Fraud Investigations & the Future

  • Reduced exposure to fraudulent activities
  • Reduced costs associated with fraud
  • Exposing vulnerable employees at risk of fraud
  • Improves the results of the organization
  • Trust and confidence of the shareholders and customers

Benefits of Fraud Analytics

Sampling

Ad-Hoc

Repetitive or Continuous Analysis

Analytics Techniques

  • Calculate statistical parameters to find out values that exceed averages of standard deviation.
  • Look at high and low values and find out the anomalies there. Such anomalies are often indicators of fraud
  • Classify the data — group your data and transactions based on specific factors like geographical area.

Benford’s Law

Implementing Data Analytics for Fraud Detection

Perform SWOT

Build a dedicated fraud management team

Build or buy option

Clean data

Setting the threshold

--

--

--

Love podcasts or audiobooks? Learn on the go with our new app.

Recommended from Medium

CraftNext — Recommending New Beers to Enjoy

Messy, initial dataframe

The 7 Steps of Machine Learning

Introduction to Marketing Mix Modeling in Python

Banalytics #9

Where to find Datasets about Guatemala (the good ones)

High Hive for telematics in B2B insurance

How to Draft Players for Sport with Machine Learning and AI

Lessons from a real Machine Learning project, part 1: from Jupyter to Luigi

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Hello team at TBCA

Hello team at TBCA

More from Medium

Save Time And Money From The Coin Toss Accuracy Of Delivery Time Estimation Sessions

The Importance of Data Protection and the Five Major Areas Where Companies are at Risk

Euro 2020 Final: A masterclass on MES selection

Decentralized decision-making: Central command vs mission command

Vladimir Putin with Shoygu looking at something through binoculars.