1. Chandrasekhara S. ( “C.S.”) Ganti
cganti51@gmail.com
508-528-4525(H)
Career Highlights /Qualifications /
An Experienced Business Analyst / Applied Statistician / Predictive Modeler with expertise in the
areas of Fraud Detection, Risk Profiling / Management, Insurance Loss Prevention, Workload
Measurement & Management, Subrogation Recovery Management, Business Process Improvement,
Business Analysis of Key performance Indicators (KPI) and Automobile Theft Deterrent (ATD) systems
operating in a deadline driven fast paced environment;
Qualifications include:
- Self Starter and an ability to be productive
- Ability to comprehend complex business scenarios and blend in corporate culture readily
- Effective utilization of Information Technology for attaining corporate goals
- Individual Contributor / an effective Team Leader / Member in significantly diverse Corporate and
Consulting groups
- Effective Communication Skills and an ability to meet project deadlines unconditionally
Education: M.S (Operations Research), the George Washington University, 1976
M.S. (Statistics), Osmania University, India 1972
Summary of Technical Skills
Hardware: Windows Platforms, IBM Mainframe,
Operating Systems: Windows XP, WINDOWS 10
Languages: SQL, SAS,PROLOG (AI software language)
Analytics Software: SAS, PC SYSTAT, CRYSTAL BALL, BEST FIT,MSEXCEL
Database Systems: MS ACCESS, MS EXCEL
Business Intelligence: COGNOS ; ACCESS
Summary of Statistical Algorithms / Modeling Functions used
Forecasting Techniques, Time Series, Analysis of Variance, Covariance, Correlation, Uni-variate /
Multivariate Multiple Regression, Logistic Regression, Discrimination / Classification, Monte Carlo
Simulation, Chi Square Distribution etc Extreme Event Analysis / Modeling Return Periods
Industries / Application Background: Property Insurance Claims, Safety / Reliability of Theft Deterrent
Systems, Government Agencies responsible for National Security, Justice and Law, DOT Oil
Transportation, NASA Aero Space - Remote Sensed Information for Agriculture and Natural Resource
Applications
Major Accomplishments
Subrogation Recoveries
Client: A major Insurance Company
Problem Statement:
Client was confronted with problems involving property insurance claims, which became candidates for
subrogation involving time and efforts; absence of an automated process contributed to this scenario;
client wanted an automated process and a reporting mechanism in place for subsequent utilization &
effective control
Statistical Solution: Developed an algorithm on a mainframe system for analyzing large files to
accomplish the following: Extensive Informational reports were generated, Subrogation efficiency Ratios

2. were statistically characterized with respect to trends in time and their distribution. Final reports were:
1. Summary of claims paid and then recovered after it was determined they were valid however the
Subrogation recovery effectiveness were based on the following criteria:
A) Type of Claim - Industry / Root Cause Analysis B) Geography C) Type of Counsel (In-house /
External) etc
Results: Project objectives were attained; substantial cost savings were realized by eliminating the
services of external legal counsel / audit consulting companies previously contracted to support project
objectives; this effort saved the clients thousand of $ in operating expenses
Analysis of Insurance Losses and Trend Analysis
Client: A major Insurance Company
Problem Statement:
Client was confronted with problem of developing Trends in Loss and Ratios for various segments of
business operation and company performance evaluation; Client requirements were:
- Analysis of past claims / losses by Month and YTD and for the preceding two Years / Year over
Comparisons for the company performance;
- Identification of key stake holders involved and their roles, Executives, Group Heads and IT
Stakeholders
- Analysis of $ amount paid (by topography, Natural vs. Physical Hazards; Loss Size Groups, No of
losses, Total Loss Amount)
Statistical Solution: Developed algorithms using analytical methodology on a mainframe system for
analyzing large files, generated reports via COSGNOS / SQL facilities to accomplish the following:
Extensive Informational Reports were generated reflecting Excel Charts and Pivot Tables to highlight
trends over time and their distribution across categories
Results: Entire processes were readily automated / bringing in a net 50 % - 75% of Cost savings.
Final reports were ready for submission for Executive Presentation on Dashboard and Key Performance
Indicators on a monthly basis – and in time for Board Meetings to be held (3 – 4 times a Year)
Automobile Theft Prevention & Strategization
Client: Consulting / Research Company Project for Industry Trade Association / Govt. Regulatory Impact
Problem Statement:
Client experienced massive losses due to automobile thefts - Client requirements were:
- Analysis of past decade or so Auto Theft Deterrent Systems (Passive, Active, Parts Making) across
Model Years, Demographics of drivers -- Age, Population Density, Urban/Suburban, Crime Index.
- Identification of previous US and other Country Auto Safety / Theft Research Study Reports /
Critique models, Review of Existing Literature on Logistical Regression
- Analysis of data for establishing a trend (mega – millions of records across many model years /
model lines and Makes)
Statistical Solution / As an Independent Consultant overseeing the Applied Statistical team: Logistical
Regression Algorithms: Guided and supervised Logistical regression algorithms on SAS / WINDOWS
based systems, using extensive Federal, Trade Association and other mega datasets across many years
– some very large datasets/files, generated summary reports to accomplish the following:
Final report was submitted to the Trade Association and the Govt. Agency responsible for regulating the
Safety /Theft Deterrent Systems and their Cost Effectiveness for implementing in various Automobile lines

3. / Models with Odds Ratios for comparison based on Logistic Regression Models.
Results: Significant Cost Savings in Hundreds of thousand dollars will be resulting due to the modeling
and avoiding unnecessary upgrades / and or other cost intensive parts markings for certain lines and
types of automobiles. President of the company commended my individual business acumen, solid
contribution of Statistical Expertise in literature review / advice along with the Team efforts and the High
Quality of our work, the results of which were promulgated as regulations across several models and type
of vehicles and was signed into an order.
Process–Reengineering
Client: Insurance / Personal Lines
Problem Statement:
Client had problem of developing efficient Market Channels for their Life Insurance Products distributed
across several geographic regions for efficiency, consistence, and profitability. The current processes
were outdated, inconsistent and inefficient. Objective of the project was to re-engineer current processes
for optimization
Client requirements were:
- Analysis of current product Marketing Channels, the processes involved, Customer Service
functions and Geography serviced past
- Current Service Product / Company – Evaluated with respect to their results delivery
- Evaluation of other Available Products in the Market Place
- Established Process Flows for better comprehension
- Streamlined Solution for efficient Policy Issuance and Semi-Real time service for problems that may
arise due to demographics of certain population segments (Age, Area of residence, Availability of
services)
Business Process Optimization Solutions: Entire processes streamlined with process flows; generated
MS VISIO To-be process flows in a large room setting of: 30 people: Client execs, Vendor execs, our
teams, business leaders and IT Professionals,
Employment History:
Name of the Employer Position Dates of Employment
State Street Corp. Client Report & QA Testing January 2013 – March 2013
Independent Consulting P&C Ins. Software / Big Data Analytics October 2010 – December 2012
U.S DHS/ Ver. Division Operations Research Analyst December 2009 – August 2010
Keane T/ Mgmt. Consulting Sr. Business Analyst / Consultant August 2006 – August 2008
JP Research / Consulting Statistician / Predictive Modeler May 2005 – June 2006
Factory Mutual Insurance Co. Underwriting Research Specialist July 1999 – October 2004