Questions tagged [fraud]

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1answer
33 views

Feature engineering using the target/dependent variable

I am a beginner and my question relates to feature engineering. My task is to help develop a model which predicts whether a customer request is a fraud case. A variable in the dataset is the ...
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1answer
41 views

How can I make use of zip codes when I am building a model for fraud detection

I have gone through few articles but I am not convinced on what should I do with these. I know from business standpoint it might be good to consider fraudulent transactions happening from unknown ...
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0answers
18 views

How to detect possible fraudulent administration of a survey questionnaire?

I'm involved in a survey on a highly sensitive topic, where I have reason to believe that the subcontractor who was responsible for data collection (a call centre) may have been pressured / paid / ...
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0answers
55 views

Combining classification models for fraud detection

i have a classification problem : fraud / non fraud. My classes are inbalanced ( 0.8% fraud rows ). I first split my data in train and test sets. Let's say I have 10 fraud and 100 non fraud rows in ...
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0answers
66 views

Question about sample size for each class for machine learning classifiers

I'm trying to use a machine learning classifier (SVM in particular) on data that I generate. Unlike other applications, the data is not given to me but rather I have the flexibility to generate how ...
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0answers
17 views

Modelling my own cost function for skewed distributions

A while ago I worked in a model used for fraud detection, as that involved a very asymmetric distribution, I used F1-score as my loss function. However, I cannot stop thinking about it, and I feel F1-...
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0answers
19 views

What test should I use to compare 2 group with very similar characteristic?

I am currenty doing a fraud detection analysis. I have 2 groups of data points with several features that I create myself. 1 group is fraud people and another group is non fraud. I found out that ...
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0answers
18 views

How to minimize dependency between existing model and retraining dataset (using fraud modeling as example)?

What are methods to minimize dependencies between the existing model in production and the data that will be used for retraining future models (when future samples are created based on the existing ...
3
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2answers
742 views

Feature engineering for fraud detection

I'm doing some research into fraud detection for academic purposes. I' d like to know specifically about techniques for feature selection\engeneering from a transactional dataset. In more details, ...
1
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0answers
31 views

How to detect fraudulent values in a data set?

First off, I don't know if this is the appropriate place to ask this question? If not, I apologize, and I'd appreciate any advice on where else to go with it. If it's ok, here's a description of my ...
8
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1answer
85 views

Would you flag this data as fraudulent?

Let's suppose you have been given some data from a randomized block design with 4 repetitions and 23 treatments. After an initial inspection of the data, you notice that for 8 treatments all ...
2
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0answers
51 views

How to compare two methods with censored and bias data

I will use an example of comparing two different antifraudes to better illustrate the statistical problem. (Antifraud is an algorithm that analyzes whether a transaction is a real transaction or a ...
2
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2answers
198 views

Alternatives to logistic regression when data is unbalanced [duplicate]

Using Python's pandas, sklearn, and stats models API, I have trained a logistic regression on a training dataset that tells me whether or not a particular purchase (based on gender, and other features)...
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1answer
577 views

Is an Average Precision of 60% acceptable output in a fraud detection machine learning algorithm? What does it signifies?

First question here, I am new to machine learning and wanted to understand the following: I used decision trees, boosting to classify fraud users and I am getting average precision around 60% on my ...
1
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1answer
1k views

any data i can use for healthcare fraud detection [closed]

I am truly desperate in looking for a healthcare fraud data for my project on fraud detection. Can some kind soul please please help me? I have searched online but found nothing..May i know where to ...
2
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0answers
69 views

Methods to detect fraudulent test data

I work for a company that manufactures widgets and we test each widget before it leaves the factory. One of the parameters that we ask our testers to manually record is the cycle time. Lately I've ...
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0answers
22 views

Experimentally testing classification models

I have implemented a machine learning algorithm (say, algorithm A) to perform binary classifications of fraudulent and non fraudulent clients. I am already using other algorithms (say, B and C) to ...
3
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0answers
178 views

How to retrain a production classifier that blocks its own positive examples?

I'm looking for help understanding how to re-train a fraud detection classifier that's been deployed to production (where it successfully blocked much, but not all fraud coming into the system). I ...
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0answers
146 views

Modeling rare events

I am looking to model fraudulent cases using logistic regression. However there are tow different datasets which are available. I used to build my model on; it had 4% of fraud cases. My model on this ...
2
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2answers
125 views

Strange election results and probability of election fraud

Suppose an election is held for the leadership position in a major political party. Four candidates are running. After the election, the following results are announced: ...
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0answers
339 views

Analysis of PValues Matrix

in clinical environment I'm setting up a model to identify fraudolent behaviours from specific sites, calculating for each site some aspects that could lead to a p-value (this approach is based on a ...
2
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1answer
85 views

Benford's law: analyse individual variables or the entire dataset?

In his 1995 paper, Hill points out that random samples from random samples will usually give rise to data that satisfy Benford's law. He mentions a newspaper frontpage as an example where data may ...
5
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1answer
169 views

data mining methods/algorithms for fraud case

I recently got into a topic regarding fraudulent transactions. I am relatively new to data mining and just looking for some input for my case here. I started with a cluster analysis / anomaly ...
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2answers
1k views

How to improve a Fraud Classification Model?

I built a classification model (Logistic Regression) in order to classify data in Fraud or Not Fraud. This data is related with online CNP (Card Not Present) transactions and after choosing some ...
2
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2answers
822 views

Machine Learning problem - identifying fake fraudulent names

I have a dataset of fraudulent orders from some business. Each order has a bunch of features such as order_amount, address, state, city, phone_number, and name. Obviously a criminal would not be ...
1
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1answer
205 views

Machine learning to catch fraud

I work for a company that ships material (a couple of thousand shipments per day) around the world. In order to ship anything a customer has to declare the weight of a shipment and declare the ...
12
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2answers
5k views

Can p-values for Pearson's correlation test be computed just from correlation coefficient and sample size?

Background: I read one article where authors report Pearson correlation 0.754 from sample size 878. Resulting p-value for correlation test is "two star" significant (i.e. p < 0.01). However, I ...
3
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2answers
1k views

Medical Insurance Fraud Detection: Text analysis

I'm trying to analyse a dataset to detect fraudulent insurance claims. Unfortunately, other than basic demographics the rest of the claim is a free format OCR scanned text file made from documents ...
6
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1answer
785 views

Identifying fraudulent questionnaires

Questionaires are often used in social sciences. Many people try to complete them very quickly and very often they only "guess" answers. Is there any statistical technique or any research in this area,...
2
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2answers
3k views

How to apply clustering analysis to help identify criminal entities out from credit card usage data?

Let's say I have a ton of credit card usage data and have also some means to predict if a given transaction is fraudulent. Now I want to know what kind of criminal entities are behind these frauds. ...
8
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2answers
409 views

How is election fraud by ballot stuffing possible?

An NPR story on the upcoming Russian presidential election mentioned that 5% of polling sites would be equipped with new electronic ballot boxes that would reject attempts to submit multiple ballots. ...
4
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2answers
264 views

Election forensics using statistical methods in practice?

Are you aware of any examples of election forensics in practice? Or at least any applied research on real large-scale datasets (e.g. govermental elections)? Thanks.
2
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0answers
100 views

Reading recommendation on using statistical analysis in online fraud prevention

Can you please recommend good reads on statistical analysis related to online fraud detection and prevention of account abuse? Thank you.
6
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1answer
453 views

Any good reference books/material to help me build a txn level fraud detection model?

I am looking for a book/case study etc on how to build a fraud detection model at the transaction level. Something applied rather than theoretical would be really helpful.
23
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2answers
574 views

Statistical forensics: Benford and beyond

What broad methods are there to detect fraud, anomalies, fudging, etc. in scientific works produced by a third party? (I was motivated to ask this by the recent Marc Hauser affair.) Usually for ...