It took me years to be skilled in financial planning and analysis. Not every finance professional can be sharp enough to detect key highlights and provide analysis for the financial statements.
The basic concepts I always hold on to when it comes to financial statement analysis are as follows:
- The financial statements should tell the story of the period.
- The budget and forecast should reflect the Company’s plans, visions, expectations and educated guesses on the market trends.
- The balance sheet and key financial ratios should tell the strengths and problems of the Company.
It’s not easy to go through all the financial data to identify what’s relevant and what’s not. It takes years or even decades of seasoning to be able to quickly identify critical areas you need to probe and analyse further.
Put that seasoned finance professional into a powerful algorithm developed through data science and you get Generative Artificial intelligence (Gen AI). It integrates the know-how of a seasoned finance professional with data crunching, scenario analysis and understanding of external factors like market trends, customer behaviour and supply chain disruptions in a blitz.
Is it there to replace the seasoned financial professional? Yes and No. Yes, in the sense that there are a lot of analyses that can now be handled by Gen AI and No, because it transforms accountants from number crunchers to strategic advisors.
For finance leaders, Gen AI can help in cash flow projections, impact analysis for tax strategies, forecast outcomes for mergers and acquisitions and even various scenarios of capital planning. For accountants, Gen AI can help in the reconciliation and in-depth risk assessment with its capability to execute tasks, understand context and patterns and suggest optimal strategies. For management, Gen AI can help with scenario planning and decision-making analysis.
Gen AI also talks in the same language as you as you can simply upload your data in systems like Chat GPT and ask queries in plain English. No coding is required. It can handle prompts to give tasks like having the system create a 5-year forecast using information from the annual report, market trends and other assumptions. It still needs a level of financial acumen to probe the data and ask the right questions to the system. It takes time to master how to convert data into answers that are accurate and relevant.
The hardest part of financial analysis is going over data and seeing relevant information, flagging data variances and coming out with a comprehensive analysis for decision-making. Gen AI can sift through data faster and go over alternative scenarios and future outcomes. It goes beyond business analytics, which guides future actions from past performance. Financial analysts, business strategists and leaders can now easily extract valuable insights for decision-making.
The Pitfalls of Gen AI
There are always ethical implications with Gen AI as there should always be fairness, transparency and accountability in place. This will be an ongoing challenge with AI as there should always be a means to review and audit the system and results. Results should be traceable to specific data and decision-making logic. There’s also the human element and ethical consideration needed for decision-making with regard to issues affecting manpower like layoffs, closure and others as this impacts employee morale and the community.
Since the technology is new, there is the question of how Gen AI Financial Statements undergo the scrutiny of regulatory requirements and audits. How do you dissect complex algorithms as compared to traditional financial models? There is a need for more guidelines for audit, accountability, transparency and compliance to add more trust and acceptability for Gen AI financial analysis.
There is always a challenge of skills and experience of people using Gen AI. There needs to be proper training and a lot of time to master how to probe the system to get more accurate, reliable and transparent information.
Gen AI is Not Perfect
While the use of Gen AI increases among finance and accountancy professionals, there is a need to create standards of assurance and verification of Gen AI Financial Statements. In time, we’ll master it well enough to reap the benefits and gain more trust with Gen AI. All roads lead to Gen AI.
