Smooth Sailing: AI For Financial Forecasting

Forecasts involve reviewing past and current market conditions to predict financial outcomes, enabling proactive planning to increase projected growth and address possible issues

- Vikram Mahidhar and Vivek saxena

Rough seas have become the norm across industries, as businesses go through ebbs and flows of profitability. to prevent potentially going under, companies look to financial forecasts as trusty navigational charts that can help with predicting and steering around troubled waters to ensure smooth sailing ahead. It is an essential task for virtually every organisation, especially public companies legally obligated to disclose their economic health to shareholders. Forecasts involve reviewing past and current market conditions to predict financial outcomes, enabling proactive planning to increase projected growth and address possible issues.

Traditional Forecasts

Traditional forecasting is a labour intensive process. Revenue calculations typically require large crews to manually review classic business data (market demand, expected price and a few other inputs), run statistical calculations, and create an outlook for different regions and markets. the whole process can consume considerable time and resources each quarter. however, it is not only effort that is required. Forecasts are also prone to inaccuracies, as calculations often leave out other leading business factors (supply-chain data, availability of stock, etc.) and non-business factors (such as how the weather or current events can impact sales). Moreover, when multiple people are involved in producing a forecast, there is greater potential for human error.