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John R Lucker

from Lakewood Ranch, FL
Age ~63
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Also known as:
John J Lucker, John Blue, Ridge John Blue
Related to:
Alex G Cannella, 27
Connected to:
James G Lucker, 72Jeanmarie M Lucker, 64Kathie L Lucker, 71Kathy K Lucker, 67William G Lucker, 63Karen S Luckerman, 62Dorothy D Luckers, 67Juan C Luckert, 56Alisha Luckett, 28Amy C Luckett, 43

John Lucker Phones & Addresses

  • Lakewood Ranch, FL
  • 88 Blue Ridge Dr, Simsbury, CT 06070 (860) 651-7979 (860) 651-9337
  • 7 Simsbury Manor Dr, Weatogue, CT 06089 (860) 651-7979
  • Rocky Hill, CT
  • West Hartford, CT
  • Sarasota, FL
  • 88 Blue Ridge Dr, Simsbury, CT 06070

Work

Company: Consultant Mar 2020 Position: Senior strategic and executive advisor

Education

Degree: Master of Business Administration, Masters School / High School: University of Rochester 1985

Skills

Analytics • Strategy • Management Consulting • Consulting • Leadership • Business Process • Management • Analysis • Risk Management • Insurance • Data Mining • Business Process Improvement • Financial Services • Predictive Modeling • Business Analytics • Business Transformation • Business Strategy • Executive Management • Project Management • Business Analysis • It Strategy • Data Warehousing • Segmentation • Professional Services • Program Management • Financial Modeling • Mergers and Acquisitions • Underwriting • Change Management • Data Analysis • Information Technology • Business Process Re Engineering • Acquisition Integration • Governance • Crm • Portfolio Management • Project Portfolio Management • Pricing • Enterprise Risk Management • Organizational Design • Banking • Statistical Modeling • Predictive Analytics • Strategic Consulting • Operational Risk Management • Due Diligence • Performance Improvement • R&D • Data Visualization • Rules Engines

Ranks

Certificate: Certified Information Systems Auditor

Interests

Www • Simsburytaverneers • Education • Vintage Base Ball • Com • Http • Health

Emails

j***[email protected]

Industries

Management Consulting

Resumes

Resumes

John Lucker Photo 1

Senior Strategic And Executive Advisor

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Location:
Rochester, NY
Industry:
Management Consulting
Work:
Consultant
Senior Strategic and Executive Advisor
Cigna Jan 1999 - Jul 2000
Controller
Deloitte Jan 1999 - Jul 2000
Principal and Partner - Global Advanced Analytics and Modeling Market Leader
Cigna Jul 1996 - Jan 1999
Chief Technology Officer
Aetna Aug 1995 - Jun 1996
Business and Audit Consultant
Education:
University of Rochester 1985
Master of Business Administration, Masters University of Rochester - Simon Business School 1983 - 1985
Master of Business Administration, Masters, Marketing, Information Systems University of Rochester 1978 - 1982
Bachelors, Bachelor of Arts, Biology Tenafly High School 1978
Dwight - Englewood School 1978
Skills:
Analytics
Strategy
Management Consulting
Consulting
Leadership
Business Process
Management
Analysis
Risk Management
Insurance
Data Mining
Business Process Improvement
Financial Services
Predictive Modeling
Business Analytics
Business Transformation
Business Strategy
Executive Management
Project Management
Business Analysis
It Strategy
Data Warehousing
Segmentation
Professional Services
Program Management
Financial Modeling
Mergers and Acquisitions
Underwriting
Change Management
Data Analysis
Information Technology
Business Process Re Engineering
Acquisition Integration
Governance
Crm
Portfolio Management
Project Portfolio Management
Pricing
Enterprise Risk Management
Organizational Design
Banking
Statistical Modeling
Predictive Analytics
Strategic Consulting
Operational Risk Management
Due Diligence
Performance Improvement
R&D
Data Visualization
Rules Engines
Interests:
Www
Simsburytaverneers
Education
Vintage Base Ball
Com
Http
Health
Certifications:
Certified Information Systems Auditor
License Currently Inactive
Information Systems Audit & Control Association, License Currently Inactive

Business Records

Name / Title
Company / Classification
Phones & Addresses
John Lucker
Connecticut Rivers Council Inc
Civic/Social Association
60 Darlin St, Hartford, CT 06108
(860) 289-6669, (860) 290-8860
John Lucker
FARMINGTON VALLEY VINTAGE BASE BALL CLUB, LLC
327 Hopmeadow St, Weatogue, CT 06089
88 Blue Rdg Dr, Simsbury, CT 06070

Publications

Us Patents

Commercial Insurance Scoring System And Method

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US Patent:
8145507, Mar 27, 2012
Filed:
Oct 23, 2001
Appl. No.:
10/054702
Inventors:
Frank M. Zizzamia - Canton CT, US
Cheng-Sheng Peter Wu - Arcadia CA, US
Dominic A. Tocci - Oak Park IL, US
Matthew R. Carrier - Naperville IL, US
John Lucker - Simsbury CT, US
Assignee:
Deloitte Development LLC - Hermitage TN
International Classification:
G06Q 40/00
US Classification:
705 4, 705 38, 705 728
Abstract:
A quantitative system and method that employs data sources external to an insurance company to generate a statistical model that may be used to more accurately and consistently predict commercial insurance profitability (the “predictive statistical model”). The system and method are able to predict individual commercial insurance policyholder profitability on a prospective basis regardless of the internal data and business practices of a particular insurance company.

Method And System For Determining The Importance Of Individual Variables In A Statistical Model

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US Patent:
8200511, Jun 12, 2012
Filed:
Nov 28, 2001
Appl. No.:
09/996065
Inventors:
Frank M. Zizzamia - Canton CT, US
Cheng-Sheng Peter Wu - Arcadia CA, US
Raymond E. Stukel - Elmhurst IL, US
Hrisanthi Adamopoulos - Wethersfield CT, US
John R. Lucker - Simsbury CT, US
Assignee:
Deloitte Development LLC - Hermitage TN
International Classification:
G06Q 40/00
US Classification:
705 4, 705 2, 705 3
Abstract:
A method and system for determining the importance of each of the variables that contribute to the overall score of a model for predicting the profitability of an insurance policy. For each variable in the model, an importance is calculated based on the calculated slope and deviance of the predictive variable. Since the score is developed using complex mathematical calculations combining large numbers of parameters with predictive variables, it is often difficult to interpret from the mathematical formula for example, why some policyholders receive low scores while other receive high scores. Such clear communication and interpretation of insurance profitability scores is critical if they are used by the various interested insurance parties including policyholders, agents, underwriters, and regulators.

Licensed Professional Scoring System And Method

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US Patent:
8335700, Dec 18, 2012
Filed:
Aug 15, 2011
Appl. No.:
13/210064
Inventors:
Frank M. Zizzamia - Avon CT, US
John R. Lucker - Simsbury CT, US
Karl J. Knable - Indianapolis IN, US
Assignee:
Deloitte Development LLC - Hermitage TN
International Classification:
G06Q 40/00
US Classification:
705 4, 705 35
Abstract:
A quantitative system and method that utilizes data sources external to a company, and when available, traditional data sources, e. g. , internal company information, to (i) provide for matching criteria such as, for example, demographic needs, to a database that can provide a number of potential recruits or customers and that can also be used to screen both current and prospective company employees matching the criteria, and (ii) generate a statistical model that can be used to predict future profitability and productivity of licensed professionals.

Licensed Professional Scoring System And Method

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US Patent:
20040054553, Mar 18, 2004
Filed:
Jul 9, 2003
Appl. No.:
10/616456
Inventors:
Frank Zizzamia - Avon CT, US
John Lucker - Simsbury CT, US
Alice Kroll - Carmel IN, US
Karl Knable - Indianapolis IN, US
International Classification:
G06F017/60
US Classification:
705/001000, 705/010000
Abstract:
A quantitative system and method that utilizes data sources external to a company, and when available, traditional data sources, e.g., internal company information, to (i) provide an easily accessible means for matching criteria such as, for example, demographic needs, to a database that can quickly provide a number of potential recruits or customers and that can also be used to screen both current and prospective company employees matching the criteria, and (ii) generate a statistical model that can be used to accurately and consistently predict future profitability and productivity of licensed professionals.

Method And System For Estimating Insurance Loss Reserves And Confidence Intervals Using Insurance Policy And Claim Level Detail Predictive Modeling

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US Patent:
20060136273, Jun 22, 2006
Filed:
Sep 9, 2005
Appl. No.:
11/223807
Inventors:
Frank Zizzamia - Avon CT, US
Jan Lommele - West Hartford CT, US
James Guszcza - Santa Monica CA, US
John Lucker - Simsbury CT, US
Peter Wu - Arcadia CA, US
International Classification:
G06F 17/10
G06Q 40/00
US Classification:
705004000, 703002000
Abstract:
A computerized system and method for estimating insurance loss reserves and confidence intervals using insurance policy and claim level detail predictive modeling. Predictive models are applied to historical loss, premium and other insurer data, as well as external data, at the level of policy detail to predict ultimate losses and allocated loss adjustment expenses for a group of policies. From the aggregate of such ultimate losses, paid losses to date are subtracted to derive an estimate of loss reserves. Dynamic changes in a group of policies can be detected enabling evaluation of their impact on loss reserves. In addition, confidence intervals around the estimates can be estimated by sampling the policy-by-policy estimates of ultimate losses.

Commercial Insurance Scoring System And Method

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US Patent:
20120271659, Oct 25, 2012
Filed:
Feb 15, 2012
Appl. No.:
13/397508
Inventors:
Frank M. Zizzamia - Canton CT, US
Cheng-Sheng Peter Wu - Arcadia CA, US
Dominic A. Tocci - Oak Park IL, US
Matthew R. Carrier - Naperville IL, US
John R. Lucker - Simsbury CT, US
Assignee:
Deloitte & Touche LLP - Wilton CT
International Classification:
G06Q 40/08
US Classification:
705 4
Abstract:
A quantitative system and method that employs data sources external to an insurance company to generate a statistical model that may be used to more accurately and consistently predict commercial insurance profitability (the “predictive statistical model”). The system and method are able to predict individual commercial insurance policyholder profitability on a prospective basis regardless of the internal data and business practices of a particular insurance company

Method And System For Determining The Importance Of Individual Variables In A Statistical Model

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US Patent:
20120284059, Nov 8, 2012
Filed:
May 3, 2012
Appl. No.:
13/463492
Inventors:
Frank M. Zizzamia - Canton CT, US
Cheng-Sheng Peter Wu - Arcadia CA, US
Raymond E. Stukel - Elmhurst IL, US
Hrisanthi Adamopoulos - Wethersfield CT, US
John R. Lucker - Simsbury CT, US
Assignee:
Deloitte Development LLC - Hermitage TN
International Classification:
G06Q 40/08
US Classification:
705 4
Abstract:
A method and system for determining the importance of each of the variables that contribute to the overall score of a model for predicting the profitability of an insurance policy. For each variable in the model, an importance is calculated based on the calculated slope and deviance of the predictive variable. Since the score is developed using complex mathematical calculations combining large numbers of parameters with predictive variables, it is often difficult to interpret from the mathematical formula for example, why some policyholders receive low scores while other receive high scores. Such clear communication and interpretation of insurance profitability scores is critical if they are used by the various interested insurance parties including policyholders, agents, underwriters, and regulators.

Fraud Detection Methods And Systems

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US Patent:
20140058763, Feb 27, 2014
Filed:
Jul 24, 2013
Appl. No.:
13/987437
Inventors:
Michael F. Greene - Boston MA, US
John R. Lucker - Simsbury CT, US
Steven E. Ellis - Linthicum Heights MD, US
James C. Guszcza - Santa Monica CA, US
Steven L. Berman - Havertown PA, US
Amin Torabkhani - New York NY, US
International Classification:
G06Q 40/08
US Classification:
705 4
Abstract:
An unsupervised statistical analytics approach to detecting fraud utilizes cluster analysis to identify specific clusters of claims or transactions for additional investigation, or utilizes association rules as tripwires to identify outliers. The clusters or sets of rules define a “normal” profile for the claims or transactions used to filter out normal claims, leaving “not normal” claims for potential investigation. To generate clusters or association rules, data relating to a sample set of claims or transactions may be obtained, and a set of variables used to discover patterns in the data that indicate a normal profile. New claims may be filtered, and not normal claims analyzed further. Alternatively, patterns for both a normal profile and an anomalous profile may be discovered, and a new claim filtered by the normal filter. If the claim is “not normal” it may be further filtered to detect potential fraud.
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John R Lucker from Lakewood Ranch, FL, age ~63 Get Report