At a glance
- Predictive analytics is becoming more accessible to accounting professionals.
- Artificial intelligence (AI) tools can help accurately forecast risk and optimise cash flow.
- Start small with existing software or low-cost AI.
Every day, accounting professionals help clients and stakeholders make crucial business decisions using financial data. Predictive analytics combines data analysis, statistical modelling, and machine learning to forecast future outcomes and identify potential risks and opportunities.
These software tools might sound out of reach, requiring data scientists and enterprise-grade systems. But as technology becomes more affordable, companies of all sizes are finding ways to harness it, using client and company data to make strategic decisions to shape the future of business.
What is predictive analytics and how can small and medium practices use it to deliver value?
What is predictive analytics?
Predictive analytics is a type of data analytics that uses statistical techniques, AI and machine learning to analyse data and forecast future events that humans might miss. It’s the technology that helps Netflix suggest what you might want to watch next.
Phillip Stanley-Marbell, Founder and CEO of Signaloid, says many accounting professionals already use some form of predictive modelling.
“Whether performed by a small organisation or the CFO office of a large firm, traditional predictive analytics often use mathematical models that capture the fundamentals while also being explainable. For example, cash flow forecasting often uses the history of actuals and their time series trend to predict future incomes and expenditures,” he says.
However, unlike traditional reporting and forecasting, predictive analytic software can make it easier to predict outcomes. Firms around the world use them to leverage clients’ transaction, customer, operational and economic data to spot patterns and deliver data-driven recommendations. Instead of projecting cash flow based on previous months, these tools use multiple variables to create more accurate predictions:
- Seasonal trends
- Economic indicators
- Industry patterns and
- Weather data
Analytics are a growing trend thanks to the broad adoption of generative AI tools and impressive use cases from the likes of Airbnb. Dr Rutherford Johnson, Senior Lecturer at the London School of Business and Finance, says it’s a common misconception that AI-driven analytics are only for large firms with extensive budgets.
“Many accountants are already using or benefiting from AI-driven analytics without realising it,” he says. “Automated transaction categorisation in cloud accounting software, AI-powered fraud detection systems that flag unusual transactions, and smart invoicing are just a few examples.”
The business case
Newer predictive analytics tools that use AI, such as the IBM Watson Analytics suite and Alteryx, apply real-time data modelling to identify risks and opportunities in pricing, expected revenue, cost analysis, balance sheet analysis and cash flow forecasting.
“AI-driven models can predict future cash flows using a broad array of data, with much more analytical power relative to previous techniques…Predictive analytics can also help identify client behaviour trends, allowing for service customisation as well as predicting financial difficulties for specific clients,” Johnson says.
Instead of spending hours poring over spreadsheets to identify trends or anomalies, these systems can instantly flag patterns and potential issues across entire client portfolios.
Although Stanley-Marbell warns the quality of the input data will impact the reliability of the output.
“Predictive analytics are most useful to the human practitioners who consume those outputs when the practitioners can know how much to trust the predictions,” he says.
If the modelling is producing surprising predictions or patterns, question the reasons behind the data. The data inputted into the model could be incomplete or inaccurate, the type of model could be wrong for the task, or, sometimes, unexpected results can highlight opportunities or risks for the company.
For firms that primarily provide clients with standard compliance work, investing in predictive analytics tools could mean offering higher-value advisory services.
For example, the same data used for VAT submissions and routine financial reporting could rapidly:
- Identify seasonal trends affecting cash flow
- Flag clients at risk of working capital shortages
- Spot growth opportunities in specific revenue streams
- Predict potential compliance issues before they occur
While pricing for these services is still evolving, early adopters are taking various approaches. Some practices bundle predictive analytics into existing advisory packages, and others create standalone services. The key is matching the service level to client needs and demonstrating clear value.
“Many accountants are already using or benefiting from AI-driven analytics without realising it.”
Dr Rutherford Johnson, Senior Lecturer, London School of Business and Finance
Making predictive analytics work for you
For smaller practices, the traditional barrier for specialised analytics technology has been cost and complexity, but there are now multiple entry points for firms ready to enhance client service.
Choose the right tools
- If you’re new to predictive analytics and want to forecast a future outcome, consider starting with a lower-cost tool like ChatGPT.
- Check if your existing accounting software offers predictive AI tools, like Sage Intacct.
Start small
- Begin with a specific service area like cash flow forecasting rather than a practice-wide roll out.
- Test with a small group of clients in industries with seasonal fluctuations or rapid growth.
Build your capabilities
- Consider having one team member develop deeper analytics expertise.
- Invest in targeted training programs to bridge knowledge gaps.
Remember, the real value isn’t in the predictions themselves, but in your interpretation of what they mean for your business or clients.
This is where you’ll differentiate your services and demonstrate your value.
The IFA’s Data analytics in accountancy webinar series provides practical insights and skills to harness the power of data in your day-to-day work from 23 April onwards. More information here.
