Advanced Business Analytics for Actuaries

CIA Annual Meeting June 2013Session 12

Kevin Pledgekevinpledge@gmail.com416 949 8920

What does analytics mean to you?

What does analytics mean to you?

Business Intelligence

BI

What does analytics mean to you?

What does analytics mean to you?

or something else?

Business Intelligence

BI

Business Intelligence

Business intelligence (BI) is a set of theories, methodologies,processes, architectures, and technologies that transform raw data into meaningful and useful information for business purposes. BI can handle large amounts of information to help identify and develop new opportunities. Making use of new opportunities and implementing an effective strategy can provide a competitive market advantage and long-term stability.BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics.Though the term business intelligence is sometimes a synonym for competitive intelligence (because they both support decision making), BI uses technologies, processes, and applications to analyze mostly internal, structured data and business processes while competitive intelligence gathers, analyzes and disseminates information with a topical focus on company competitors. If understood broadly, business intelligence can include the subset of competitive intelligence

Business Intelligence

In a nutshell…

structuring your internal datafor reporting

Data Warehouse

Extraction, Transformation and Loading (ETL)

Metadata(data about data) Online Analytical

Processing (OLAP)

Source Systems

End User(there are other forms)

Typical BI StructureTypical BI Architecture

‘single version of the truth’

Business Intelligence

you don’t know what you don’t know

there may not be a single version of the truth

retrospective changes messy if possible at all

designed seriatim aggregations

hard to keep up to date

but

Big DataBig data is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualization. The trend to larger data sets is due to the additional information derivable from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data, allowing correlations to be found to "spot business trends, determine quality of research, prevent diseases, link legal citations, combat crime, and determine real-time roadway traffic conditions. As of 2012, limits on the size of data sets that are feasible to process in a reasonable amount of time were on the order of exabytes of data.[ Scientists regularly encounter limitations due to large data sets in many areas, including meteorology, genomics, connectomics, complex physics simulations, and biological and environmental research. The limitations also affect Internet search, finance and business informatics. Data sets grow in size in part because they are increasingly being gathered by ubiquitous information-sensing mobile devices, aerial sensory technologies (remote sensing), software logs, cameras, microphones, radio-frequency identification readers, and wireless sensor networks. The world's technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s; as of 2012, every day 2.5 quintillion (2.5×1018) bytes of data were created. The challenge for large enterprises is determining who should own big data initiatives that straddle the entire organization.Big data is difficult to work with using most relational database management systems and desktop statistics and visualization packages, requiring instead "massively parallel software running on tens, hundreds, or even thousands of servers”. What is considered "big data" varies depending on the capabilities of the organization managing the set, and on the capabilities of the applications that are traditionally used to process and analyze the data set in its domain. "For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration."

Big Data

Unstructured Data (including external)

Marketing Lingo

but Big Data is here

… and it’s big

US$28bn in 2012US$34bn in 2013

it’s not really about the platform

it’s about the analysis

Descriptive Title Quantitative Sophistication/Numeracy Sample Roles

Data Scientist or Quantitative Analyst Advanced Math/Stat

Internal expert in statistical and mathematical modelling and development, with solid business domain knowledge.

Business Intelligence / Operational Analytics

Good business domain, background in statistics optional

Running and managing analytical models. Application of traditional methods such as experience studies.

Business Intelligence/ ReportingData and numbers oriented, but no special advanced statistical skills

Reporting, dashboard, OLAP and visualization, some design, posterior analysis of results from quantitative methods. Spreadsheets, “business discovery tools”

Analytic Types

Types of Analysis

Type V

Data Scientist Job Description• Passion for “playing” with tons of data and supporting scientific experiments to

validate the performance of algorithms• Advanced degree in Statistics or related area• Experience with traditional as well as modern statistical learning techniques,

including: Support Vector Machines; Regularization Techniques; Boosting, Random Forests, and other Ensemble Methods.

• Strong computer science skills with high-level languages, such as R, Python, Perl, Ruby, Scala or similar scripting languages.

• Experience with Hadoop and working with multi-terabyte systems. • Extensive hands on experience working with very large data sets, including

statistical analyses, data visualization, data mining, and data cleansing/transformation.

• Business expertise and entrepreneurial inclination to discover novel opportunities for applying analytical techniques to business/scientific problems across the company.

• Good communication ability

Data Scientist

Statistical skillsComputer scientistBusiness expertCommunication skills

How do you train a data scientist?

Neil Raden“Like Actuaries”

Is there an opportunity for actuaries here?

If so what is it?

SOA initiative

Working group

White paper and recommendation

Opportunities

Statistical skills

Computer skills

How to deliver this

Opportunities

Actuaries already have: Most the statistical skills Some computer skills Business expertise Communication skills

Significant job growth in analytics is predicted

Reputation for actuaries in analytics can be enhanced

However… we have competition

U.S. Department of Laboroccupations forecasted for growth in analytics

Job Titles Expected Growth by

2018

Total # Expected

Projected Median Income

Top 10% Income

Librarians 8% 172,400 $52,530 $81,130

Accountants/Auditors 22% 1,570,000 $59,430 $102,380

Statisticians 13% 25,500 $72,610 $117,190

Ops Research Analysts 22% 76,900 $69,000 $118,130

Management Analysts 24% 925,200 $73,570 $133,850

Actuaries 21% 23,900 $84,810 >$160,780

Opportunities

Current employers/Current roles

Current employers/New roles

New employers/New roles

“Required” Skills/Techniques

Traditional Statistical Techniques Ordinary Least Squares Logistic Regression Generalized Linear Model Time Series

Methods That Group/Organize Trees/Clustering

Prep for Analysis Model Validation

Advanced Business Analytics – Computer Skills

Excel R SASMatlabStatisticaSPSSS-PlusStataEmblem

How do they compare? – Social Networks Followers(from blog by Robert Muenchen)

How do they compare? – Discussion Forum Posts(from blog by Robert Muenchen)

r-project.orgcoursera.org