CPA Practical Paper




Extract from the Competence Framework

Use information technology to support decision making through business analytics. Demonstrate digital competency in preparation and analysis of financial statements, simulation, forecasting and related areas and appreciate the provisions of the data protection Act.



This paper is intended to equip the candidate with competencies to use information technology to support decision making through business analytics in areas such as analysis of financial statements, forecasting and other related areas in accounting. .



A candidate who passes this paper should be able to:

  • Prepare and analyse financial statements
  • Estimate costs and do costing for products
  • Carry out breakeven analysis
  • Prepare various budgets and carry out variance analysis
  • Compute taxes for individuals and companies
  • Demonstrate knowledge of financial mathematics
  • Evaluate Long term capital projects and advise on their viability
  • Apply an analytical mindset to decision making
  • Understand the fundamental principles that underlie financial data visualization
  • Communicate analysis of results through industry standard frameworks for effective decision making
  • Understand and apply the provisions of the Kenya Data Protection Act


The course requires knowledge of prior areas of accounting; Financial Accounting and reporting, Management Accounting, Tax and Financial Management, with knowledge of excel..



Financial Accounting and Reporting

  • Prepare Financial Statements of a,
  • Sole trader,
  • Partnership
  • Company (with basic adjustments)
  • Group with a single subsidiary and associates/joint ventures


The financial statements include the statement of profit or loss, other comprehensive incomes, statement of financial position and a statement of cash flows.

1.2    Analyse Financial Statements

  • Compute financial ratios from a given set of financial statements
  • Prepare common Size financial statements
  • Carryout trend analysis and cross-sectional analysis
  • Prepare forecast financial statements given some minimal assumptions.
  • Carry out sensitivity and scenario analysis for the above activities
  • Use of relevant graphs and charts to aid in the analysis.


Financial Predictive Modelling

  • Prepare forecast financial statements with an outline of underlying assumptions.
  • Carry out sensitivity and scenario analysis for the above activities
  • Understand the core regression principles and regression output interpretation
  • Learn financial models optimization
  • Conduct financial time series modelling


Accounting Data visualization

  • Demonstrate Data Visualization Building Blocks
  • Build Operational and Strategic Dashboards for KPI’s and Analytics Dashboards for trends analysis


Management Accounting

  • Costing Estimation and Costing products
  • Derive the cost function using the High-Low and Regression methods
  • Estimate costs using the derived cost functions of High-Low and Regression Method
  • Estimate costs of products (goods and services) and their prices
  • Carry out sensitivity and scenario analysis for different cost estimates and prices


Break-even analysis

  • Establish the breakeven levels by computation and by use of graphs
  • Establish the target revenues and target profits and margins of safety
  • Carry out sensitivity and scenario analysis for various inputs of the breakeven analysis



  • Prepare various types of budgets for a manufacturing entity from production budget, material usage and procurement budget, labour budgets and other overheads.
  • Prepare a profit or loss budget and a cash budget.
  • Prepare a flexible budget
  • Compute variances and comment on causes of the variances.



  • Computing Tax Payable
  • Compute Tax Payable by an individual (Employee, Sole Trader and a Partner)
  • Compute Corporation Tax for a company.
  • Prepare Wear and Tear Deduction schedules


Financial Management

Financial Mathematics

  • Establish the Present value and Future value of a single amount or series of cash flows.
  • Determine the interest rates given present values or future values and time period.
  • Prepare the Loan Amortization Schedule
  • Application of calculus in minimizing cost and maximizing of returns
  • Prepare dashboards and create friendly data visualization
  • Demonstrate the use of correlation to describe relationship between two or more variables


Evaluating Projects using different techniques

  • Return on Investment (Accounting Rate of Return)
  • Payback Period and Discounted Payback Period.
  • Net Present Value
  • Internal Rate of Return
  • Profitability Index
  • Risk Management in Project Evaluation


Risk Management in project evaluation and Data Act

  • Sensitivity analysis
  • Scenario analysis
  • Key provisions of the Kenya Data Protection Act 2019



KASNEB reading list for Business and Data Analytics

1. Business Intelligence Guidebook: From Data Integration to Analytics Rick Sherman 1   2015
2. Successful Business Intelligence: Unlock The Value Of BI & Big Data Cindi Howson 2   2016
3. Data Science for Business Provost, F. and T. Fawcett 1   2013
4. Big Data and Machine Learning in Quantitative Investments Guida, T 1   2019






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