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ACCA Strategic Professional · Strategic Business Leader · Finance transformation

Corvane Insurance uses a machine-learning model to forecast claim costs, and finance uses the output to set reserves. An internal review finds that the training data came largely from one age group, so forecasts for other groups are unreliable. Which issue should finance transformation governance address first?

Governance should first address data quality and bias in the training data. A model trained largely on one age group produces unreliable forecasts for others, so reserves based on it are unsafe. Speed, dashboards or reducing volume would not correct the unrepresentative inputs.

  1. AData quality and bias in the training data, which undermines reliability of the outputCorrect
  2. BInsufficient data velocity, because the model should process claims faster
  3. CLack of data visualisation, because dashboards would remove the unreliability
  4. DExcess data volume, because the model should use fewer records

Explanation

The problem is that unrepresentative training data creates biased, unreliable forecasts, so data quality and bias must be addressed through governance before relying on reserves. Speed, visualisation and volume do not fix unrepresentative inputs; more varied data would likely be needed rather than less.

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