There are various reasons to build a business, and some of them don’t focus on profitability. Maybe you want to leave a legacy for future generations, or challenge yourself, or create jobs — or perhaps you’re just bored. But whatever your motivation may be, the reality of the situation is that your finances are of critical importance. If you don’t handle them, you won’t stay open.
Financial management can be challenging, though, particularly for larger companies with massive numbers of payments to process or businesses lacking any financial expertise. Technology is the obvious solution, and every year brings fresh tools and services to make it easier to keep things in line, but there’s still more that can be done.
Enter big data, the practice of collecting and analyzing vast pools of information from throughout the digital world (and even beyond through IoT connectivity). In principle, it seems very promising as far as managing finances goes — but what kind of effect can we anticipate?
In this piece, we’re going to consider how big data will affect how businesses across the world manage their finances. Let’s get started:
It’ll help them deal with fraudulent transactions
Greater insight into data through fraud management services will make it significantly easier for a business to minimize the impact of fraudulent transactions. Banks already provide anti-fraud services, flagging up transactions that seem questionable, but it’s only going to get more sophisticated in future with all the nuanced ways in which financial data can be analyzed.
The standard hypothetical scenario for demonstrating the value of big data compares payments from any given account to confirm legitimacy. Let’s say a card is used for a transaction at a bar in one country at 3pm, then used for a large retail buy at a store in another country at 4pm — the anti-fraud system could crunch the logistics to decide if both transactions could be genuine.
If there’s no realistic way for someone to issue both (they simply couldn’t have made it from location A to location B in that time), then the system can flag them up for manual review. If not, and if other factors point to them being genuine, it can leave them alone, preventing a lot of unnecessary hassle.
Related read: How Big Data Has Transformed the Real Estate Industry
It’ll greatly simplify tax calculations
Varying from country to country and even state to state (or region to region), sales tax can be a great source of frustration for companies that have wide-reaching operations. Furthermore, there’s the need to report associated details to government agencies. No one wants to be subjected to a painstaking audit, particularly if they can avoid it.
Not only will big data make it simpler to carry out calculations using up-to-date tax codes and figures, but it will also make it much easier for governing bodies to stay apprised of what’s going on. Instead of needing to assemble full reports, they can simply request and receive access to the relevant databases, and glean everything relevant from them.
Tax calculation has already become much easier, but there’s plenty of room to improve. Overall, given that tax brackets and laws can (and do) change fairly easily, no longer needing to chase details will be a big time-saver for businesses of all kinds.
It’ll make financial data protection much easier
Now that it’s been a fair while since the implementation of GDPR in the EU, there’s been enough time for the common vulnerability of private data to be acknowledged and discussed at great length. People are keenly aware of the need to keep their data secure, and that goes as much for businesses as it does for individuals.
Consider the typical online retailer, dealing with numerous transactions on a daily basis. Whenever a customer elects to save their credit card information to place one-click purchases, that information needs to be carefully protected.
Using big data to perform system-wide audits, a business will be able to more easily find the vulnerabilities in its data security, enabling it to patch them out far more rapidly than would have been possible without such widespread data. The bigger the system, the more likely it is to have such vulnerabilities, so it’s certainly worth hunting them down.
It’ll smartly predict budget requirements
How many of each type of product will you need next month, or the month after that, or for the entirety of next year? It’s hard to gauge, but it’s vital to have some idea of what to expect, because you need to plan ahead for budgeting. If you allocate too little money for the next quarter, you can run into problems.
If you allocate too much, though, you can end up wasting that excess (e.g. purchasing too much stock and needing to offload it at reduced cost). This can eat into your cash flow and cause problems with your regular operation — you might have payroll lined up and out of mind (automated payroll software is commonplace), but if your financial reserves dip too much, you can start missing employee payments. Before long, you can have a full-blown mutiny.
Fortunately, while people aren’t great at predicting demand, sufficiently advanced computer systems are excellent at it. An algorithm can pull from a large battery of data sources — factoring in historical sales, popular search terms, and the changing zeitgeist — to offer relatively reliable outlines of what’s just over the horizon.
If you have a solid idea that your business will face a lean period in the next quarter, you can start to cut costs and set money aside immediately, allowing you to make it through the slowdown without suffering major damage.
Big data analysis will fundamentally change how many regular business operations are handled, and financial management is certainly no exception. Machines are numerically inclined, and if you provide the right parameters (and the right sources), they can achieve remarkable things. It’ll be interesting to see what’s next.
This is a guest post by Kayleigh Alexandra. Kayleigh is a writer from MicroStartups.org – a blog dedicated to supporting micro businesses by donating its ad revenue to a different charity each month.