BIG DATA ANALYTICS FOR RISK AND
INSURANCE 2026 TEST PAPER SOLVED
QUESTIONS AND SOLUTIONS
◉ In link prediction, a model attempts to predict Answer: A pair of
instances.
◉ If a predictive model makes 60 percent positive predictions in a
situation in which without the model, only 40 percent of positive
predictions would be made by chance, which one of the following is
the model's leverage? Answer: 0.20
◉ Which one of the following measures only the positive results of a
model? Answer: Precision
◉ In the context of a predictive model, a true positive results when
the model Answer: Correctly predicts a positive
◉ Which one of the following is the term for the most similar
instances in a data model? Answer: Nearest neighbors
◉ A predictive model is applied to a clothing manufacturer's data of
1,000 employees, 50 of whom had workplace injuries in the past
,year. The table below shows how often the model correctly and
incorrectly predict for each employee "yes, will have an accident" or
"no, will not have an accident."
Predicted No+Predicted Yes=Total (1,000 Employees)
Actual No 945 5 950
Actual Yes 10 40 50
Based on the preceding number, these statements can be made:
There are 40 true positives (TP) for which the model correctly
predicted yes.
There are 945 true negatives (TN) for which the model correctly
predicted no.
There are 5 false positives (FP) for which the model incorrectly
predicted yes (and the actual answer is no).
There are 10 false negatives (FN) for which the model incorrectly
predicted no (and the actual answer is yes).
What is the accuracy of the workplace injury predictive model?
Answer: *PLEASE SEE QUESTION BELOW, VERY SIMILAR
.985
(TP + TN) ÷ (TP + TN + FP + FN); (40 + 945) ÷ (40 + 945 + 5 + 10) =
0.985
,◉ A predictive model is applied to a clothing manufacturer's data of
1,000 employees, 50 of whom had workplace injuries in the past
year. The table below shows how often the model correctly and
incorrectly predict for each employee "yes, will have an accident" or
"no, will not have an accident."
Predicted No+Predicted Yes=Total (1,000 Employees)
Actual No 945 5 950
Actual Yes 10 40 50
Based on the preceding number, these statements can be made:
There are 40 true positives (TP) for which the model correctly
predicted yes.
There are 945 true negatives (TN) for which the model correctly
predicted no.
There are 5 false positives (FP) for which the model incorrectly
predicted yes (and the actual answer is no).
There are 10 false negatives (FN) for which the model incorrectly
predicted no (and the actual answer is yes).
What is the F-score of the workplace injury predictive model?
Answer: *PLEASE SEE QUESTION ABOVE, VERY SIMILAR
.842
The recall of the workplace injury predictive model is calculated as
40 ÷ (40 + 10) = .80; The precision of the workplace injury
predictive model is calculated as 40 ÷ (40 + 5) = .889; The F-score
, formula is 2 × [(Precision × recall) ÷ Precision + recall)]; The
workplace injury predictive model's F-score is calculated as 2 ×
[(.889 × .80) ÷ (.889 + .80)] = .842
◉ When examining a model's results, insurance and risk
management professionals should defer to Answer: Their
professional experience.
◉ A predictive model was developed for Shelton Manufacturing to
determine the likelihood of current and future employees suffering
from hearing loss. The predictive model was applied to Shelton
Manufacturing data of 200 employees, 10 of whom developed
hearing loss in the past year. Based on the numbers shown in the
performance metric below, what is the accuracy of the hearing loss
predictive model?
Predicted No+Predicted Yes=Total (200 employees)
Actual No 178 12 190
Actual Yes 2 8 10 Answer: 0.93
The accuracy of the hearing loss predictive model is 0.93. The
following formula is used to measure accuracy (TP + TN) ÷ (TP + TN
+ FP + FN) (8 +178) ÷ (8 + 178 + 12 + 2) = 186/200 = 0.93
◉ Which one of the following statements is correct?
INSURANCE 2026 TEST PAPER SOLVED
QUESTIONS AND SOLUTIONS
◉ In link prediction, a model attempts to predict Answer: A pair of
instances.
◉ If a predictive model makes 60 percent positive predictions in a
situation in which without the model, only 40 percent of positive
predictions would be made by chance, which one of the following is
the model's leverage? Answer: 0.20
◉ Which one of the following measures only the positive results of a
model? Answer: Precision
◉ In the context of a predictive model, a true positive results when
the model Answer: Correctly predicts a positive
◉ Which one of the following is the term for the most similar
instances in a data model? Answer: Nearest neighbors
◉ A predictive model is applied to a clothing manufacturer's data of
1,000 employees, 50 of whom had workplace injuries in the past
,year. The table below shows how often the model correctly and
incorrectly predict for each employee "yes, will have an accident" or
"no, will not have an accident."
Predicted No+Predicted Yes=Total (1,000 Employees)
Actual No 945 5 950
Actual Yes 10 40 50
Based on the preceding number, these statements can be made:
There are 40 true positives (TP) for which the model correctly
predicted yes.
There are 945 true negatives (TN) for which the model correctly
predicted no.
There are 5 false positives (FP) for which the model incorrectly
predicted yes (and the actual answer is no).
There are 10 false negatives (FN) for which the model incorrectly
predicted no (and the actual answer is yes).
What is the accuracy of the workplace injury predictive model?
Answer: *PLEASE SEE QUESTION BELOW, VERY SIMILAR
.985
(TP + TN) ÷ (TP + TN + FP + FN); (40 + 945) ÷ (40 + 945 + 5 + 10) =
0.985
,◉ A predictive model is applied to a clothing manufacturer's data of
1,000 employees, 50 of whom had workplace injuries in the past
year. The table below shows how often the model correctly and
incorrectly predict for each employee "yes, will have an accident" or
"no, will not have an accident."
Predicted No+Predicted Yes=Total (1,000 Employees)
Actual No 945 5 950
Actual Yes 10 40 50
Based on the preceding number, these statements can be made:
There are 40 true positives (TP) for which the model correctly
predicted yes.
There are 945 true negatives (TN) for which the model correctly
predicted no.
There are 5 false positives (FP) for which the model incorrectly
predicted yes (and the actual answer is no).
There are 10 false negatives (FN) for which the model incorrectly
predicted no (and the actual answer is yes).
What is the F-score of the workplace injury predictive model?
Answer: *PLEASE SEE QUESTION ABOVE, VERY SIMILAR
.842
The recall of the workplace injury predictive model is calculated as
40 ÷ (40 + 10) = .80; The precision of the workplace injury
predictive model is calculated as 40 ÷ (40 + 5) = .889; The F-score
, formula is 2 × [(Precision × recall) ÷ Precision + recall)]; The
workplace injury predictive model's F-score is calculated as 2 ×
[(.889 × .80) ÷ (.889 + .80)] = .842
◉ When examining a model's results, insurance and risk
management professionals should defer to Answer: Their
professional experience.
◉ A predictive model was developed for Shelton Manufacturing to
determine the likelihood of current and future employees suffering
from hearing loss. The predictive model was applied to Shelton
Manufacturing data of 200 employees, 10 of whom developed
hearing loss in the past year. Based on the numbers shown in the
performance metric below, what is the accuracy of the hearing loss
predictive model?
Predicted No+Predicted Yes=Total (200 employees)
Actual No 178 12 190
Actual Yes 2 8 10 Answer: 0.93
The accuracy of the hearing loss predictive model is 0.93. The
following formula is used to measure accuracy (TP + TN) ÷ (TP + TN
+ FP + FN) (8 +178) ÷ (8 + 178 + 12 + 2) = 186/200 = 0.93
◉ Which one of the following statements is correct?
