Predictive Modelling: Maritime Risk Management Through World-Class Statistical Analysis

Insurance companies and maritime risk management (MRM) companies have previously used predictive modelling to try to find and eliminate risks However, digitalization in the maritime industry is transforming how risk management is done – through the use of more accurate, clear and thorough statistical analysis.

Maritime digital solutions can predict the likelihood of an event and estimate what kind of damage that event will do. It’s a bit like figuring the odds at the racetrack or the way a life insurance company predicts the odds you’ll live beyond your policy.

Full statistical analysis modelling is far more in-depth and accurate than modelling, which can only find direct causal relationships between events. In HiLo’s full fleet risk management statistical analysis, we can include this information on causal relationships after the fact to understand how an event occurred; but also take this information forward to plot trends and find future, as yet unforeseen risks.

How Maritime Statistical Analysis Works

At HiLo, we use data we gather both publicly and privately from our clients – over 4,000 of them. We use this to model possible incidents, their likelihood, and preventative measures maritime companies can take.

The ultimate result is a model of potential risks that allows leaders in maritime shipping companies to mitigate and prevent damage or injury. This maritime digital transformation creates a risk decision tool for the maritime industry that outperforms anything that’s ever existed before.

The Advantages to our Maritime Statistical Analysis

Previous modelling can be unreliable or make predictions that can be detrimental to a company. For example, predictive modelling is used to rate bonds of all kinds. Those ratings are based on a model that might predict that a specific entity is likely to default on the bond. The entity might not warrant this prediction. Since it’s based on a set of variables that an entity, like a company or a municipality, has very little control over, they might get a negative rating without a lot of data to back up the rating.

In our fleet risk management statistical analysis, all predictions save lives, cargo, ships, and money. It’s based on massive amounts of data that’s processed to deliver a prediction of potential risks.

Confidence

Using extremely large datasets gleaned from digitalization in the maritime industry, you’re able to get better predictions. One example of this is Big Data, the information that tech companies like Google and Facebook gather. That massive amount of data allows them to predict what consumers are going to do to a level of precision that would have been undreamt of a generation ago.

The HiLo model is similar in its power in fleet risk management analysis. As the data sets are so massive, they allow for both better predictive abilities and precise methods for resolving risks than ever before.

Information

Because the datasets are so massive and drawn from thousands of maritime digital solutions, it makes it easy to keep the leadership of maritime companies informed of every eventuality.

If an unknown threat shows up, company management knows about it as soon as information is available. This allows for better protection of assets by preventing leaders from being blindsided by a threat that someone already knew about.

Proactive

Having the right fleet risk management analysis in hand, maritime leaders can proactively prevent incidents. They can seek remedies for incidents before those incidents even happen. If, for example, you knew icebergs had reached further south than usual, into North Atlantic shipping lanes, you might move your luxury liner further south to avoid a collision.

Being proactive versus reactive is the best way to ensure that losses are never incurred. While it’s vital to learn from everything that happens, it’s better to prevent the incident.

Making Predictive Modelling the Norm

In fleet risk management analysis, it’s traditionally been the purview of former captains, industry leaders, and trained excerpts to assess risks and provide risk management. With the digitalization in the maritime industry, we’re able to create a risk decision tool for the maritime industry that provides more insight and is more accurate than ever before.

Using computers wasn’t readily adopted, as it was a profession with a long and glorious history.

Data sharing in the industry only happened after there was an incident. Then, after everyone knew something had happened, shipping companies would finally share details. Often, the only things that were shared were incidents that cost lives or a great deal of money.

With information from thousands of shipping companies now being filtered in, we’re able to both predict risks and provide the solutions We aren’t waiting for catastrophic incidents. We can see the smaller incidents that forewarn of a larger problem.

Today, many more maritime companies are embracing the power of HiLo’s statistical analysis.

The Human Factor

Even with maritime digital solutions, amazing algorithms, and massive datasets, there’s still a lot that a human can contribute. That’s why the best fleet risk management analysis companies still employ former captains and other risk management personnel to know what each pristine means. They can take a prediction from the computer and translate it into on-the-ground action that can prevent incidents from occurring.

The One Factor

“Unsuccessful predictive modeling can always be traced back to one factor–inadequate data. Predictive modeling is only as good as the data it hinges on. It’s an unfortunate fact that companies who carry out predictive modeling using only basic data that’s publicly available will not see effective reports with valuable insights.” – https://www.maritime-executive.com/features/what-makes-or-breaks-predictive-modeling-for-risk-management

More data is more complete. That’s exactly why Google, Facebook, Microsoft, and other tech companies are mining data every second of every day. The more they know, the better they can predict our behaviour and place ads in front of us that will get us to buy from their customers.

The single most important factor, regardless of who your fleet risk management analysis company is, is the size of the datasets. If it’s too small, you’ll miss those smaller occurrences that might warn of much larger and more costly problems.

Increase your fleet safety

HiLo’s sole focus is to make everyone safer at sea, through the data we receive and the analysis and recommendations we provide. The more companies who share their anonymous data with us, the more we can reduce maritime risk.

Try our demo today and help us get more seafarers home safely.