how do you insure yourself against the big data tsunami
TRANSCRIPT
Copyright © 2011, SAS Institute Inc. All rights reserved.
How do you insure yourself against the Big Data tsunami? Develop a Big Analytics policy! Keith Collins Senior Vice President & Chief Technology Officer SAS Institute
2
Copyright © 2011, SAS Institute Inc. All rights reserved.
3
Copyright © 2011, SAS Institute Inc. All rights reserved.
Who is SAS?
4
Copyright © 2011, SAS Institute Inc. All rights reserved.
Industry Focus
5
Copyright © 2011, SAS Institute Inc. All rights reserved.
Today’s Discussion
Hardware Landscape
Step Change in Data
Big Analytics
6
Copyright © 2011, SAS Institute Inc. All rights reserved.
Changes in Technology
Storage Cost per Megabyte Shifts in Hardware
Source: PC Magazine, October 2, 2007
C. Moore, Data Processing in ExaScale-Class Computer Systems,
Salishan, April 2011
7
Copyright © 2011, SAS Institute Inc. All rights reserved.
Step Change in Data
8
Copyright © 2011, SAS Institute Inc. All rights reserved.
Step Change in Data
RDBS Specialized DB:
SAS, Netezza, Greenplum, Hadoop
9
Copyright © 2011, SAS Institute Inc. All rights reserved.
PROBLEM:
The disconnect between the ease
of acquiring data and the ability to
make decisions on them.
10
Copyright © 2011, SAS Institute Inc. All rights reserved.
Competitive Gap of Data Management
Source: Economist Intelligence Unit: Big data,
Harnessing a game-changing asset. September 2011
5–6% more productive
than competitors
11
Copyright © 2011, SAS Institute Inc. All rights reserved.
“Big Data” in Insurance Industry
New Data
In-vehicle
Demographic
Social
Location
Importance of data quality
12
Copyright © 2011, SAS Institute Inc. All rights reserved.
Big Analytics: Fraud
Problem: Fraud revenue loss across lines of business
Strategy:
Use analytics to detect fraud patterns in enterprise data
Prioritize investigator time and focus through alerts and scoring
Become proactive in detecting fraud (First Notice of Loss)
Case Study: Large Commercial Insurer
SAS Fraud Framework
» 100% ($16B) of company’s workers compensation and general liability claims processed
» Hosted solution with SAS OnDemand
» 57% uplift on existing fraud detection process
» Incremental estimated $10.3M saved annually
» SAS’s analytics drove 35% better analytics than competitors
13
Copyright © 2011, SAS Institute Inc. All rights reserved.
Mitigating Risk in Minutes
United Overseas Bank
Portfolio of millions of loans and 44,000 security instruments
Complex economic capital and market risk models
Hosted grid appliance in SAS’s ASP environment
Re-entrant code is propagated across all notes so additional blades and processors do not degrade performance
Computation time went from 8-12 days down to just a few minutes
Imagine putting that computational power to work during a catastrophic event
14
Copyright © 2011, SAS Institute Inc. All rights reserved.
Customer Analytics
Problems: No single view of customer, ineffective customer segmentation, inability to predict behavior, multiple distribution channels
Strategy:
Consolidate data management capabilities
Analyze data for trends to:
» calculate customer retention scores to provide early-warning indicators
» determine customer value
Case Study: Max New York Life
SAS Business Analytics (SAS Campaign Management, SAS Enterprise Miner, SAS Enterprise Guide)
» 20% increase in cross-sales
» 40% increase in premium revenue
Copyright © 2011, SAS Institute Inc. All rights reserved.