Should You Use Predictive Analytics For Finance?

Image of data analytics screens on two computers atop a dark brown desk for the Should You Use Predictive Analytics For Financial Forecasting? blog post header image by Brixx

In order for companies to move forward, having an understanding of market progression can help them expand to the best of their potential.

While there are many analytics models that can help organisations gain insight into their operations, predictive analytics can help you get the valuable information your company needs to plan for its future. With key analysis contributing towards your financial forecasting, you won’t want to skip out on the benefit of using predictive analytics.

What is predictive analytics?

Predictive analytics is the practice of using statistical techniques and machine learning algorithms to analyze data and make predictions about future events or outcomes.

It involves analyzing past data to identify patterns and relationships and uses this information to predict what is likely to happen in the future. This can be done across almost all industries to anticipate future trends and patterns. It can be used to identify potential opportunities and risks, and make data-driven decisions based on those predictions.

What is an example of predictive analytics?

A credit card company can analyze a customer’s spending patterns to predict the likelihood of future default on payments. The company can use various data points such as the customer’s credit score, payment history, spending behavior, and demographics to create a predictive model. The model can then predict the probability of a customer defaulting on payments in the future and take proactive measures such as reducing the credit limit or offering a payment plan to avoid default. This can help the credit card company reduce the risk of losses due to defaults and improve overall profitability.

How are predictive analytics used?

There are a variety of uses for predictive analytics, all of which can help you to make the most out of your resources over time.

Budgeting and resource allocation

Predictive analytics technology uses data from multiple sources to identify patterns and trends that will help you to see if your budget is likely to deliver your desired ROI (return on investment). This is done by identifying patterns in historical data to advise the best possible resource allocations to achieve the desired outcomes.

Forecasting cash flow

Predictive analytics uses invoice data, past payment trends, cash position, and more to help you gain better visibility into cash inflows and outflows. It can help you better predict the timing of inflows and outflows, better plan for investments, the likelihood of customer payments, and more.

Identifying financial risks

Credit risk management apps that help score customers and identify their risk each time they make a credit purchase is generally powered by an AI engine. This type of predictive analytics collects information from sources like credit reports and market data. This information is used to minimize payment risks and predict blocked orders based on customer payment history, limits, credit utilization, and more.

Working capital management for accounts receivable

Insight into account receivable can provide you with timely insights into risk and receivables that may put a strain on your working capital. Predictive analytics can be used here to give you a snapshot of your ageing accounts, days sales outstanding, percentage overdue, and more. Here, companies use predictive analytics to classify accounts and predict available working capital.

Risk management

Another use case for predictive analytics is to help with predicting the risk associated with different tasks. This is often done by classifying them according to the impact on the business and are used to prevent potential fraud.

Make customer payment predictions

A common use case for predictive analytics is that of customer payment prediction. This generally allows you to track past payment trends and prioritise accounts to predict possible payment issues and find possible actions to take.

What are the benefits of predictive analytics?

By analyzing past data and identifying patterns, there are a multitude of benefits to using predictive analytics.

The problem with using predictive analytics for forecasting

Improved decision making

Predictive analytics can provide insights and predictions that can help organizations make informed decisions, leading to better outcomes and improved performance.

Increased efficiency

Predictive analytics can help automate and streamline processes, reducing the need for manual intervention and increasing efficiency.

Better customer experiences

Predictive analytics can help organizations better understand their customers, leading to personalized and targeted marketing campaigns and improved customer experiences.

Reduced risks and costs

Predictive analytics can identify potential risks and help organizations take proactive measures to reduce them, leading to cost savings and improved risk management.

Competitive advantage

Predictive analytics can provide organizations with a competitive edge by enabling them to identify and capitalize on opportunities faster than their competitors.

Overall, predictive analytics can provide businesses with valuable insights that can help them make informed decisions, increase efficiency, improve customer experiences, reduce risks and costs, and gain a competitive advantage.

Why SMEs should do their own forecasting

As a small business owner, doing your own forecasting is crucial as it not only allows you deeper insight into your current and future financial state, but it affords you the opportunity to gain a true understanding of your company from a granular level. This is something that isn’t possible with predictive analytics.

By conducting regular financial forecasting, you can get a better handle on how and where your company can grow. You can plan for multiple scenarios based on information that algorithms simply cannot predict or plan for and save yourself plenty of time and valuable resources while doing so.

By conducting your own financial forecasting, you are more likely to understand how you can plan to accomplish long-term growth goals and keep your company from going underwater.

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