The ways in which predictive analytics can help businesses
The use of predictive analysis is widespread across industries. The ability to project and predict trends is extremely helpful in various niches. Predictive analytics is also used by finance managers of various companies.

Predictive analytics in finance helps business leaders to orient their financial decisions to business goals more accurately. Let us learn how it can help businesses to control finances and decisions.

How can predictive analysis help in finance?

• Predictive analysis entails sifting through a large amount of data to draw patterns and predict outcomes. Indeed, there is a vast amount of data coming out of various customer transactions like RFID sensors, online transactions, internal and external financial reports, social media etc.

How can this help a company?

• This can indeed help a company by targeting more profitable customers, forecasting cash flow, demand planning, detecting financial frauds and risk management about performance.
• Companies can use the results of predictive analytics finance to predict changes in customer needs, target customers with real-time and appropriate product offerings, offer contextual information to customers etc.

What is the relationship between profitable customers and predictive analysis?
Customer data is available in tonnes through RFID sensors as well as online purchases and web navigation. If you can analyze this data, it may throw up interesting facts about customers. This can help you target profitable customers.

How can predictive analytics in finance help in cash forecasting?

• You need to manage your cash flow so that business operations go on smoothly. Predictive analytics can help you manage your cash flow.
• You can estimate your future cash requirements and plan accordingly. This is a very helpful outcome of predictive analytics.
• If you dig deep into the data coming out of company cash flow, you can identify vendors who pay late or who pay on certain dates. This will help you in managing receivables.

How to detect financial risks with the help of predictive analysis?
Business managers have been using predictive analytics finance extensively to detect financial risks. It helps to detect both internal frauds by employees and external frauds. It can identify fraudulent purchase orders and other indicators.

What are the examples of predictive analytics in real life?

• Some real-life examples of using predictive analytics finance can be found in card tracking, managing trade instruments, claim handling, risk analysis etc.
• You can analyze credit card usage of your customers by tracking the data resulting from their credit card transactions. This can help in identifying the spending behaviors of specific customers.
• Once you have such account specific behavioral insight, you can target these customers with innovative real-time offers and recommendations. You can also develop targeted marketing campaigns. This can result in enhanced sales of certain products. If there is a slowdown in spending in a group of customers, you can analyze the reason behind it.

How can predictive analysis throw light on the competition?

• As a business, you have to thrive in this competitive environment. With the help of predictive analytics in finance, you can ride out the rigors of competition and get an insight into what your competitors are doing.
• If the data on the volume of transaction, spending in each transaction, return purchases etc are analyzed carefully, it can throw up interesting insights about the practices followed by your competitors.