CAIIB ABM is one of the papers where understanding concepts is important, but knowing the right formulas can make numerical questions much easier to solve. Topics such as Statistics, Sampling, Correlation, Regression, Probability, Ratio Analysis, Break-Even Analysis, Vroom’s Theory and Provisioning Coverage Ratio require regular formula revision.
To help candidates with quick preparation, we have listed the CAIIB ABM important formulas in one place. Candidates can use this formula sheet for revision, numerical practice and last-minute preparation before the CAIIB ABM exam.
What are the important CAIIB ABM formulas?
The CAIIB ABM syllabus includes several numerical and formula-based topics, especially in Module A, Module B, Module C and Module D. Candidates should not only memorise the formulas but also understand where each formula is used. The most important areas include central tendency, dispersion, probability, correlation, regression, ratio analysis, break-even analysis and PCR.
- Central Tendency and Dispersion
- Sampling and Standard Error
- Correlation and Regression
- Time Series and Forecasting
- Probability
- Risk and Expected Loss
- Vroom’s Motivation Theory
- Compa Ratio
- Ratio Analysis
- Break-Even Analysis
- Margin of Safety
- Provisioning Coverage Ratio
Download the CAIIB ABM Formula Sheet PDF
Candidates can use the CAIIB ABM Formula Sheet PDF for quick revision of important formulas. The formula sheet covers the key numerical areas from the ABM syllabus and can be used along with CAIIB study material, previous year questions and mock tests.
What are the important Statistics formulas for CAIIB ABM?
Statistics is an important part of CAIIB ABM Module A and includes questions based on central tendency, dispersion, sampling, correlation, regression and probability. Candidates should be comfortable with both direct formula-based questions and numerical questions. The following formulas cover the major areas that should be revised before the exam.
| Topic | Formula |
|---|---|
| Class Width | Upper Class Interval − Lower Class Interval |
| Class Mark | (Lower Class Limit + Upper Class Limit) / 2 |
| Relative Frequency | Frequency / Total Frequency |
| Percentage Frequency | (Class Frequency / Total Frequency) × 100 |
| Frequency Density | Class Frequency / Width of Class |
What are the Sampling and Standard Error formulas?
Sampling is another important area of Module A. Questions can be asked on standard error, sample mean, finite population correction and the Central Limit Theorem. Candidates should understand the difference between infinite and finite population formulas because the finite population formula includes the correction factor.
- Important Sampling formulas
- Standard Error of Mean for Infinite Populationσₓ̄ = σ / √n
- Z-value for Sample Meanz = (x̄ − μ) / σₓ̄
- Standard Error for Finite Populationσₓ̄ = (σ / √n) × √[(N − n) / (N − 1)]
- Finite Population CorrectionFPC = √[(N − n) / (N − 1)]
- Where:
- σₓ̄ = Standard Error
- σ = Population Standard Deviation
- n = Sample Size
- N = Population Size
What are the Central Tendency formulas for CAIIB ABM?
Mean, Median, Mode, Geometric Mean and Harmonic Mean are important topics under Central Tendency. Questions can be based on both ungrouped and grouped data. Candidates should also remember the relationships between Arithmetic Mean, Geometric Mean and Harmonic Mean, as well as the empirical relationship between Mean, Median and Mode.
| Topic | Formula / Relation |
| Arithmetic Mean (Ungrouped Data) | x̄ = Σxᵢ / n |
| Arithmetic Mean (Grouped Data) | x̄ = Σ(fᵢxᵢ) / Σfᵢ |
| Continuous Grouped Data | Class mark or mid-value is used as x |
| Combined Mean | x̄ = (n₁x̄₁ + n₂x̄₂) / (n₁ + n₂) |
| Corrected Mean | Corrected Mean = Corrected Sum / Number of Observations |
| Geometric Mean (Raw Data) | GM = (x₁ × x₂ × … × xₙ)^(1/n) |
| Geometric Mean (Grouped Data) | GM = (x₁^f₁ × x₂^f₂ × … × xₖ^fₖ)^(1/n) |
| Geometric Mean | n = Σf |
| Harmonic Mean (Ungrouped Data) | HM = n / Σ(1/xᵢ) |
| Harmonic Mean (Grouped Data) | HM = n / Σ(fᵢ/xᵢ) |
| Relationship Between AM, GM and HM | AM > GM > HM |
| Relationship Between AM, GM and HM | AM × HM = (GM)² |
What are the Median, Quartile and Mode formulas?
Median, quartiles and mode are commonly used to measure the position of data. Candidates should understand how the formula changes for individual observations and grouped data.
| Topic | Formula / Details |
| Median (Odd Number of Observations) | Median = ((n + 1) / 2)th observation |
| Median (Even Number of Observations) | Median = Average of the middle observations |
| Median (Grouped Data) | Median = l₁ + [(l₂ − l₁)(N/2 − cf)] / f |
| Median: l₁ | Lower limit of median class |
| Median: l₂ | Upper limit of median class |
| Median: f | Frequency of median class |
| Median: cf | Cumulative frequency before median class |
| Median: N | Total frequency |
| First Quartile (Q₁) | Q₁ = l₁ + [(l₂ − l₁)(N/4 − CF)] / f |
| Second Quartile (Q₂) | Q₂ = Median |
| Third Quartile (Q₃) | Q₃ = l₁ + [(l₂ − l₁)(3N/4 − CF)] / f |
| Mode (Grouped Data) | Mode = l₁ + [(l₂ − l₁)(f₁ − f₀)] / [2f₁ − f₀ − f₂] |
| Mode: f₁ | Frequency of modal class |
| Mode: f₀ | Frequency of preceding class |
| Mode: f₂ | Frequency of succeeding class |
| Empirical Relationship | Mode = 3(Median) − 2(Mean) |
| Range | Range = Maximum − Minimum |
| Coefficient of Range | (Maximum − Minimum) / (Maximum + Minimum) |
| Quartile Deviation | QD = (Q₃ − Q₁) / 2 |
| Coefficient of QD | (Q₃ − Q₁) / (Q₃ + Q₁) |
| Interquartile Range (IQR) | IQR = Q₃ − Q₁ |
| Mean Deviation (Ungrouped Data) | MD(x̄) = Σ|xᵢ − x̄| / n |
| Mean Deviation (Grouped Data) | MD(x̄) = Σfᵢ|xᵢ − x̄| / Σfᵢ |
| Coefficient of Mean Deviation | Coefficient of MD = MD(Mean) / Mean |
| Standard Deviation (Ungrouped Data) | σ = √[Σ(x − x̄)² / n] |
| Standard Deviation Shortcut | σ = √[Σx²/n − (x̄)²] |
| Standard Deviation (Grouped Data) | σ = √[Σf(x − x̄)² / Σf] |
| Standard Deviation Shortcut (Grouped Data) | σ = √[Σfx²/N − (Σfx/N)²] |
| N | N = Σf |
| Coefficient of Variation | CV = (σ / x̄) × 100% |
What are the Correlation and Regression formulas?
Correlation and regression are important numerical topics in CAIIB ABM Module A. Candidates should understand the relationship between two variables and how regression equations are used for estimation.
| Topic | Formula / Details |
| Correlation Coefficient | r = cov(X,Y) / (σₓσᵧ) |
| Covariance | cov(X,Y) = (1/N)Σ(x − x̄)(y − ȳ) |
| Computational Correlation Formula | r = [NΣxy − (Σx)(Σy)] / {√[NΣx² − (Σx)²] × √[NΣy² − (Σy)²]} |
| Regression Equation | y = a + bx |
| b | Slope |
| a | y-intercept |
| Value of a | a = ȳ − bx̄ |
| Value of b | b = cov(X,Y) / σₓ² |
What are the Time Series formulas?
Time Series and Forecasting are also included in the Statistics portion of ABM. Candidates should revise the basic trend equation and the formulas used when coded values have a mean of zero. Important Time Series formulas
- ŷ = a + bx
- b = Σxy / Σx², when coded mean x = 0
- a = ȳ
What are the important Probability formulas for CAIIB ABM?
Probability is a scoring numerical area when the basic concepts and formulas are clear. Candidates should revise probability rules, permutation, combination, conditional probability, independent events and the binomial mode.
| Topic | Formula / Details |
| Basic Probability | P(A) = nA / n |
| Basic Probability | Probability = Favourable equally likely outcomes / Total equally likely outcomes |
| Permutation | nPr = n! / (n − r)! |
| Combination | nCr = n! / [r!(n − r)!] |
| Factorial | 0! = 1 |
| Factorial | 1! = 1 |
| Addition Rule | P(A ∪ B) = P(A) + P(B) − P(A ∩ B) |
| Addition Rule for Mutually Exclusive Events | P(A ∪ B) = P(A) + P(B) |
| Conditional Probability | P(A|B) = P(A ∩ B) / P(B) |
| Conditional Probability | P(A ∩ B) = P(A|B)P(B) |
| Conditional Probability | P(B|A) = P(A ∩ B) / P(A) |
| Conditional Probability | P(A ∩ B) = P(B|A)P(A) |
| Independent Events | P(A|B) = P(A) |
| Independent Events | P(B|A) = P(B) |
| Independent Events | P(A ∩ B) = P(A)P(B) |
| Complement Rule | P(Aᶜ) = 1 − P(A) |
| Multiplication Rule | P(A ∩ B) = P(A)P(B|A) |
| Multiplication Rule | P(A ∩ B) = P(B)P(A|B) |
| Multiplication Rule for Independent Events | P(A ∩ B) = P(A)P(B) |
| Probability for Three Events | P(A ∪ B ∪ C) = P(A) + P(B) + P(C) − P(A ∩ B) − P(B ∩ C) − P(A ∩ C) + P(A ∩ B ∩ C) |
What are the important Risk and Estimation formulas?
Risk and estimation formulas are useful for questions involving portfolio risk, expected loss and confidence intervals. Candidates should also revise point estimation and sample variance.
| Topic | Formula / Details |
| VaR at 95% Confidence | VaR = [Return of Portfolio − 1.65σ] × [Value of Portfolio] |
| VaR at 99% Confidence | VaR = [Return of Portfolio − 2.33σ] × [Value of Portfolio] |
| Z-value at 90% Confidence | 1.645 |
| Z-value at 95% Confidence | 1.96 |
| Z-value at 99% Confidence | 2.58 |
| Expected Loss | Expected Loss = PD × EAD × (1 − LGD) |
| Point Estimation | Sample mean x̄ is used as a point estimator of population mean μ |
| Sample Variance | s² = Σ(x − x̄)² / (n − 1) |
| Confidence Interval | x̄ ± 1.64σₓ̄ |
| Upper Confidence Limit | UCL = x̄ + 1.64σₓ̄ |
| Lower Confidence Limit | LCL = x̄ − 1.64σₓ̄ |
What are the important CAIIB ABM Module B formulas?
Module B includes concepts related to Human Resource Management. Vroom’s Expectancy Theory and Compa Ratio are important formula-based areas that candidates should revise.
| Topic | Formula / Details |
| Vroom’s Motivation Theory | Motivation = Expectancy × Instrumentality × Valence |
| Expectancy | Represents the relationship between effort and performance |
| Instrumentality | Represents the relationship between performance and reward or outcome |
| Valence | Represents the importance or value of the reward |
| Compa Ratio for Individual Employee | Compa Ratio = Employee’s Actual Salary / Midpoint of Salary Range × 100 |
| Group Compa Ratio | Group Compa Ratio = Average Actual Salary of Group / Midpoint of Salary Range × 100 |
What are the important Ratio Analysis formulas in CAIIB ABM?
Ratio Analysis is an important part of Module C Credit Management. Questions can be asked on liquidity, solvency, turnover, profitability and shareholder ratios. Candidates should learn the formula as well as understand what each ratio indicates.
| Ratio | Formula |
|---|---|
| Current Ratio | Current Assets / Current Liabilities |
| Quick Ratio | Quick Assets / Quick Liabilities |
| Cash Ratio | (Cash + Marketable Securities) / Current Liabilities |
| Debt Equity Ratio | Debt / Equity |
| DSCR | Earnings Available for Debt Service / [Interest + Instalments (Principal Component)] |
| Interest Coverage Ratio | EBIT / Interest |
| Preference Dividend Coverage Ratio | PAT / Preference Dividends |
| Equity Dividend Coverage Ratio | (PAT − Preference Dividend) / Equity Dividend |
| Fixed Assets to Long-Term Fund Ratio | Fixed Assets / Long-Term Funds |
| Proprietary Ratio | Proprietary Funds / Total Assets |
| Capital Turnover Ratio | Sales / Capital Employed |
| Fixed Assets Turnover Ratio | Sales / Fixed Assets |
| Working Capital Turnover Ratio | Sales / Working Capital |
| Debtors’ Turnover Ratio | Credit Sales / Average Accounts Receivable |
| Creditors’ Turnover Ratio | Credit Purchases / Average Accounts Payable |
| ROE | [PAT − Preference Dividend] / [Equity Share Capital + Reserves and Surplus − Fictitious Assets] |
| EPS | [Profit After Taxes − Preference Dividend] / Number of Equity Shares |
| DPS | Total Dividends Distributed to Equity Shareholders / Number of Equity Shares |
| P/E Ratio | Market Price per Share / Earnings per Share |
| ROCE | Return / Capital Employed × 100% |
| ROI | Profit Before Interest and Tax / Capital Employed × 100% |
What are the Capital Gearing and Proprietary Ratio formulas?
Capital structure ratios help in understanding the relationship between different sources of finance and the ownership position of a business. These formulas are useful for questions related to financial analysis and credit assessment.
| Topic | Formula / Details |
| Capital Gearing Ratio | Capital Gearing Ratio = [Preference Share Capital + Debentures + Long-term Loans] / [Equity Share Capital + Reserves and Surplus − Losses] |
| Alternative Capital Gearing Ratio | Capital Gearing Ratio = Fixed Income Bearing Securities / Non-Fixed Income Bearing Securities |
| Proprietary Ratio | Proprietary Ratio = Proprietary Funds / Total Assets |
| Proprietary Funds | Share Capital + Reserves and Surplus − Fictitious Assets |
What are the Inventory and Working Capital formulas?
Turnover ratios help measure how efficiently a business uses its assets and working capital. These formulas are relevant for financial analysis and credit-related questions in ABM.
| Topic | Formula / Details |
| Average Stock | Average Stock = 1/2 (Opening Stock + Closing Stock) |
| Raw Material Turnover Ratio | Raw Material Turnover Ratio = Raw Materials Consumed / Average Raw Materials Stock |
| Debtors’ Turnover Ratio | Debtors’ Turnover Ratio = Credit Sales / Average Accounts Receivable |
| Average Collection Period | Average Collection Period = Average Accounts Receivable / Average Daily Credit Sales |
| Average Collection Period (Alternative) | Average Collection Period = 365 / Debtors’ Turnover Ratio |
| Creditors’ Turnover Ratio | Creditors’ Turnover Ratio = Credit Purchases / Average Accounts Payable |
| Average Payment Period | Average Payment Period = Average Accounts Payable / Average Daily Credit Purchase |
| Average Payment Period (Alternative) | Average Payment Period = 365 / Creditors’ Turnover Ratio |
What are the important Break-Even Analysis formulas?
Break-Even Analysis is an important numerical topic under Credit Management. Candidates should understand fixed cost, variable cost, contribution and selling price before solving questions based on the break-even point.
- Break-Even Point
- BEP in Units = Fixed Costs / (Selling Price per Unit − Variable Cost per Unit)
- BEP in ₹ = Fixed Costs / Contribution Margin Ratio
- Contribution Margin Ratio
- CMR = (Selling Price − Variable Cost) / Selling Price
What are the Margin of Safety formulas?
Margin of Safety shows the difference between actual sales and break-even sales. It can be asked in both rupee and percentage form.
- Margin of Safety in ₹MOS = Actual Sales − Break-Even Sales
- Margin of Safety PercentageMOS% = [(Actual Sales − Break-Even Sales) / Actual Sales] × 100
What is the Provisioning Coverage Ratio formula for CAIIB ABM?
Provisioning Coverage Ratio, or PCR, is important for understanding provisioning against bad loans and credit risk. It is relevant to the credit management and compliance portions of the ABM syllabus. Candidates should remember both the formula and the meaning of the terms used in it.
- PCR = Total Provisions for NPAs / Gross NPAs × 100
- Where:
- Total Provisions for NPAs refers to provisions created for bad loans.
- Gross NPAs refers to the total value of NPAs.
How should you revise CAIIB ABM formulas?
Formula revision works best when it is combined with numerical practice. Instead of trying to memorise all formulas in one sitting, divide them according to modules and practise questions after each topic. Candidates should also use CAIIB previous year questions and mock tests to understand how these formulas are used in the examination.
- Revise the formula and understand each term used in it.
- Solve 2–3 questions based on the formula.
- Mark formulas that are difficult to remember.
- Revise important formulas again before attempting a mock test.
- Analyse mistakes after every numerical practice session.
- Give extra attention to Statistics, Probability, Ratio Analysis and Break-Even Analysis.
Which CAIIB ABM formulas should you revise first?
If you have limited time, start with the formulas that are most useful for numerical and application-based questions. Central Tendency, Standard Deviation, Correlation, Regression, Probability, Ratio Analysis, Break-Even Analysis and PCR should receive special attention. Vroom’s Theory and Compa Ratio should also be revised because they are comparatively short and easy to recall.
- Mean, Median and Mode
- Standard Deviation and Coefficient of Variation
- Correlation and Regression
- Probability
- Sampling and Standard Error
- Ratio Analysis
- Break-Even Point and Margin of Safety
- Vroom’s Motivation Theory
- Compa Ratio
- Provisioning Coverage Ratio
FAQs
Module A has several numerical topics, especially Statistics, Sampling, Correlation, Regression and Probability.
Yes, it helps candidates revise important formulas quickly before the examination.
Mean, Median, Mode, Standard Deviation, Variance, Correlation, Regression and Sampling formulas are important.
PCR = Total Provisions for NPAs / Gross NPAs × 100.
Motivation = Expectancy × Instrumentality × Valence.
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