ML for forecasting cash flow with disparate systems

Cash is the lifeblood of a business whether to fulfil spikes in demand curves or surviving through precarious times. No doubt, cashflow forecasting systems are becoming a big IT spend although their effectiveness is a matter of debate.

Sure, a forecasting system gives you heads up on upcoming cash crunch, allowing you time for preventive measures. What when it doesn’t?

A minor cash crunch may constrain your critical business processes while a major one might put you at the brink of bankruptcy

Limitation of current cash flow forecasting systems

The sclerotic structure of enterprise IT around legacy systems and siloed databases restricts the data pool available to forecasting systems. You see a forecasting system need past data to make prediction about the future. When the lagged data is insufficient, the forecast tend to be inaccurate. As a result, organizations are investing in modern cash flow forecasting systems that rely on machine learning models to bring more data from disparate systems and, thus, deliver accurate results. One such ML model is ARIMA.

Cash flow Forecasting with ARIMA

Autoregression integrated moving average or ARIMA is a forecasting methodthat uses lagged data on a time series analysis to deliver forecasts. ARIMA method is extremely effective in making forecasts on probably any value that’s time series data is available, including cashflow.

That is, if you keep a record of your account receivables and deductibles in a time series format, ARIMA will make accurate forecasts on your cash flow in no time.

Integrating ARIMA with your system

You may integrate ARIMA into your existing systems as a free Python or R library. In addition, you may integrate it directly into your browser and NodeJS-based application with a dedicatednpm package.

Moreover, ARIMA also saves you from manually gathering data from those spreadsheets and isolatedcomputers. As an ML model, it can learn and adapt to become better integrated with your disparate set of systems.

ARIMA as a cost-cutting measure

A vendor-oriented cloud-based cashflow forecast tool may cost thousands of dollars in annual fees. Since ARIMA is an open-source library available, it is not only more accuratebut alsoa lot more affordable than any other solution in the market.

SARIMA and SARIMAX

A cash forecasting system is only as good as the data it takes to make the prediction. Since ARIMA only takes lagged data into consideration, it isimmune to exogenous factors such as seasonal changes, which may impact future. SARIMA is an extension of ARIMA that takes seasonal changes into account while making forecasts.

There is more to seasonal changes that may affect the future, what about unpredictable weather like hurricane or man-made disaster likedrought. ARIMAX is an extension of ARIMA that takes exogenous factors like these into account while making predictions.

According to IDC’s Survey, 40% of the businesses have added cash flow forecast tools to their ERP systems. IDC believes organizations with intelligent cash flow management tools like those based on machine learning will be more adaptable to current market conditions and may find new avenues of growth.