Predictive analytics is a form of technology that looks at current and historical data patterns and predicts how likely those patterns are to repeat in the future. It makes these predictions by drawing on a series of techniques, including AI, data mining, modelling, machine learning, and statistics.
This guide will cover:
- Types of predictive analytics models
- How accountants can use predictive analytics
- How Countingup helps accountants service clients better
Types of predictive analytics models
Predictive analytics normally comes in three forms, including:
Decision trees are useful if you want to understand what leads to someone’s decisions. This type of predictive analytics places data into sections based on specific variables like price or market capitalisation. As the name suggests, decision trees resemble real trees with individual branches representing choices available and leaves that present a particular decision. This model is the simplest because it’s easy to understand. Decision trees are also very useful for making decisions in a short time.
This model is mostly used in statistical analysis. Regression is best suited for determining patterns in large sets of data. This model operates by figuring out a formula that represents how all inputs in the dataset are related. You can use regression to determine how price and other key variables can shape security performance in a system.
Neutral Networks is a form of predictive analytics developed by imitating the way human brains work. This model uses AI and pattern recognition to deal with complex data relationships. It’s useful if you have multiple hurdles to overcome, like having too much data on hand, not having the formula to find a relationship between inputs and outputs in your dataset, or when you need to make predictions, not find explanations.
How accountants can use predictive analytics
Predictive analytics has many uses for multiple industries. We’ve listed the main ways accountants can use it below:
Detecting and reducing risk
Predictive analytics is useful for detecting fraud since combining multiple analytics methods can improve pattern detection and help prevent fraud or other criminal activity. High-performance behavioural analytics can boost cybersecurity in accounting firms by examining all actions on a network in real-time to spot abnormalities.
Credit scores are another well-known example of predictive analytics that incorporates all data relevant to a person’s creditworthiness.
Optimising marketing campaigns
In marketing, predictive analytics helps accounting firms optimise their campaigns by determining customer responses or purchases and finding cross-sell opportunities. Using predictive models allows firms to determine where to focus ad spend, qualify and prioritise leads, and tailor their efforts to attract and retain clients that are the most profitable.
Predictive analytics shows how likely a customer is to act, allowing marketing teams to devote more attention to them and minimise wasted time and money spent on customers that won’t respond.
Accounting firms can also use predictive analytics to forecast inventory, manage resources, set prices for their services, and so on. Predictive analytics can identify where resources will be needed most and can have the greatest impact. Accounting firms can use this information to make profitable decisions and optimise their daily operations.
By integrating modelling capabilities into the firm’s software, you could even run business scenarios through the predictive analytics platform to determine the best course of action. This insight allows you to make informed decisions backed by data.
Building a budget
Accountants spend a lot of their time building budgets, especially during the last few months of the tax year. As you know, creating annual budgets is no small task and may include hundreds of line items. Since many of those items involve predicted costs, it could significantly differ when comparing budgeted costs to actual expenditures.
Predictive analytics technology has the ability to create extraordinarily accurate forecasts. It processes data from a range of sources, which helps you spot subtle patterns and trends so you can create a more precise budget for your client.
Analysing loss drivers for clients
Clients expect their accountants to provide advice on different aspects of their business. It’s not only about crunching the numbers anymore. Employing predictive analytics will give your firm invaluable foresight about potential areas that are draining resources in their business.
Share this information with your client and offer advice on how to prevent the situation from worsening. It will boost their confidence in your firm and improve your relationship with them.
Determining what drives people to make sales is a complex equation that has a number of variables, which means it’s practically impossible to predict future sales manually. But predictive analytics empowers accountants to accurately and quickly assess data from different sources to achieve a precise sales forecast.
This way, you can empower your clients with the data they need to make critical decisions to help their businesses grow and evolve.
Analysing data is a must-have skill for accountants these days. Mastering the art of predictive analytics means you can deliver unmatched results for your clients, contributing to a thriving firm in the future.
How to save time managing small business clients
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