AI FOR CORPORATE FINANCE TRAINING COURSE

Course Introduction

AI for Corporate Finance Training Course is a comprehensive and practical professional programme designed to equip finance professionals, accountants, financial analysts, treasury specialists, CFOs, finance managers, investment professionals, auditors, and business leaders with advanced skills in applying Artificial Intelligence (AI), machine learning, predictive analytics, generative AI, automation, and financial data analytics to corporate finance. The programme explores how AI can transform financial planning and analysis (FP&A), financial forecasting, cash flow management, treasury management, budgeting, investment analysis, working capital management, financial reporting, risk management, and strategic decision-making. Participants will learn how to use AI-powered technologies to improve the speed, accuracy, efficiency, and quality of corporate financial processes.
The training provides practical coverage of AI-enabled financial forecasting, predictive financial modelling, scenario analysis, budgeting automation, variance analysis, cash flow forecasting, working capital optimization, liquidity management, credit risk analytics, investment analysis, and financial performance management. Participants will examine how organizations can combine accounting data, ERP data, banking information, market information, operational data, and external economic indicators to generate actionable financial insights. The programme also introduces generative AI for financial analysis, automated reporting, financial research, management commentary, data interpretation, and finance productivity while emphasizing appropriate human review and governance.
Participants will develop practical capabilities in identifying AI use cases, preparing finance data for AI applications, designing AI-assisted financial models, interpreting predictive analytics, automating repetitive finance activities, and building AI-supported dashboards and decision-support systems. The programme addresses AI governance, data quality, privacy, cybersecurity, model risk, bias, explainability, human oversight, and responsible AI adoption in corporate finance. Relevant general case studies will demonstrate how organizations can use AI to improve forecasting accuracy, optimize working capital, identify financial anomalies, strengthen treasury decisions, accelerate reporting, and improve strategic financial planning.
By the end of the training, participants will be able to evaluate, design, and apply AI-enabled corporate finance solutions that support better forecasting, financial analysis, risk management, liquidity planning, investment decisions, and strategic performance management. The programme is suitable for corporations, banks, investment companies, government institutions, NGOs, development organizations, manufacturing companies, technology companies, and other organizations seeking to transform finance through AI and advanced analytics. The course can be customized according to the organization's financial systems, ERP environment, data maturity, AI strategy, reporting requirements, and corporate finance priorities.

Course Objectives

1. Understand the fundamentals of Artificial Intelligence and its applications in corporate finance.
2. Identify high-value AI use cases across financial planning, analysis, treasury, accounting, and financial management.
3. Apply AI and machine learning techniques to financial forecasting and predictive financial analysis.
4. Improve budgeting, scenario planning, variance analysis, and financial modelling using AI.
5. Apply AI to cash flow forecasting, liquidity management, and working capital optimization.
6. Use generative AI to support financial reporting, research, analysis, and management decision-making.
7. Apply AI-powered analytics to identify financial risks, anomalies, fraud indicators, and emerging trends.
8. Evaluate AI tools, data requirements, model outputs, risks, governance, and implementation considerations.
9. Develop responsible AI practices covering data privacy, cybersecurity, model governance, human oversight, and explainability.
10. Develop an AI-enabled corporate finance transformation roadmap aligned with organizational strategy and financial objectives.

Organization Benefits

1. Improves financial forecasting accuracy and planning effectiveness.
2. Accelerates financial analysis and management reporting.
3. Reduces manual and repetitive finance activities through intelligent automation.
4. Strengthens cash flow forecasting and liquidity management.
5. Improves working capital management and financial performance.
6. Enables faster identification of financial risks, anomalies, and emerging trends.
7. Enhances budgeting, scenario planning, and strategic financial modelling.
8. Supports data-driven investment, treasury, and corporate finance decisions.
9. Improves finance team productivity through AI-powered tools and workflows.
10. Supports digital finance transformation and development of an AI-enabled finance function.

Target Participants

The course is designed for Chief Financial Officers (CFOs), Finance Directors, Finance Managers, Financial Controllers, Accountants, Management Accountants, Financial Analysts, FP&A Professionals, Treasury Managers, Investment Analysts, Risk Managers, Auditors, Internal Auditors, Corporate Finance Professionals, Business Analysts, Data Analysts, ERP Professionals, Strategy Managers, and senior executives responsible for financial planning, financial management, investment, risk, treasury, reporting, and digital transformation.

Course Outline

Module 1: AI Foundations for Corporate Finance

1. Introduction to Artificial Intelligence, machine learning, generative AI, predictive analytics, and intelligent automation.
2. AI applications across corporate finance, accounting, FP&A, treasury, investment, risk, and financial reporting.
3. Finance data requirements including structured data, unstructured data, ERP data, accounting data, market data, and economic indicators.
4. AI-enabled financial decision-making, intelligent workflows, automation, and finance productivity.
5. Identifying and prioritizing AI use cases based on business value, feasibility, risk, and data readiness.
6. General Case Study: Developing an AI opportunity map for a corporate finance department covering forecasting, reporting, treasury, working capital, budgeting, and financial analysis.

Module 2: AI-Powered Financial Planning, Forecasting and Budgeting

1. AI-powered financial forecasting, predictive modelling, trend analysis, and financial scenario planning.
2. Machine learning applications in revenue forecasting, expense forecasting, profitability analysis, and cash flow prediction.
3. AI-assisted budgeting, rolling forecasts, driver-based planning, and dynamic financial modelling.
4. Automated variance analysis, budget-versus-actual analysis, financial performance interpretation, and management commentary.
5. Scenario modelling using economic indicators, market variables, operational drivers, and historical financial data.
6. General Case Study: Developing an AI-supported FP&A model for forecasting revenue, expenses, EBITDA, cash flow, and financial performance under multiple business scenarios.

Module 3: AI for Treasury, Cash Flow and Working Capital Management

1. AI-powered cash flow forecasting, liquidity planning, cash positioning, and treasury analytics.
2. Predictive accounts receivable analysis, collections forecasting, customer payment behaviour, and credit risk.
3. Accounts payable analytics, supplier payment optimization, payment scheduling, and cash conservation.
4. Working capital optimization using AI-driven inventory, receivables, payables, and cash conversion cycle analysis.
5. AI applications in foreign exchange analysis, interest-rate monitoring, liquidity risk, and treasury decision-making.
6. General Case Study: Using AI analytics to optimize cash flow, improve receivables collection, manage supplier payments, and reduce working capital requirements.

Module 4: Generative AI, Financial Analytics and Reporting

1. Generative AI applications in financial reporting, management commentary, financial research, and corporate finance analysis.
2. AI-assisted analysis of financial statements, budgets, forecasts, management accounts, and performance reports.
3. Automated financial reporting, narrative generation, executive summaries, and financial dashboard interpretation.
4. AI-supported financial research, market analysis, competitor analysis, industry intelligence, and investment research.
5. Prompt engineering for finance professionals, validation of AI-generated outputs, fact checking, and human oversight.
6. General Case Study: Designing a generative AI workflow for preparing monthly management reports, analysing financial performance, identifying key variances, and producing executive insights.

Module 5: AI for Financial Risk, Investment and Decision Analytics

1. AI-powered financial risk identification, risk scoring, anomaly detection, and predictive risk analytics.
2. Fraud analytics, unusual transaction detection, financial anomaly identification, and continuous financial monitoring.
3. AI applications in investment analysis, portfolio analytics, valuation, market intelligence, and scenario analysis.
4. Predictive credit risk, customer risk assessment, counterparty analysis, and financial exposure monitoring.
5. AI-supported strategic decision-making using financial, operational, market, and economic datasets.
6. General Case Study: Developing an AI-powered financial risk dashboard to identify unusual transactions, liquidity risks, credit exposures, investment risks, and emerging financial threats.

Module 6: AI Governance, Implementation and Corporate Finance Transformation

1. AI governance frameworks, responsible AI, model risk management, transparency, explainability, and human oversight.
2. Financial data privacy, cybersecurity, access controls, data quality, data governance, and regulatory considerations.
3. Evaluating AI solutions, vendors, finance technology platforms, implementation costs, benefits, and return on investment.
4. AI implementation strategies, change management, finance workforce skills, process redesign, and organizational readiness.
5. Developing AI performance indicators, governance mechanisms, continuous improvement processes, and AI adoption maturity models.
6. General Case Study: Developing an AI-enabled corporate finance transformation roadmap covering technology, data, people, processes, governance, cybersecurity, use cases, implementation priorities, and expected financial benefits.

General Information

1. Customized Training: All our courses can be tailored to meet the specific needs of participants.
2. Language Proficiency: Participants should have a good command of the English language.
3. Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.
4. Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).
5. Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training, customized to the client's schedule.
6. Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.
7. Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.
8. Additional Services: Accommodation, pickup services, flight booking, and visa processing arrangements are available upon request at discounted rates.
9. Equipment: Tablets and laptops can be provided to participants at an additional cost.
10. Post-Training Support: We offer one year of free consultation and coaching after the course.
11. Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.
12. Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.
13. Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.
14. Website: Visit our website at www.fdc-k.org for more information.