Fraud Detection with Transactional Data

FRAUD DETECTION WITH TRANSACTIONAL DATA

CASE STUDY

Organisation for Security and Co-operation in Europe

The OSCE stands for the Organization for Security and Co-operation in Europe. With 57 States from Europe, Central Asia and North America, the OSCE is the world’s largest regional security organisation.

OSCE believed they may be facing some fraudulent activity with their organisation.

At ML Sense, we took some simple steps to detect as many instances of fraud as possible in OSCE’s transactional data.

Analyse

We analysed their HR, accounts, employee salaries and other transactional data.
This was millions of rows of data.

Dashboards

We created dashboards that allow stakeholders to extract actionable insights.

Machine Learning

We applied machine learning techniques to find fraudulent activity.

Flagged Accounts

We flagged accounts that required further investigation.

Results

As a result, OSCE was quickly able to investigate the majority of the fraudulent activity in their transactional data.
This helped them take the necessary steps to avoid future cases of fraud and malicious activities.

@MLSenseAI

ML Sense

MLSenseAI

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