The advance of technology is rapidly gaining pace. Companies are adopting technology across all areas of business due to its ability to streamline processes and drive efficiencies. One of the main ways tech is shaking up businesses is through the production of big data. With real-time data collected fueling evidence-based decision making, we can create a new level of financial reporting.
If you’re a complete newbie to the idea of big data and analytics, or you’re ready to think about how big data can vastly improve your business, read on. Learning more about big data and how it can work for you and your business is the first step.
There are many big data applications in finance. The integrity of financial data is crucial to the healthy operation of any business, and that is where analytics can help.
The benefits of using big data analytics in finance are numerous – but we’ve picked four to give you a broad yet detailed overview of why you should be using these systems in your business.
Firstly, what do we mean by Big Data?
Big data describes a large volume of data that a business produces on a daily basis. However, the volume of data you collect is not particularly relevant, it’s what a business does with their big data that can produce smart results. If a business analyses big data effectively, it can lead to innovative insights and inspire strategic business decisions. Sounds pretty good, right?
Big data has arrived and financial reporting needs to catch up
Despite, the potential influence of big data strategy in financial reporting, financial professionals are finding it tricky to adapt to the latest development in tech. Failing to implement big data thinking, can rob the financial industry of effective, data-driven solutions. Data-driven decisions have proven to be invaluable to financial reporting, so we think it’s time the financial industry hopped on board this fast-moving train.
Now, how can we apply big data thinking to finance (particularly financial reporting) and even debt collection? Good question. Let’s take a look.
This is undoubtedly one of the major applications of big data in finance. Continuous monitoring can be thought of as an automated (and, obviously, continuous) audit and checking process.
Due to its ability to quickly detect issues, continuous monitoring has become increasingly entrenched in financial reporting. As big data in the finance industry has grown, it has become a feature of high-tech software programs for financial insights.
There are three central parts to Continuous Monitoring technology:
1. Continuous audit
Using big data in auditing means that the financial reports are continuously checked for changes, discrepancies and errors. The advantageous features of continuous audit using big data are volume, velocity, variety and veracity. Of course, when any new tech comes along, there are always problems in tow.
Challenges facing continuous auditing for financial insights include data with different formats, tampered data, incomplete data and search encrypted data. Being aware of future challenges when implementing new technology is one way to prepare for such challenges.
2. Continuous controls monitoring
Effectively collecting big data can lead to continuous control monitoring. So, basically, you’ll have eyes everywhere and your team won’t miss a thing!
The system continuously monitors financial controls that have been put in place. Should any controls be breached or found to be weak, the system will alert the user quickly. Real-time results lead to faster problem solving and it most cases, cost-saving initiatives.
3. Continuous transaction inspection
In 2019, protecting data is just as important as collecting it. As more and more powerful devices are implemented, the task to secure your data becomes more challenging. So, continuous transaction inspection means that transactions are continuously inspected, as the system looks out for suspicious or unauthorised transactions.
Use of continuous monitoring as a big data application in finance can enable problems to be caught earlier – reducing the potential need to investigate discrepancies in your accounts. Likewise, if you are ever audited by the ATO or a regulator, your records will be much easier to validate – ultimately saving you time and money. It’s a win-win. Plus, who doesn’t love a bit of extra organisation, right?
Enhanced security protection
This follows on from continuous monitoring in that big data systems will provide a much faster alert if a red flag is raised within the system. To clarify, if you’re using big, data-driven systems in the finance industry, if any suspicious or criminal activity occurs within your business, the activity is likely to be picked up within a day or two.
This type of automation also eliminates human error. Your business will no longer have to rely on employees to be the watchdog, so you can maximise efficiency, then re-distribute their talents into your business.
Previously, something like a staff member regularly exceeding transaction limits or making dubious purchases may have gone undetected for months – possibly only being recovered when the police, debt collectors or the regulator are involved. Trust us, as a debt collection agency, we’ve seen it all.
However, with an intelligent system constantly scanning your reports and searching for discrepancies, deviations can be found and rectified much faster.
System automation strikes to the heart of efficiency in business infrastructure. It’s not about reducing jobs, it’s about effectively distributing talent, whilst automation gets on with the routine or grunt work. Automation through big data in the finance industry is now commonplace for good reason – it can markedly increase the quality of your financial reports. There are plenty of benefits to system automation, so here’s just a few:
1. Time saved
The manual data entry process is either eliminated entirely or drastically reduced. By automating your invoicing and reporting systems, for example, your monthly reconciliation statements can self-populate each time you pay an invoice.
2. Eliminating human error
If your system is automatically populating data as it is entered, you cut out a large amount of risk associated with human error. Accidents that arise from human limitations, like double payments and incorrect amounts being recorded, can be cut out of the process and replaced by a purely mechanical mind.
Whilst system automation has positive applicants, we’re all about looking at both sides. So, here are a few pitfalls to watch out for when implementing system automation into your financial reporting:
Choosing what to automate
100% automation is not on the cards, yet. So, when implementing system automation, you need to pick and choose what is right for your business. Particularly in areas like compatibility, user interface, or any area that requires manual testing. Areas that are characterised by complex business logic should probably be left to a human!
Therefore, it’s best to start with automatically basic jobs, then moving to more complex situations.
High upfront cost
Implementing automation for financial reporting will reduce your costs in the long run, however, the initial cost may be steep. With great technology, comes great cost, unfortunately. However, it’s important to remember your endgame. Automate financial reporting for better results, and efficient use of talent in your business operations.
With big data on board, access to real-time graphs and other visualisations will (in most systems) be generated automatically in your dashboard, ready to be extracted for any presentations or offline reports.
As many financial controllers know, it can be downright painful trying to explain numbers to a non-numbers person. It’s often much easier to just show them a graph that visually demonstrates the gap between projected and actual revenue.
A good analytics system will provide you with customisable dashboards that will enable precise drill-down so that you can easily access the underlying data should you need to examine this.
Big data is a BIG win for financial reporting
As you can see, the applications of big data in finance are numerous. But if you take a step back and look at these applications as a bigger picture, it’s easy to see that the use of big data in the finance industry is predominantly about driving efficiency.
By continuously monitoring finances, providing greater security and automation options, big data can greatly increase the speed of work while reducing risks – generating greater cost savings. If you’re interested in finding out more about the power of big data in financial reporting, download our eBook The strategic CFO: How to implement a data-driven business strategy.