By: Bart Baesens, Seppe vanden Broucke
This QA first appeared in Data Science Briefings, the DataMiningApps newsletter as a “Free Tweet Consulting Experience” — where we answer a data science or analytics question of 140 characters maximum. Also want to submit your question? Just Tweet us @DataMiningApps. Want to remain anonymous? Then send us a direct message and we’ll keep all your details private. Subscribe now for free if you want to be the first to receive our articles and stay up to data on data science news, or follow us @DataMiningApps.
You asked: What does break point analysis mean in the context of fraud detection?
Our answer:
Break point analysis is an intra-account fraud detection method. A break point indicates a sudden change in account behavior which merits further inspection. The method starts from defining a fixed time window. This time window is then split into an old and new part. The old part represents the local model or profile against which the new observations will be compared. E.g., in (Bolton and Hand, 2002), the time window was set to 24 transactions whereby 20 transactions made up the local model, and 4 transactions were used for testing. A Student’s t-test can be used to compare the averages of the new and old parts. Observations can then be ranked according to their value of the t-statistic. This is illustrated in the figure below.
 |
- Bolton, R. J., & Hand, D. J. (2002). Statistical Fraud Detection: A Review. Statistical Science, 17(3), 235–249.
