How Machine Learning Can Aid in Error Detection for Construction Finance

Mistakes happen, but that’s no consolation to the lender who dispersed the incorrect funds, the developer who accidentally approved a change or the contractor who used the wrong tile on the flooring. The fact that these mistakes can happen at any – and every – moment doesn’t make these parties feel any better, either. We all make mistakes, that’s a given (we’re human, after all). But what if you could take human error out of the equation? Or at least minimize the number of manual touchpoints, thereby also limiting the opportunities for errors? You can with machine learning and automation.

Machine learning allows intelligent software to gather information, “read” data and organize it in the appropriate places. Once the system has absorbed enough of this information, it can move from data processing to data analytics – essentially predicting what an outcome may be based on past results and the facts at hand. When applied to construction finance this could be automatically extracting information from hundreds of invoices, pay apps, and lien waivers and then connecting all of that information to the project budget. This eliminates 80% of the manual data entry typically required from a development manager or loan admin. In fact, companies leveraging intelligent construction finance software (such as Rabbet) have reported spending 75% less time managing documents.  

So what does this mean for your project? A whole lot. It starts with a massive reduction in time, money and energy lost to human errors. OPIN Systems, an enterprise reporting software provider, notes an individual manually entering data will make about four errors per every 100 entries. When you think about how many numbers, documents and communications are included in a project, that error rate becomes quite daunting. A draw request alone can have more than 500 documents!

Machine Roles Vs. Human Roles

Machine learning may already sound wonderful, but not all humans are sold on it. That’s because many worry automation will replace their roles within organizations. This isn’t true. Instead, it frees up those workers to tackle higher-value tasks since the machines can do the rest. Automation works best on logical tasks that have a low degree of imagination. This includes tasks that are:

• Routine
• Sequential
• Straight-forward
• Repetitive

Humans, on the other hand, thrive on creativity. With automation, their skills can be best used on creative endeavors, including, reporting,  problem-solving, and communicating with partners.

When errors are eliminated at the “ground-floor” level – meaning within the data – this frees humans up to maximize their use of this data. This results in better standard operating procedures, fine-tuned best practices, more accurate trendspotting and forecasting, enhanced risk mitigation and, ultimately, projects that are completed on time and on budget.

Accountability at Its Finest

Most people know errors will happen. What they don’t know is whether they will be able to catch those errors before they become a huge problem for a project. This means your primary solution is to put a review system in place where someone is constantly checking documents for errors. 

Everyone would likely agree that spending hours reviewing documents is a waste of company resources. But what if we could lean on machine learning and let intelligent software do the heavy-lifting? Automated systems not only detect errors, but, as mentioned above, they can alert the right people to them. For construction finance, this means you can automatically know when an invoice is missing, when amounts aren’t lining up or when one of your custom rules hasn’t passed. You can spot cost overruns when there’s still time to address them, and you can make sure projects are staying on track. By freeing your team up to spend more time solving problems and less time searching for them, machine learning yields a tremendous boost for efficiency.

Automating tasks and digitally centralizing data also empowers your team to spot trends and patterns. By spotting those patterns you can often prevent the same errors from occurring in the future. Is the same employee responsible for more than one error? It may be time to have a talk. Is the same error occurring across multiple projects? That may involve some additional training, or a re-examination of your processes.

Getting Started

With so many moving parts, developers owe it to themselves to ensure their projects run as smoothly as possible. A huge part of this is minimizing costly, time-consuming errors and leveraging machine learning is a great place to start. 

Interested in empowering your team with powerful construction finance software backed by machine learning? Rabbet can help and we’d love to show you how. Schedule a demo today.