Data science news

Health in­surers work­ing on data ana­lyt­ic skills for bet­ter pri­cing

Stronger data bank and data ana­lyt­ic skills will help health in­sur­ance com­pan­ies in bet­ter un­der­writ­ing of in­sur­ance policies, which in­cludes un­der­stand­ing risk pro­files and pro­duct pri­cing. Strong data bank will also en­sure bring­ing down fraud in the sys­tem. Health in­sur­ance com­pan­ies are work­ing to­geth­er to strengthen data ana­lyt­ic cap­ab­il­it­ies, said a FICCI re­port.

“From col­lect­ing in­tern­al data in­de­pend­ently, in­surers are now slowly mov­ing to­wards data shar­ing on a col­lab­or­at­ive basis. However, with the in­crease in the num­ber of com­pet­it­ors, there is a need for in­surers to think out of the box and make a gradu­al shift to­wards more ad­vanced tech­niques in data ana­lyt­ics that can help take the Indian in­sur­ance busi­ness prof­it­ably in­to the fu­ture,” said FICCI.

The Effect of Predictive Analytics on the Homeowners’ Industry

Insurance ex­ec­ut­ives are still grap­pling with an all-too-slowly re­cov­er­ing eco­nomy, de­clin­ing re­turns on equity and in­creas­ing pres­sure to turn a profit any way they can and car­ri­ers of­fer­ing Homeowners’ cov­er­age face ad­ded volat­il­ity in light of re­cent cata­stroph­ic weather events like Superstorm Sandy.

In or­der to bring some bal­ance to this equa­tion, there is a grow­ing need to bet­ter un­der­stand and man­age risk in Homeowners’ in­sur­ance.

The num­bers tell the story: According to A.M. Best and the Insurance Information Institute, Homeowners’ com­bined ra­tio swung from a high of 158.4 per­cent in 1992 to a low of 88.9 per­cent in 2006. The av­er­age com­bined ra­tio for Homeowners’ car­ri­ers from 2008-2011 is 113 per­cent, com­pared to 102 per­cent across all oth­er P&C lines.


Firms have taken to big data. Here are Mike Gualtieri’s four pre­dic­tions for key en­ter­prise big data themes in 2013:

  • Firms will real­ize that “big data” means all of their data.
  • The al­gorithm wars will be­gin.
  • Real-time ar­chi­tec­tures will swing to prom­in­ence.
  • Naysayers will fall si­lent.

India aims for world’s big data

Growing de­mand for big data skills will see com­pan­ies look­ing to out­sourcing to plug the gap, present­ing op­por­tun­it­ies for India. But, it must first ad­dress sev­er­al fun­da­ment­al chal­lenges.

In its re­port “Big data: The next big thing”, Indian IT ser­vices in­dustry group Nasscom ex­pects the country’s big data in­dustry to grow from US$200 mil­lion in 2012 to US$1 bil­lion in 2015. The biggest chal­lenge and op­por­tun­ity is to sat­is­fy the de­mand for data sci­ent­ists. Avendus Capital, for one, es­tim­ates the United States will suf­fer a short­age of up to 200,000 data sci­ent­ists by 2018, a gap that will most likely be filled by out­sourcing.

Healthcare IT: The 4 Pillars Of Technical Innovation

Four ma­jor tech­no­logy trends, which are be­com­ing more in­ter­twined every day, will dom­in­ate the health­care IT land­scape in 2013, ac­cord­ing to IDC Health Insights’ top re­search­er, Scott Lundstrom.

These trends so­cial me­dia, cloud, big data and ana­lyt­ics, and mo­bil­ity already are hav­ing a big im­pact on many health­care pro­vider and pay­er or­gan­iz­a­tions, but CIOs will be faced with man­aging and de­ploy­ing many of these tech­no­lo­gies as their use be­comes per­vas­ive dur­ing the com­ing year. Lundstrom calls these tech trends the “four pil­lars” of health­care IT and re­cently presen­ted them dur­ing a key­note present­a­tion at UBM Technology’sHealthcare IT Summit.

“By us­ing tech­no­logy we can go out and make a dif­fer­ence in the qual­ity and cost of care,” Lundstrom told the CIOs gathered at the con­fer­ence. “The an­swer to do­ing more with less in health­care is get­ting closer to the pa­tient with cloud, ana­lyt­ics, mo­bile, and social/unified com­mu­nic­a­tions.”

Big Data Analytics: Not Just for Big Business Anymore

So much data and so little busi­ness in­tel­li­gence. That’s the irony of the in­form­a­tion age, which is adding an­other 2.5 quin­til­lion bytes to the data uni­verse each day. Companies can either get bur­ied by this ava­lanche of big data or use tech­no­logy tools to mine its riches. This abil­ity to ac­cess and ana­lyze end­less sources and types of struc­tured and un­struc­tured data such as so­cial me­dia chat­ter, com­mer­cial trans­ac­tions, fin­an­cial mar­ket data, GPS trails, ge­n­om­ics is re­vo­lu­tion­iz­ing mar­ket­ing and trans­form­ing en­tire in­dus­tries.

Because of its scope, big data has largely been the province of big busi­nesses with big data cen­ters. Large cor­por­a­tions have in­ves­ted armies of data spe­cial­ists and fant­ast­ic sums of money in big data. Those that har­ness big data can make highly data-driven busi­ness de­cisions, and re­spond and ad­apt to chan­ging mar­ket con­di­tions more quickly than their com­pet­it­ors. Marketing de­part­ments and ad agen­cies use big data to tar­get cus­tom­ers with in­creas­ing gran­u­lar­ity and ac­cur­acy.

Predictive ana­lyt­ics for per­form­ance man­age­ment, the time is now

A long list of sup­pli­ers are flog­ging the con­cept of pre­dict­ive ana­lyt­ics, that is the use of ma­chine in­tel­li­gence to sift through the massive, ever grow­ing amount of log data op­er­a­tion­al sys­tems gen­er­ate, to pre­dict prob­lems be­fore they oc­cur so they can be re­solved be­fore the IT house of cards falls down. Is this a tool or­gan­iz­a­tions can rely on or just the most re­cent catch phrase.

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