|
Clementine
An improved risk management framework for tax collection
Lyne Sincennes
Director
Canada Revenue Agency
Canada
With personal income tax accounting for 47 percent of total budgetary revenues, efficient tax collection is crucial to support the Canadian government’s spending plans. Playing an important role in the process is the Canada Revenue Agency’s (CRA) Debt Management Branch, which is responsible for ensuring compliance with filing and reporting laws within a self-assessment tax system.
This session described how the CRA used SPSS’ Clementine workbench, to develop risk models to:
- Identify those non-compliant taxpayers who are likely to respond positively to appropriate enforcement actions
- Predict the likelihood of a taxpayer voluntarily resolving a tax debt
- Predict the probability that a collections officer will need to take enforcement action to resolve a debt
- Predict the likelihood of success of automated or call centre responses to debt issues.
In addition, CRA showed how they used SPSS models to identify and claim $7 million in new revenues from previously written-off, non-compliant taxpayers in a pilot project. Once in full production, the CRA expects to generate $180 million of additional revenue.
Back
|
Clementine, Text Mining for Clementine
Mining Dutch history: researching public debate in the nineteenth century
Dr José de Kruif
Researcher
Utrecht University Research Institute
for History
The Netherlands
The presentation discussed research into the role of pamphlet and newspaper texts in the Netherlands during the 19th Century, a period of transition in the Dutch media landscape.
Many textual sources traditionally used by historians are becoming available in electronic form, opening new possibilities for the use of OCR and text mining to examine large quantities of printed materials. The paper described how pamphlets and newspapers covering important public issues were scanned and, through OCR techniques, converted into electronic texts.
Then, using text mining, the Research Institute compared texts for common occurrences of rhetorical devices, terminology, references to persons, institutions, events and arguments.
Text mining was also used to compare the results with metadata such as the medium, authorship and genre of the publications.
The session described how this method results in a much clearer image of how the media worked in the 19th Century, and how it offers more concise answers to the questions of what messages were being conveyed, who they were meant for and how they were being communicated.
Attendees also heard how the research completed – and partly replaced – fragmented impressions of nineteenth-century press culture in the Netherlands, especially during a period of passionate dispute between the Government and Protestant and Roman Catholic citizens.
Back
|
|
SPSS, SPSS Server, Clementine
Data mining catches fraudulent patient sharing schemes
Marcee Sturino
Director, Data Informatics
TrustSolutions LLC
USA
TrustSolutions LLC is a Program Safeguard Contractor for the United States Department of Health and Human Services’ Centers for Medicare and Medicaid Services. It works with the U.S. federal government to detect and prevent fraud, waste and abuse in one of the country’s major health-care programs.
One particular issue that TrustSolutions was called upon to investigate was an allegation that health care facilities were sharing patients among themselves – and collecting fraudulent payments for each case.
In this session, TrustSolutions described how they used statistics to extract and format patient and claims data, and applied data mining to find and validate instances of fraud. As result, they disclosed, there were several referrals to law enforcement agencies in relation to potential overpayments exceeding US $14 million.
Back
|
SPSS, Clementine, Dimensions, SPSS Text Analysis for Surveys
Using analytics to develop stronger and safer communities
Keith Bentley
Chief Superintendent (Retired)
Greater Manchester Police
UK
In the UK, responsibility for delivering crime reduction and public safety initiatives, at both strategic and tactical levels, falls to the police and to local authority personnel. In Oldham, a town near Manchester, the local government authority and the police formed a strategic partnership with SPSS to integrate data collection with traditional surveys and analysis methods to help deploy community safety platforms.
People concerned with establishing and maintaining safe and secure communities were interested to hear how Oldham Police used these analytical methods to embed crime reduction and public safety improvements within local communities through ‘Local Area Agreements’ that provide a road map for sustainable improvements in public safety and securing government support.
While SPSS Base and Dimensions were the primary tools for this exercise, the session also discussed concepts for linking SPSS Clementine into an intelligence model that may be helpful to police operations.
Back
|
|
SPSS
Improving social welfare policy-making with SPSS reporting
Carlo Vreugde
Analyst Co-ordinator
SGBO
The Netherlands
This presentation particularly informative for those who use SPSS Base to analyse data, and then output the results to Microsoft® Word.
SGBO is a research and consulting agency specialising in local government issues (formerly, it was the research arm of the association of Dutch municipal governments). Following the introduction of a new law that makes local government agencies responsible for a wide range of social services, SGBO was commissioned to produce benchmark reports for more than 150 municipalities.
To achieve this efficiently, SGBO used SPSS syntax to export hundreds of different analytical results to Word documents, not as blocks of text but automatically placing text, tables and graphs in the placeholders and bookmarks set up in Word.
SGBO went on to describe how automated reporting has improved the effectiveness and cost-efficiency of local government, enabling municipalities to minimise local taxes.
Back
|
Clementine
Data mining – what it really is and what it can do for your organisation
Richard Hren, PhD
Director, Product Marketing
SPSS Inc.
USA
‘Data mining’ is a frequently used yet often misunderstood technical term, and in this session talked about the ‘true’ meaning of data mining: what it is – and isn’t; what it does – and doesn’t do; and how it can integrate and inform the day-to-day decision processes of many organisations.
As importantly, the session gave an appreciation of the incredible value that predictive analytics delivers to an organisation – how the use of analytics drives better decisions to provide rapid and significant returns.
In fact, the ability to deliver impressive return-on-investment figures is the critical proof of the rationale for deploying predictive analytics and becoming a true Predictive Enterprise.
Back
|
|
Clementine
Using data mining to target defaulters and increase tax payments
Véronique Vandamme
Data Warehouse Manager
Elly Goossens
Business analyst
FOD Financiën
Belgium
According to the American inventor and statesman Benjamin Franklin, “In this world nothing can be said to be certain, except death and taxes”. Not everyone believes him, however, and some people will try hard to avoid or default on their tax obligations. But thanks to analytics, avoiders and defaulters in Belgium are finding it very difficult to escape.
The Minister of Finance instructed the Federal Public Service Finance (FPSF) to recover €75 million in unpaid taxes, and as part of the plan to achieve this, the organisation is building a warehouse of information about people who don’t pay their taxes.
This session was about how statistics are used to increase tax revenues by analysing a combination of internal and external sources, and how the expertise of FPSF’s analysts is being distributed in a format that can be used throughout the organisation.
The FPSF also confirmed results that exceeded expectations, with €4 million recovered in the first phase of trials and a further €2,7 million in the second. Perhaps Ben Franklin was right after all.
Back
|
Clementine, SPSS Predictive Enterprise Services
Faster, more flexible development of statistical processes with SPSS
Dr Helma Schapendonk-Maas
Statistical Researcher
Statistics Netherlands
The Netherlands
Like many official statistical agencies, Statistics Netherlands (SN) is facing a continuously changing environment: new, often large data sources appear, and existing ones change.
To cope with the dynamic processes required, and with changing business rules, the organisation needs tools that can be adapted for new types of data exploration and facilitate easy development.
As a result, SN used Clementine and SPSS Predictive Enterprise Services to develop new statistical processes, with the aim of achieving faster development times, more development flexibility and a more uniform process environment.
This presentation described how, using data mining, new processes were developed for demographical statistics that were not as dependent on support from IT experts and could easily be maintained by statisticians, and how Clementine proved very suitable for transforming large datasets with relatively few variables.
In addition, SN described how SPSS Predictive Enterprise Services ensures reproducible and traceable results, including version control and audit trails; how it supports iterative development using Clementine on the actual statistical data; and also how it provides a generic tool for maintaining and using statistical rules.
As a result, Statistics Netherlands developed, tested and put in production multiple streams for many different statistical products while meeting the planned development schedule. Building similar processes using standard development methods and tools would have taken two to three times longer.
Back
|