Presentation MISSI2012_ Identifying Fraudulent Shipments Through Matching Shipping Documents With...

7/29/2019 Presentation MISSI2012_ Identifying Fraudulent Shipments Through Matching Shipping Documents With Phone Records 19.09.2012

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Identifying fraudulent shipments through matching

shipping documents with phone records

CzesawJdrzejek

MISSI 2012

With M. Nowak and M. FalkowskiInstitute of Control and Information Engineering

Poznan University of Technology


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Agenda

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1. Motivation2. Goals

3. The model

4. Rules and queries

5. Conclusions and Future Work


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Motivation Presentation of analytic approach to complex legal problems

This results in lack of analytic tools able to go beyondcollecting facts and performing some form of visualization onthese facts for a complete case

According toACFE economic crimes cost typical organization

5% of its annual revenue.

Economic crimes, 300-600 types, are particularly difficult tomodel and code into an expert system (contrary to a medicalarea, where knowledge appears mainly in form of

taxonomies). For example, fraudsters use many types ofschemes, techniques and transactions to achieve their goals,so it seemed impossible to construct a simple conceptualmodel of any generality

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Goal

Construct minimal ontology of a typical model (assetmisappropriation constituted two-thirds of all economiccrimes, PWC 2009 survey) we selected fraudulentdisbursement

Develop methodology ofanalysis

Generalize to a larger category of economic crimes

Design and implement a tool (AFIZ, Analyzer of Facts andrelations)

Verify with legal experts

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Motivation

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Despite enormous effort devoted to theconstruction of top level, core legal andapplication ontologies, there exists avery small number of works resulting indevelopment of practical systems


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Goals

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We want to decide whether a shipment to Czech

Republic/Slovakia could occur as stated in CMRdocuments.

Whether the driver could have reached the

destination point in Czech Republic/Slovakia by 15

oclock on day T2

Whether the driver could have reached the

destination point in Czech Republic/Slovakia on day

T2

Whether the driver could have reached the goods

receiving place in Poland on day T3, if known.


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The model

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We extract data from CMR documents to create

objects which correspond to origin and delivery

locations of the shipment.


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Transport day

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Transport day:

Criteria 1

Criteria 2

Criteria 3

Then 3 location objects form the transport day, which isthe main object of our analysis.


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Phone records convertion

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We convert phone records into phone calls objects withGIS property (of its corresponding BTS tower).


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Automated analysis

All objects are then moved into the map application.

Our system separates them by date, and performs day

by day analysis

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The algorithm

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Conclusions and Future Work We extended the minimal economic crime minimal model to a

widertypology

The importance of this work is not in formal progress in reasoning

but demonstrating that it is possible to build ontologies for

nontrivial cases

It is important to ask why in law area we deal with such a detailed

description is possible? The reason is that there is no

unintentional fraud, and evidence we considerare documents and

bank accounts, something that is traceable.

We hope that the knowledge base we develop will be amenable to

extensions that would make it highly practical

We are working on implementation of the knowledge base and

generation ofartificial data to test our approach 13


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THE END

Thank you for your attention!

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