The Cost of Poor Customer Data

 Unity Technologies: Bad data undermines algorithmic decision-making

In early 2022, Unity Technologies disclosed that inaccurate data ingestion had corrupted datasets used to train advertising-related machine learning models. Faulty data sources introduced errors into data pipelines supporting predictive targeting and bidding algorithms. Unity reported approximately USD 110 million in lost revenue tied to underperforming models, delayed initiatives and the cost of retraining affected datasets.

Equifax: Inaccurate credit scores affect lending outcomes

In 2022, Equifax issued inaccurate credit scores to millions of consumers due to incorrect data values generated by a legacy system. In some cases, errors were significant enough to influence lending decisions, exposing both consumers and lenders to financial risk.

Beyond the blow to the company’s reputation, the fallout included regulatory scrutiny, class-action litigation and a USD 725,000 settlement—one of several penalties the company faced for credit reporting and dispute-handling failures.

Samsung Securities: Human error triggers market disruption

In 2018, Samsung Securities processed an invalid data entry while attempting to issue employee dividends, mistakenly triggering the issuance of billions of duplicate shares. Insufficient validation and human-in-the-loop controls allowed the erroneous data values to reach downstream trading systems.

Although the issue was identified within minutes, the consequences were severe: market disruption, regulatory penalties, leadership resignations and an estimated hundreds of millions of dollars in market value loss.

 The Cost of Poor Customer Data


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