The top tech trends in financial reporting systems - SystemsAccountants

Estimated reading time: 5 minutes The top tech trends in financial reporting systems

The days of monthly reports based on manual spreadsheets that must be created fresh every few weeks and updated manually are long gone. Today’s collaborative, automated, connected systems outperform their precursors. Today, machine learning is driving advancements in financial reporting systems at warp speed.

Books are being closed faster than ever, while Enterprise Resource Planning (ERP) systems with AI capabilities can spot inefficiencies in different production stages, or if factory machinery is about to overheat, or even which employees are overworked, unhappy and likely to quit.

And there are some game-changing developments on the horizon.

It can be a challenge just to keep pace with advances in automation and machine learning, however, particularly as they redefine what ERP and Enterprise Performance Management (EPM) systems are capable of. Software today is a far cry from the previous generation of financial reporting tools, with accounting continually reaching new heights with the array of solutions now available to handle real-time problem-solving.

So, what are the major technology trends impacting finance systems today, and those set to have a significant influence on the accounting function of tomorrow?


1. AI is transforming ERP & EPM systems

For decades, ERP systems didn’t really change an awful lot. Company information was managed and processed in a uniform manner; slowly, often plagued with errors.

And the finance function itself was generally considered a necessity to be endured, rather than an opportunity to be seized. Data had to be entered manually, and the same people (think batch processes) then moved it slowly again through the system to support business operations.

AI has changed all of this. Modern ERP systems automate data entry and other repetitive tasks, and can execute multiple business processes, provide alerts and messages on system events in a fraction of the time it takes a person.

AI-powered ERP systems offer automated reporting and big data visualisation tools that can recalibrate the finance function as a strategic operation, adding value to the business and helping shape future direction.

The future of ERM systems is also incredibly dynamic. Connected, cloud-based analytics programs use sophisticated models to detect patterns, narrow down predictions and present users with recommended actions. Integration of smart ERM tools across platforms and functions can also elevate company performance by boosting different functions such as sales, supply chain and HR.

2. Automated financial close processes generate time for more high-value work

The financial close can be a challenging, time-draining process to verify and adjust account balances at the end of a designated period, before the accounting cycle closes.

Producing financial reports that gives an accurate picture of the company’s health is the goal, with which the  can then inform stakeholders such as investors, boards, lenders and regulators.

Many businesses struggle with the close. Some 87% of professionals work overtime during this period, with the added stress of doing so, unable to focus on important tasks and high-value work that can help a business grow.

Automating aspects of the record-to-report process can give a better view of operations, real-time reporting, and the ability to sort and prioritise risks, while one of the greatest benefits of outsourcing drudge work to machines is the reduction of errors.

There is an arms race to close faster playing out amongst the largest corporations, as they understand how reducing the time talent spends on preparing, reviewing and approving can have a big impact elsewhere in the business.

Efficiency gains from automation can eat into the time it takes to close and consolidate, freeing up the finance team to focus on more valuable work.

3. Rise of the robots

AI is having a two-pronged effect on the world of financial reporting. Robotic process automation and AI are reducing the need for repetitive jobs, while the rise in digitisation is increasing the demand for high-skilled workers.

Staying relevant is the key to avoiding redundancy via machine; the jobs most at threat of redundancy via machine tend to be things accountants do not enjoy, such as manual data entry, logging receipts, mapping resources etc.

Robots may eventually take a large proportion of these medium and low-skilled tasks, but as more processes become digital so grows the need for data scientists and the like. New possibilities in data analytics means new opportunities for accountants.

Recurring, predictable processes will continue to be automated, while the consolidation of financial systems into a single platform makes it possible for machines to take on more of the unsophisticated tasks accountants carry out each month.

4. Cloud-based accounting on the rise

Accounting systems hosted on the cloud have opened companies to a new paradigm in client engagement, and this development is set to continue. The ease of accessing digitally hosted systems anytime, anywhere, combined with the ability to share, edit and copy files collaboratively has helped businesses more accurately track sales, inventory and expenses, and fix problems before they escalate into a threat.

The cloud has also blurred the lines between bookkeepers, who now have analytic tools to provide insights and guidance, and accountants, who can access live banking feeds that record purchases and sales to inform their work for a client.

The all-in-one aspect of cloud accounting makes this possible, and every signal is of a further blending of finance roles, including those of wealth and succession planners. More features, add-on modules and dashboard analytics are appearing to help finance teams meet the demands of the present economic environment.

5. Predictive data analytics improves forecasting

Artificial intelligence doesn’t just remove manual processes; it can elevate operations across all areas of an organisation. The advancement of predictive analytics and algorithmic modelling based on enterprise data is enabling companies to identify weaknesses in their own operations.

Finance teams can use predictive data analytics, processed from a range of sources, to develop more accurate forecasting models, track client progress and collect previously hidden insights to inform business decisions and more.

Machine learning tools are blending transactional information with other data points to provide more accurate projections, helping the accountant devise smarter strategies for the business or give advice on loss drivers or other aspects of budgeting.

“Hey Siri, are there any outstanding invoices?”

The constant need for businesses to undergo digital transformations in order to gain efficiencies, scale and become more competitive has triggered a boom in demand for advisory services.

Finance functions are feeling the effect of this, as the search for efficiencies and new ways of working almost always begins with the numbers. A glut of intelligent financial reporting tools to help improve demand forecasting, resource mapping, production planning, transportation management, and more, are appearing in response to these needs.

Emerging trends in technology point to the acceleration of machine learning, AI and automation across financial reporting systems, forcing finance professionals to move with the times or risk being left behind.