Dr. Adrian Gilbert (Ph.D) Email & Phone Number

Sydney, New South Wales, Australia

I'm working as a behavioral psychologist specialising in counselling clients suffering with anxiety, depression, schizophrenia, bipolar disorder and multiple personalities.

Sydney, New South Wales, Australia

Sydney, Australia

I'm working with GOY assisting them with their marketing and working towards building partnerships with some of the major internet sales organisations.

Sydney, Australia

I was involved in developing customer churn and retention models using SAS/SQL. The models were logistic regression models.

Sydney, Australia

My role involved the documenting and cleansing of datasets using SAS/SQL.

Canberra, Australia

I developed statistical models to predict long term claim liabilities using IBM modeller and techniques such as OLS regression and ARIMA. The role involved continual interaction with senior managers and analysts. Potential savings could have been up to $10 million a year.

Sydney

I was involved in data extraction using SQL and then analysing the data using SAS to develop a series of customer churn models for various insurance products such as Car, Home, Travel and Life Insurance. Potential savings could have been up to $1 million per product.

North Sydney

Developed statistical models to help target AMEX customers more effectivelyProvided CRM Reporting for Sony and BCFWon modeling contract with AMP for propensity to churn and segmentation modelsUsed SQL, SPSS and IBM Modeller to summarise data and develop models

Sydney, Australia

Developed propensity to churn and segmentation models using Logistic Regression and Clustering

Sydney

Assisted with CRM/email marketing with statistical models that lead to more efficient email campaigns ($100k)Developed cross-sell and up-sell modelsDeveloped profitable marketing segments for targeting ($200k) Evaluation of effectiveness of on site marketing

North Sydey

Used Logistic Regression to Predict Identity FraudUsed ARIMA and Regression to predict odometer readingsProduced reports for Senior Managers and MP'sDaily use of SAS and SQL

Chatswood

Created new data driven marketing segments that will help generate more revenue. Used SPSS to perform PCA and Clustering to define the segments based on sales revenue.

Sydney, Australia

Built statistical models to predict customer churn using SPSS Clementine.Over a dozen data bases were accessed to create the final data file to be analysed.A number of different models were built that included neural nets, regression and tree models. (Potential savings of $450K per year)Built statistical models to predict fraud using SPSS. A large number of databases were accessed and a file was created consisting of millions of records and over a thousand variables. Fraud projects included Dental Fraud, Optical Fraud and Employee Fraud.A combination of Clustering and Trees were used to create the models.(Potential savings of $200K a year)Set up new more profitable customer segments. A Trees algorithm called C5 was used to create a profile of customers who were generating the most revenue for HCF. (Potential savings of $10K per campaign)Built statistical models to generate increased product cross-sell and up-sell. These models were built for the Products Marketing Team, the Eyecare Team and the Life Insurance team using a mix of Regression and Trees. (Potential savings of $20K per project)

Canberra

While at the AIC I wrote a report dealing with levels of violence in Australian societyRedesigned a firearms questionnaireSetup firearms database

Wellington

Whilst at the Inland Revenue Service I was involved in building a regression scorecard to predict student loan defaulters using spss clementine and writing a report (Potential savings of $1 million a year)Data quality checking using clementineAdhoc queries for Price Waterhouse using Hyperion Brio

Sydney

Whilst at Suncorp I was involved in:Setting up an access data base with excel front end to evaluate reasons for client retention for Home Insurance RiskData extraction and reporting about no. and dollar amounts of home insurance claims and type of claim using SAS & SQLFactor Analysis/Cluster Analysis using SPSS to segment Home Insurance Clients and profitable segmentsSummary reports dealing with particular home insurance segments such as profitable customers and at risk of attrition customersProviding advice about appropriate sample sizes for market research surveys

Melbourne, Australia

While at Flybuys I was involved in the segmentation of Coles, NAB and Mike Hill Data with regard to product usage and amount purchased (Each report was billed at $2K)Predicting likelihood to purchase behavior using Logistic RegressionUsing SQL to generate reports of client purchasing behavior by product and over time

Melbourne, Australia

Whilst contracted to the NAB I was involved in the Evaluation of Home Loan Default Risk Scorecard Performance with regard to model fit (Potential savings of $1Million)Evaluation of Flexi Plus Home Loan Default Risk Scorecard Performance with regard to model predictiveness (Potential savings of $1Million)Suggested scorecard improvements to reduce RiskProviding advice about some aspects of the Basel II Accord and the tighter reporting requirements it imposes with regard to Risk

Melbourne, Australia

Whilst contracted to Telstra I was involved in the use of Logistic Regression to predict Risk of clients leaving TELSTRA to move to competitors and 3 presentations to senior managers.(Potential savings of $1Million a year)Use of clustering & factor analytic techniques and Tree Algorithms to conduct segment construction and comparison with regard to profitability.Use of logistic regression to predict Risk of leaving Telstra with regard to internet customers(Potential savings of $100K a year)Use of ANOVA to measure the impact of a phone sticker campaign.(Potential savings of $10K for future campaigns)

Melbourne, Australia

Built ARIMA Models to gauge the effects of the Recession and the Drink Drive AdvertisingCampaign on Crash Frequency and Severity. Achievements:Two volume report detailing the impact of advertising and speed cameras on the Risk of road trauma.