This post highlights the various value-additions that machine learning can provide to actuaries in their analytical work for insurance companies. As such, a key problem of swapping specific risk for systematic risk in general insurance ratemaking is highlighted along with key solutions and applications of machine learning algorithms to various insurance analytical problems.
‘In pricing, are we swapping specific risk for systematic risk?’
Added by Syed Danish Ali on June 20, 2016 at 1:30am — No Comments
Up till recent past, the artificial intelligence portion of data science was looked upon cautiously due to its history of booms and flops. In the latest stream of events, major improvements have taken place in this field and now deep learning, the new leading front for Artificial Intelligence, presents promising prospect for overcoming problems of big data. Deep learning is a method of machine learning that undertakes calculations in a layered fashion starting from high…Continue
Added by Syed Danish Ali on June 20, 2016 at 1:15am — No Comments
Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time. Big data "size" is a constantly moving target, as of 2012 ranging from a few dozen…Continue
Added by m.kiransingh on June 20, 2016 at 1:00am — No Comments
In 2000, Seisint Inc. (now LexisNexis Group) developed a C++-based distributed file-sharing framework for data storage and query. The system stores and distributes structured, semi-structured, and unstructured data across multiple servers. Users can build…Continue
Added by m.kiransingh on June 20, 2016 at 1:00am — No Comments
In this case study for Complexity Science, we aim to show its value addition through agent based modeling of an important insurance problem, i. e, underwriting cycle. Underwriting in Property-Casualty/General Insurance is where insurance underwriting follows and mimics the Economy and its cycles of boom and busts. These soft and hard market swings are a key source of challenge and volatility to insurers. The main value addition of…Continue
It is quite difficult at first to precisely define ‘Complexity Science’. It is a new perspective of methodology and modeling approaches that are based more on reality than assumptions. Quite simply put, Complexity Science is a new way to grasp and manage reality. It does not study systems in isolation like gambling dice or planetary motion only. It studies the complex, holistic, inter-connected reality in which we actually live such as financial stock…Continue
Topology is the mathematical study of the properties that are preserved through deformations, twistings, and stretchings of objects. Tearing, however, is not allowed. Topology can be used to abstract the inherent connectivity of objects while ignoring their detailed form. Put simply, Topology is a mathematical discipline that studies shape and assumes that shape has meaning. This post discusses topology’s applications in finance and insurance. While…Continue
This is a quick, short and concise tutorial on how to impute missing data. Previously, we have published an extensive tutorial on imputing missing values with MICE package. Current tutorial aim to be simple and user friendly for those who just starting using R.
I have created a simulated dataset, which you can load on your R environment by using the…
Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week.
Added by Vincent Granville on June 18, 2016 at 9:30am — No Comments
Canada will soon be passing legislation to allow for physician-assisted suicide. Sometime over the course of debate between our Parliament and Senate, I found what at the time seemed like a peculiar pattern of woodchips in the back of my pick-up. It was such an interesting image, I thought I would share it here. On closer inspection, I discovered that in fact I was looking at hundreds of tiny flower shafts and seeds.…Continue
Added by Don Philip Faithful on June 18, 2016 at 8:30am — No Comments
Source for picture: click here
This blog about series of videos was created by Kevin Markham. Kevin is a data science educator and the founder of Data School. He specializes in Python and machine learning. He has hundreds of hours of experience as a data science classroom instructor, and thousands of hours of experience developing high-quality data science educational materials.…Continue
Added by Emmanuelle Rieuf on June 17, 2016 at 2:30pm — No Comments
This blog about machine learning was written by Emily Barry. Emily is a Data Scientist in San Francisco, California. She really loves emoji. Another thing she loves is data science. The more she learns about machine learning algorithms, the more challenging it is to keep these subjects organized in her brain to recall at a later time. So, she decided to marry these two loves in as productive a fashion…Continue
Financial institutions are under tremendous pressure to comply with regulatory and securities laws. Traditional methods of compliance relied on hand-coded rules that provided detailed control, but introduced human bias and yielded false negative results. Ensuring compliance is complicated by diverse channels such as email, chat, instant messaging, social media, and a…Continue
Added by Amy Krishnamohan on June 17, 2016 at 8:50am — No Comments
2014 was a watershed moment in Indian politics for a variety of reasons. The foremost one was the stupendous victory of the Narendra Modi led NDA in the 2014 Lok Sabha elections. Modi managed to win 282 seats for his party in the elections, the first time in 30 years that a political party had come to power with absolute majority.
Several reasons have been attributed to this victory. Political analysts have spent hours in TV newsroom debates discussing the reasons for this victory.…Continue
Added by Tanmay Bhandari on June 16, 2016 at 9:00pm — No Comments
Contributed by Zi Jin. She is currently in the NYC Data Science Academy 12 week full time Data Science Bootcamp program taking place between April 11th to July 1st, 2016. This post is based on her first class project - (due on the 2th week of the program).
Hedge fund is an important…Continue
Added by NYC Data Science Academy on June 16, 2016 at 11:30am — No Comments
Added by NYC Data Science Academy on June 16, 2016 at 11:09am — No Comments
Your Step-By-Step Guide To Learning R Programming.
Do you want to learn R Programming?
Do you get overwhelmed by complicated lingo and want a guide that is easy to follow, detailed and written to make the process enjoyable?
If so, “R: Easy R Programming for Beginners - Your…Continue
Added by Emmanuelle Rieuf on June 16, 2016 at 10:30am — No Comments
Introducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you'll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science.
About the Technology
Many companies need developers with data science skills to work on projects ranging from social media marketing to machine learning. Discovering…Continue
Added by Emmanuelle Rieuf on June 16, 2016 at 10:00am — No Comments