Entry level by KASNEB
Areas Covered: Business Mathematics, Business Environment, Fundamentals of Accounting, Fundamentals of Management, Principles of Entrepreneurship, Introduction to Business CommunicationLevel: Mid-level qualification by KASNEB
Areas Covered: Financial Accounting, Business Law, Economics, Principles of Taxation, Cost Accounting, Management Accounting, Auditing Financial ManagementFoundation Level
the first of three levels in the KASNEB CPA program. It provides foundational knowledge in accounting and finance, preparing students for the intermediate and advanced levels. The level consists of six papers: Financial Accounting, Communication Skills, Introduction to Law and Governance, Economics, Quantitative Analysis, and Information Communication Technology.Advanced Level
This is the final section of the CPA. It comprises compulsory and optional specialization papers, requiring candidates to take a minimum of five and a maximum of six papers, including at least one compulsory paper and possibly a selective paper or two. Key papers include Advanced Taxation, Advanced Auditing and Assurance, Advanced Management Accounting, Advanced Public Financial Management, Advanced Financial Reporting, and Leadership and Management.Intermediate Level
This level builds upon the Foundation Level by delving deeper into core accounting and financial subjects. This level includes compulsory subjects like Company Law, Financial Management, and Financial Reporting and Analysis, along with elective subjects such as Auditing and Assurance, Management Accounting, and Public Finance and Taxation. The aim is to equip candidates with advanced skills for managing financial resources and navigating complex regulatory environments.is a KASNEB (Kenyan) professional qualification focusing on using data analytics to support decision-making and improve business processes, particularly in areas like financial statement analysis, forecasting, and management accounting. The exam is a computer-based, practical paper that tests proficiency in tools like Microsoft Excel and potentially R, requiring candidates to apply data analytics techniques to financial data, present insights, and manage large datasets.