Question 1
XYZ Inc. has quick assets of ₹ 5,50,000 and current liabilities of ₹ 2,50,000. The company purchased ₹ 85,500 in inventory on credit. After the purchase, the quick ratio would be
1.6
2.5
2.0
2.2

The IIT Madras BS Financial Forensics (Financial Forensics) Quiz 2 paper sat on 6 Aug 2023, in the May 2023 term: 25 questions for 25 marks in 120 minutes. Every question is below with its answer. Take it as a timed mock test to be marked, or read it through first.
XYZ Inc. has quick assets of ₹ 5,50,000 and current liabilities of ₹ 2,50,000. The company purchased ₹ 85,500 in inventory on credit. After the purchase, the quick ratio would be
1.6
2.5
2.0
2.2
Correct answer
1.6
An increasing inventory turnover ratio
Indicates a shorter time span between the purchase and sale of inventory
Indicates a longer time span between the ordering and receiving of inventory
Indicates a shorter time span between the ordering and receiving of inventory
Indicates a longer time span between the purchase and sale of inventory
Correct answer
Indicates a shorter time span between the purchase and sale of inventory
A decrease in selling and administrative expenses would impact which of the following ratio?
Fixed asset turnover ratio
Debt-to-equity ratio
Current ratio
Times interest earned ratio
Correct answer
Times interest earned ratio
Which ratio is reported on the financial statement or in the notes to the statements?
Basic Earnings per share ratio
Diluted Earnings per share ratio
Both basic and diluted Earnings Per share ratio
Net profit ratio
Correct answer
Both basic and diluted Earnings Per share ratio
Which of the following transactions would usually cause accounts payable turnover to increase?
Payment of cash to a supplier for merchandise previously purchased on credit.
Collection of cash from a customer.
Purchase of merchandise on credit.
None of these
Correct answer
Payment of cash to a supplier for merchandise previously purchased on credit.
You are considering two independent projects that have differing requirements. Project A has a required return of 12 percent compared to Project B’s required return of 13.5 percent. Project A costs ₹75,000 and has cash flows of ₹21,000, ₹49,000, and ₹12,000 for Years 1 to 3, respectively. Project B has an initial cost of ₹70,000 and cash flows of ₹15,000, ₹18,000, and ₹41,000 for Years 1 to 3, respectively. Based on the NPV, you should:
accept both Project A and Project B.
accept Project A and reject Project B.
accept Project B and reject Project A.
reject both Project A and Project B.
Correct answer
reject both Project A and Project B.
Your company has a project available with the following cash flows:
| Year | Cash Flow |
|---|---|
| 0 | −₹81,600 |
| 1 | 21,250 |
| 2 | 24,500 |
| 3 | 30,300 |
| 4 | 25,750 |
| 5 | 19,300 |
If the required return is 13 percent, should the project be accepted based on the IRR?
Yes, because the IRR is 15.43 percent.
Yes, because the IRR is 14.82 percent.
No, because the IRR is 16.05 percent.
No, because the IRR is 14.82 percent.
Correct answer
Yes, because the IRR is 14.82 percent.
Scott has been offered an employment contract for ten years at a starting salary of ₹ 65,000 with guaranteed annual raises of 5 percent. What is the current value of this offer at a discount rate of 7 percent?
₹ 638,724.17
₹ 602,409.91
₹ 558,845.85
₹ 630,500.00
Correct answer
₹ 558,845.85
A trust has been established to fund scholarships in perpetuity. The next annual distribution will be ₹ 1,200 and future payments will increase by 3 percent per year. What is the value of this trust at a discount rate of 7.4 percent?
₹ 17,189.19
₹ 19,960.00
₹ 27,272.73
₹ 24,609.11
Correct answer
₹ 27,272.73
An insurance settlement offer includes annual payments of ₹ 36,000, ₹ 42,000, and ₹ 50,000 over the next three years, respectively, with the first payment being made one year from today. What is the minimum amount you should accept today as a lump sum settlement if your discount rate is 7 percent?
₹ 111,144.18
₹ 105,000.10
₹ 118,924.27
₹ 114,556.88
Correct answer
₹ 111,144.18
A stock with a beta of zero would be expected to have a rate of return equal to:
Risk-free rate.
Market rate of return.
Market risk premium
Zero.
Correct answer
Risk-free rate.
The excess return earned by an asset that has a beta of 1.0 over that earned by a risk-free asset is referred to as the:
Market rate of return.
Market risk premium.
Total return.
Real rate of return.
Correct answer
Market risk premium.
Stock A has an expected return of 12 percent and a variance of 0.0203. The market has an expected return of 11 percent and a variance of 0.0093. What is the beta of Stock A if the covariance of Stock A with the market is 0.0137?
0.68
1.55
1.47
1.32
Correct answer
1.47
The risk-free rate of return is 3.68 percent and the market risk premium is 7.84 percent. What is the expected rate of return on a stock with a beta of 1.32?
9.17 percent
13.12 percent
14.03 percent
14.36 percent
Correct answer
14.03 percent
Phil's Carvings wants to have a weighted average cost of capital of 9.5 percent. The firm has an after tax cost of debt of 6.5 percent and a cost of equity of 12.75 percent. What debt-equity ratio is needed for the firm to achieve its targeted weighted average cost of capital?
0.84
0.92
1.08
0.76
Correct answer
1.08
What is the KS of the below table?
| Decile | Non Event | Event | % Non-Event | % Event | Cum % Event | Cum % Non Event | KS |
|---|---|---|---|---|---|---|---|
| 1 | 51 | 49 | 5.7 | 49 | 49 | 5.7 | 43.3 |
| 2 | 81 | 19 | 9 | 19 | 68 | 14.7 | 53.3 |
| 3 | 86 | 14 | 9.6 | 14 | 82 | 24.2 | 57.8 |
| 4 | 90 | 10 | 10 | 10 | 92 | 34.2 | 57.8 |
| 5 | 95 | 5 | 10.6 | 5 | 97 | 44.8 | 52.2 |
| 6 | 99 | 1 | 11 | 1 | 98 | 55.8 | 42.2 |
| 7 | 99 | 1 | 11 | 1 | 99 | 66.8 | 32.2 |
| 8 | 99 | 1 | 11 | 1 | 100 | 77.8 | 22.2 |
| 9 | 100 | 0 | 11.1 | 0 | 100 | 88.9 | 11.1 |
| 10 | 100 | 0 | 11.1 | 0 | 100 | 100 | 0 |
43.3
53.3
37.2
57.8
52.2
Correct answer
57.8
What is the capture rate at the top 5 bins from the below report?
| decile | min_prob | max_prob | avg_prob | cnt_cust | cnt_resp | cnt_non_resp | rrate | cum_cust | cum_resp | cum_non_resp | cum_cust_pct | cum_resp_pct | cum_non_resp_pct | KS | Lift | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 9 | 9 | 0.092405 | 0.279624 | 0.135947 | 993.0 | 146.0 | 847.0 | 14.70 | 993.0 | 146.0 | 847.0 | 9.93 | 31.74 | 8.88 | 22.86 | 3.20 |
| 8 | 8 | 0.067002 | 0.092342 | 0.078040 | 1004.0 | 65.0 | 939.0 | 6.47 | 1997.0 | 211.0 | 1786.0 | 19.97 | 45.87 | 18.72 | 27.15 | 2.30 |
| 7 | 7 | 0.052288 | 0.066914 | 0.059026 | 1002.0 | 51.0 | 951.0 | 5.09 | 2999.0 | 262.0 | 2737.0 | 29.99 | 56.96 | 28.69 | 28.27 | 1.90 |
| 6 | 6 | 0.042523 | 0.052263 | 0.047149 | 1001.0 | 49.0 | 952.0 | 4.90 | 4000.0 | 311.0 | 3689.0 | 40.00 | 67.61 | 38.67 | 28.94 | 1.69 |
| 5 | 5 | 0.034578 | 0.042492 | 0.038425 | 996.0 | 36.0 | 960.0 | 3.61 | 4996.0 | 347.0 | 4649.0 | 49.96 | 75.43 | 48.73 | 26.70 | 1.51 |
| 4 | 4 | 0.027969 | 0.034553 | 0.031175 | 1002.0 | 37.0 | 965.0 | 3.69 | 5998.0 | 384.0 | 5614.0 | 59.98 | 83.48 | 58.85 | 24.63 | 1.39 |
| 3 | 3 | 0.022718 | 0.027931 | 0.025235 | 1001.0 | 32.0 | 969.0 | 3.20 | 6999.0 | 416.0 | 6583.0 | 69.99 | 90.43 | 69.00 | 21.43 | 1.29 |
| 2 | 2 | 0.017885 | 0.022694 | 0.020290 | 998.0 | 18.0 | 980.0 | 1.80 | 7997.0 | 434.0 | 7563.0 | 79.97 | 94.35 | 79.28 | 15.07 | 1.18 |
| 1 | 1 | 0.012894 | 0.017842 | 0.015400 | 1002.0 | 16.0 | 986.0 | 1.60 | 8999.0 | 450.0 | 8549.0 | 89.99 | 97.83 | 89.61 | 8.22 | 1.09 |
| 0 | 0 | 0.003341 | 0.012885 | 0.009852 | 1001.0 | 10.0 | 991.0 | 1.00 | 10000.0 | 460.0 | 9540.0 | 100.00 | 100.00 | 100.00 | 0.00 | 1.00 |
31.74%
45.87%
56.96%
67.61%
75.43%
Correct answer
75.43%
Which of the following statements regarding the Weight of Evidence (WoE) technique is correct?
WoE is primarily used to measure the accuracy of a statistical model.
WoE is a feature engineering technique that assigns numerical values to categorical variables.
WoE is a supervised learning algorithm used for binary classification tasks.
WoE is only applicable to linear regression models.
Correct answer
WoE is a feature engineering technique that assigns numerical values to categorical variables.
What is the rollback rate for 60-89 DPD after 18 MOB?
80.27%
75.46%
74.47%
46.01%
29.63%
Correct answer
74.47%
In the context of credit scoring and loan approval, what does "Reject Inferencing" refer to?
It is a statistical technique used to reject outliers in a dataset.
Reject Inferencing is a method to assess the probability of loan default for rejected loan applications.
It is a process of rejecting loan applications without any specific criteria.
Reject Inferencing is a term used for rejecting a hypothesis during hypothesis testing.
Correct answer
Reject Inferencing is a method to assess the probability of loan default for rejected loan applications.
Consider a credit card company analyzing its customer base to assess the risk of default on credit card payments. The company wants to use the WoE technique to transform the "Income Level" feature, which is a categorical variable with values "Low," "Medium," and "High," based on the observed relationship with the target variable (default or non-default). After analyzing historical data, the company finds that the WoE values for each income level are as follows:
● WoE for "Low" income level = -0.75
● WoE for "Medium" income level = 0.15
● WoE for "High" income level = -0.90
What does the negative WoE value for the "High" income level suggest in the context of credit risk modeling?
Customers with a high income level are less likely to default on credit card payments.
Customers with a high income level are more likely to default on credit card payments.
The "High" income level has no significant impact on the risk of default.
WoE cannot be interpreted for categorical variables with more than two levels.
Correct answer
Customers with a high income level are more likely to default on credit card payments.
In credit risk analysis, the "roll forward rate" is used to:
Calculate the total outstanding debt of a borrower over time.
Assess the likelihood of a borrower defaulting on a loan in the future.
Measure the percentage change in credit scores for borrowers over a specific period.
Monitor the migration of borrowers between different credit risk categories over time.
Correct answer
Assess the likelihood of a borrower defaulting on a loan in the future.
Suppose a bank is analyzing the credit risk of a group of borrowers over a period of four quarters (Q1, Q2, Q3, and Q4). The bank uses the "roll forward rate" to assess the probability of default for these borrowers during this time. The following table shows the number of borrowers in different credit risk categories:
| Quarter | Low Credit Risk | Moderate Credit Risk | High Credit Risk |
|---|---|---|---|
| Q1 | 3000 | 1500 | 500 |
| Q2 | 2800 | 1600 | 400 |
| Q3 | 2600 | 1700 | 300 |
| Q4 | 2400 | 1800 | 200 |
What does the roll forward rate indicate about the credit risk migration of borrowers from Q1 to Q4?
Borrowers with high credit risk in Q1 significantly improved their credit risk status by Q4.
The credit risk status of borrowers remained stable with no significant changes over the quarters.
Borrowers with low credit risk in Q1 are likely to have a higher probability of default by Q4.
The number of borrowers in each credit risk category decreased steadily over the quarters.
Correct answer
Borrowers with high credit risk in Q1 significantly improved their credit risk status by Q4.
A credit analyst is developing a credit risk model for a bank. The analyst is evaluating the "Credit Score" feature, which represents the creditworthiness of borrowers. The analyst categorizes borrowers into four groups based on their credit scores and examines the number of good and bad loans in each group:
Calculate the Weight of Evidence (WoE) for the "Credit Score" feature for the "701-850" range.
1.892
2.303
2.778
3.171
Correct answer
3.171
In credit risk modeling, the Weight of Evidence (WoE) is used to:
Measure the accuracy of a predictive model.
Assess the total amount of information in a dataset.
Evaluate the predictive power of a feature in distinguishing between default and non-default cases.
Calculate the proportion of good loans to bad loans in a dataset.
Correct answer
Evaluate the predictive power of a feature in distinguishing between default and non-default cases.