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Capgemini IT: GROWTH ACCELERATOR

IT trends spotted and checked by experts

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What happens

In May 2016 American law firm BakerHostetler announced it was recruiting ROSS, a robot equipped with an artificial intelligence engine, to work with the team specialising in bankruptcy procedures and company restructuring.

so what?

CEO of Sinequa

Alexandre Bilger is CEO of Sinequa. A graduate of both the Polytechnic School and MINES ParisTech, he began his career in 1995 as a software architect with Nat Systems before co-founding the software editing...

Cognitive computing aims to reproduce the way the human brain functions, notably by bringing together automated learning and language processing. The goal is to give meaning to mass data and to facilitate decision-making.

Why should we be interested in cognitive computing? 

It is all about extracting knowledge from mass data, given that the latter can now be processed thanks to big data analysis tools. Businesses accumulate vast amounts of internal and external information - information that humans are simply not capable of analysing. Cognitive computing aims to gain "insights" from this data by putting it into context. Notably, it relies on self-learning technology (machine learning), graph analysis and language processing. 
The algorithms the technology uses are not new, but they have benefited from the exponential growth in processing power (as established by Moore's law). With cognitive computing, the days of binary-style "yes or no" answers are long gone. It does not predict one particular result, but many, along with correlations. For example: "there is an X% probability that the client will terminate their contract". 


This type of IT involves self-learning, and the pertinence of the results depends on the quality of the examples provided. This requires preliminary work in terms of linguistic and semantic development, in order to turn raw data into data that is workable and adapted to the sector in question.   

How can this technology been used? 

 In many different ways: in the customer relations domain, cognitive computing can reduce the churn rate by detecting weak indicators obtained from CRM data or call centre interactions. 

And by identifying abnormal patterns in financial transactions, it can help fight money laundering and the financing of terrorism. 

The technology can also help a law firm find the best lawyer to defend a client in a given case, based on their previous case defence history. 

Via social networks, a pharmaceutical laboratory can use AI to monitor how happy clients are with a newly released drug: have comments been positive, negative or neutral? Does the information come from patients, associations, doctors or advocates of the drug? This type of analysis can also shed light on possible secondary effects which were not identified during clinical trials, allowing for measures to be taken quickly.  

Does cognitive computing replace humans?

No, because there is an important parallel relationship between man and machine. By analysing data from disparate sources in order to identify links, cognitive computing helps with human decision-making. This is also true the other way round. For example, Deep Blue, IBM's chess computer, won a game against a grand master but lost against a "mixed" team in which humans worked in tandem with a computer. Google translate calls upon internet users to help improve the quality of its translations. How do you translate "change agent" into French, for example? The automated translation will give the result "agent de change". However, depending on the context, a human might suggest "agent de changement", which may be more appropriate. 

In a work context, an intelligent system could provide an employee with tasks to complete during the day by supplying the latter with the contextualised data they need. This would reduce the large number of data that the employee would have to sift through in order to complete the same objective. 
  

Who cares?

- Cognitive computing is used in numerous artificial intelligence applications, notably expert systems, natural language programming and neuronal and robotic networks. According to the International Data Corporation, by 2020, 50% of all data analysis tools will use predictive modelling technology based on cognitive functions. 

- Numerous sectors are concerned. IBM's "Watson" super-computer helps doctors carry out diagnoses as well as helping sales people to understand their markets.

- In France, the Crédit Mutuel CIC bank wants to use such technology to help employees deal with customer emails. In the UK, clothing company Macy's is experimenting with an intelligent mobile app which answers client questions based on the specific store they are in, to help them find the best-suited locally available products.
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Innovators Race

As Capgemini turns 50, we give early stage start-ups the opportunity to jump-start their business and win equity-free funding of $50,000.

For more information: www.innovatorsrace50.com

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