You’ve probably heard of the Internet of Things (IoT), but what about the Internet of Vehicles (IoV)? This is a system where cars and trucks can talk to each other, share feedback, and even predict—and prevent—accidents. A vehicle can transmit its speed, location, and direction of travel to another one, and they can automatically work together to avoid a collision.
While this kind of real-time data used to exist only in the minds of Asimov and his contemporaries, it’s becoming a part of everyday life.
But real-time data plays perhaps its most prominent role in the business world, where companies harvest information from people, machines, and sensors, then use it to make decisions and boost efficiency. Here are some ways real-time data and analytics are pushing the boundaries of efficiency in the risk management space.
Enabling Early Warning Systems
You can use the real-time data in predictive analytics software to establish early warning indicators and then take action to prevent risk events. In this way, decision-makers don’t have to painstakingly consult a range of charts, websites, people, and publications before making a decision. Instead, they simply pull up a screen, see the info they need, and make a call that could save tens of thousands of dollars—or more.
Adding this level of efficiency to the event prevention process can free up precious hours for risk managers and other stakeholders. And with this kind of capability embedded on a systemic level, others can use the data to avoid and plan around risk events as well.
Automatically Discovering and Flagging Fraud
Fraudsters often can’t help but leave a trail of data that, when followed, leads investigators to them and enables risk managers to prevent their attacks. For example, many insurance thieves work in groups, collaborating to stage fake accidents and then file claims to steal money from insurance companies.
With real-time data, you can see claim information as it comes in and compare it to other claims being filed at the same time. If two people are collaborating, the timing of their claims, the amounts, their locations, and other data can be used to instantly flag the incident. You can then advise adjusters and others to act accordingly.
This is far more efficient than waiting for fraud to become manifest after the fact, and then trying to retrieve money or pursue damages in court. With real-time data and analytics, you can avoid legal fees, miscommunications, and pulling claims staff away from their other work to recover stolen funds.
Using Pattern Recognition to Assess Risk
Manually identifying patterns without a data analytics platform can be cumbersome, time-consuming, and rife with inaccuracies. For instance, how would you answer the question, “What’s more expensive for our company, workers’ compensation claims from clients with over 100 employees, or weather-related incidents in the southeastern U.S.?”
Without data analytics, digging out a reliable answer may involve a series of phone calls and emails, followed by hours of scouring through spreadsheets.
On the other hand, with real-time data and analysis using predictive analytics software, you can surface an accurate answer in a few moments. With real-time information streaming in from across your organization, even if the numbers change, you can see it right away. You can then include it in an important report, videoconference, board meeting, or strategic discussion.
Avoid Coverage Issues Before They Arise
Given enough time, risk managers can identify most, if not all, coverage gaps a company faces. But doing this manually is inefficient. Data visualization software can make it easy to identify coverage gaps in seconds, adding speed and accuracy as you adjust your policies.
For some organizations, overpaying for too much coverage may be putting unnecessary pressure on their budgets. Using integrated, integrated risk management software (IRM) software, you can quickly assess your coverage needs and then see whether you’re spending too much, too little, or just enough.
Create More Efficient Renewal Processes
Manually reaching out to inventory and equipment managers to compile lists of assets can gnaw away many hours when it comes time to renew coverage. But with IRM software, you can make sure the data has been inputted in real-time as new assets get added and old ones decommissioned or sold.
Using data analytics, you can compare your current and previous inventories, as well as how much you’ve paid in the past. Identifying trends is similarly straightforward because you can generate reports that demonstrate increases or drops in coverage needs over time.
By putting your data to work in this way, you can slice days off the renewal process and prevent inaccuracies at the same time.
With Ventiv's AI-based embedded analytics, you can collect and analyze risk data in real-time and use your insights to make time-sensitive decisions. Whether you’re improving the claims process, reducing costs, preventing fraud, or more, Ventiv Predict gives you the data and analytical tools to make each process more efficient and reliable. Chat with an expert to see how Ventiv Analytics is right for your organization.
