Under SR 11-7, what distinguishes a 'model' from a 'tool' for purposes of model risk management scope?
Select an answer to reveal the explanation.
Short Explanation
Here's the deal — you're right when you focus on the quantitative method that applies expert judgment or statistical techniques to turn inputs into decision-informing outputs. SR 11-7 can cover simple spreadsheets if they do that, so don't get tripped up by machine-learning or approval rules.
Full Explanation
The correct distinction is that models involve quantitative methods that apply expert judgment or statistical techniques to produce outputs that inform decisions. SR 11-7 broadly defines a model as a quantitative method, system, or approach that applies statistical, economic, financial, or mathematical theories or techniques to transform inputs into quantitative estimates used for decision-making, which can include simple spreadsheets when they meet this criterion. The machine-learning requirement with spreadsheet exclusion is incorrect because SR 11-7 predates modern ML and applies to traditional quantitative models as well. The more-than-1,000-parameters threshold has no basis in SR 11-7. The regulatory-authority approval requirement is incorrect because regulatory pre-approval is not required for model scope inclusion.