The best real-world applications of predictive analytics in business

Best business uses of
predictive analytics.

Turn your data into future insights
Learn how different organisations are using predictive analytics to better determine future trends and outcomes

Transforming Operations

Applying predictive analytics to business processes.

The demand for predictive analytics has increased over the years as organisations find ways to assess future economic conditions, risk areas, and deploy resources more efficiently. This growth in turn has driven the development of sophisticated solutions allowing data scientists and analysts to build better algorithms and predictive models.

Organisations that have successfully deployed predictive analytics are seeing a significant impact on their operations. They take advantage of their historical data to discover complex correlations between data sets, identify new opportunities and forecast the future.

We’ve identified 5 use-cases of predictive analytics in the sectors of government, environment, and banking and finance. Each example provides you with a glimpse of how maximising the power of predictive analytics can allow you to generate predictive models that transform your data into actionable insights.


Forecasting waste requirements.

The volume of data available within the public sector is massive. Predictive analytics sifts through this large set of data helping government agencies in employing preventive measures and effective risk management.

Sustainability Victoria (SV), for instance, uses predictive analytics to drive the planning of infrastructure and strategic development for the management of hazardous waste in the state. By developing a projection model based on the Microsoft stack of technologies, it’s able to take advantage of the enormous data inputs coming from the Environment Protection Authority Victoria (EPA), and map out waste generation, profile trends and forecast waste arisings in Victoria.

Banking and Finance

Improving customer service and fraud management.

The banking and finance sector are now using predictive analytics to transform customer experience. It also helps them analyse the most common operational patterns regarding trades, purchases and fraud prevention.

For instance, many banks are no longer selling products to their customers based on generic segmentation models alone. Instead, they analyse unstructured customer data such as customer emails, survey feedback and call center transcripts to better track customer pain points and identify cross-sell and up-sell opportunities.

Financial service businesses also use predictive analytics to strengthen their fraud detection and prevention. By tracking user activity and checking them against their own fraud indicators, they can quickly determine “out of pattern” events and flag any potential fraudulent activities.

Predictive Analytics

Become a forward-thinking organisation.

Predictive analytics allows you to transform your data into actionable insights. Talk to our data experts today and learn how you can further improve your predictive analytics capabilities.


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