Deployment of data analytics to fight fraud in organizations worldwide 2019

Published by
Petroc Taylor,
May 23, 2022
Exception reporting or anomaly detection are the most commonly deployed data analysis technologies in organizations for anti-fraud purposes, according to a global survey in 2019. Sixty-four percent of the respondents said that these technologies were currently in use in their companies, with a further eight percent expecting their organizations to adopt them in the next one or two years.

Data analysis techniques deployed to fight fraud in companies worldwide as of 2019

CharacteristicCurrently useExpect to adopt in next 1-2 years
Exception reporting/anomaly detection 64% 8%
Automated red flags/business rules 54% 18%
Data visualization 35% 12%
Predictive analytics/modeling 30% 22%
Link analysis/social network analysis 22% 13%
Text mining 18% 12%
Geographic data mapping 16% 10%
Artificial intelligence/machine learning 13% 25%
Emotional tone/sentiment analysis 7% 9%
Showing entries 1 to 9 (9 entries in total)
Created with Highcharts 7.2.2Share of respondents8%8%18%18%12%12%22%22%13%13%12%12%10%10%25%25%9%9%64%64%54%54%35%35%30%30%22%22%18%18%16%16%13%13%7%7%Currently useExpect to adopt in next 1-2 yearsException reporting/anomaly detectionAutomated red flags/business rulesData visualizationPredictive analytics/modelingLink analysis/social network analysisText miningGeographic data mappingArtificial intelligence/machine learningEmotional tone/sentiment analysis
0%5%10%15%20%25%30%35%40%45%50%55%60%65%70%75%

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Release date

June 2019

Region

Worldwide

Survey time period

February 2019

Number of respondents

1,055 respondents

Special properties

ACFE members

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