data storm that lies ahead?

Many would argue that the idea of banks taking this approach is well overdue. But the financial sector hasn’t had it easy over the last few years. The credit crunch, repeated software errors and poor reputation has led leaders to focus on reacting to crises as opposed to being innovative. Whilst I’m all for a change in direction towards smart data, the kind of analytics that enable it make robust demands on the condition of the data estate: it must be possible to achieve consolidated, joined up views for the analytics to operate on.

The current reality is that the data is fragmented, spread across historically accrued siloes, plagued by vocabulary mismatches and comes in a myriad of different varieties, even within a single institution. The way this is currently handled is data integration, but research shows that traditional data integration projects are failing organisations.

Last year 65% of IT managers admitted that they never expect to see any ROI from data integration projects – despite 25% of their overall IT budget supporting them. The issue is that many IT managers are stuck on an integration treadmill, using traditional options that not only take colossal amounts of time to seek through the vast volumes, velocity and variety of data, but don’t wind up achieving anything at the end of it. A far better alternative is to use semantic search. It allows IT managers to find, examine and link data across the entire business – instead of mindlessly going round in circles trying to source the specific information they need.

If the financial sector wants to become more innovative for its customers in 2014, it must start to use more innovative tools to be successful. Semantic search is key to breaking the shackles that weigh organisations’ data down and instead, enables them and their customers to become smarter with their data.


TagsMobile & onlineInnovation

Comments: (2)

Ketharaman Swaminathan
Ketharaman Swaminathan - GTM360 Marketing Solutions - Pune | 23 January, 2014, 15:45

Let me guess: Author's company Ontology is into Semantic Search.

Check out website: Ontology applies the power, simplicity and speed of semantic search to gain insight ... 

Verdict: Guess seems right. 

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Alex Johnson
Alex Johnson - Zoot Enterprises - Bozeman | 28 January, 2014, 22:29


That 65% statistic is just brutal. I can absolutely picture an IT manager sitting in his office pounding his fists into his computer over and over.

I think semantic search is definitely an interesting way to circumvent the problem. Another approach that we see our clients use frequently is what we are calling “actionable data”. Instead of trying to boil an entire ocean of data, these institutions are biting off a smaller data set and using it to drive actionable insights for their customers. It’s not as sexy as Big Data and it needs to be done carefully, but it can drive extremely predictive analytics.

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