Predictive Modelling

HiLo uses industry-leading predictive modelling to save lives at sea. HiLo has developed some of the world’s most advanced statistical analysis to predict high impact events and reduce risks for seafarers. We collect full data sets from subscribing shipping companies and use predictive modelling to turn them into life-saving insights.

Our powerful predictive model pinpoints the leading indicators that can lead to catastrophic events at sea. Through regular reporting, we arm company leaders with details of the real risks facing their fleets. The HiLo predictive model empowers shipping companies around the world to keep their crews safe and protect their assets.

We’re passionate about saving lives at sea through secure data sharing and predictive modelling. We collect data from every part of hundreds of shipping companies to give our subscribers the most accurate risk analysis in the industry. Because HiLo looks at full data sets, not just incident databases, we see leading indicators missed by other systems. This means that you can be confident that HiLo’s predictions show the real risks for your fleet.

Our statistical analysis makes improving onboard safety a data-based process. We highlight the specific areas that need attention, enabling shipping companies to address the issues that are most likely to lead to an incident.

Will my fleet benefit from HiLo?

HiLo’s new approach unlocks your safety data. Shipping companies create so much data, it is difficult to see where the real issues lie. HiLo does this for you. We collect, standardise and analyse every data sets to show you the full picture.

Be Confident Our accurate analysis gives shipping companies complete clarity when it comes to the risks facing their own vessels. Knowing our statistics leave no room for uncertainty means company leaders can make decisions with confidence and access the reports to back them up.

Because HiLo uses leading indicators to pinpoint the areas that need improvement, shipping companies can use their insights to fix the most pressing issues for the long term. The ability to make sustainable safety improvements in the areas that need them most enables companies to allocate budgets and resources effectively.

Our technology team has created an interface that is simple and easy to use, putting the insights you need right at your fingertips.

Be Informed We provide accurate reports and interactive dashboards to ensure HiLo subscribers always have access to up-to-date analysis. Our members also receive monthly alerts about incidents that have occurred within the HiLo fleet.

Along with the customised risk reports we send each company, our quarterly reports also include anonymised risk analysis for the entire HiLo fleet. This allows companies to see how they are performing against the rest of the fleet.

Be Proactive HiLo has proven a transformative force in the way the maritime industry uses its data. Historically, most shipping companies relied on frequency analysis to try and estimate high risk areas.

Using our data to analyse leading indicators is a far more effective way of preventing incidents from happening in the first place. We use shipping companies’ big data to take a proactive approach to risk, helping companies to take action before it’s too late.

HiLo data is anonymised, so subscribers can be sure in the knowledge that no identifiable data will be shared, while taking advantage of invaluable insights into the real risks facing their own vessels and the wider industry.




What is Predictive Modelling?

Predictive modelling enables us to accurately identify the real risks of incidents and highlight them to shipping companies. Through maritime predictive modelling, HiLo empowers shipping companies to take the appropriate action and reduce risks, avoiding loss of life and damage to their vessels.

HiLo’s predictive modelling tool analyses hundreds of thousands of data points every year to pinpoint the leading indicators that can lead to incidents at sea. Thanks to the many shipping companies that share their data with us, we have access to a unique amount of big data that enables us to analyse risk accurately.

HiLo developed this ground-breaking predictive modelling tool through engagements with industry experts in dozens of workshops and by analysing thousands of maritime accidents.

The model calculates the probabilities of leading events progressing to incidents and the impact of those incidents. The frequency of occurrences is multiplied by the probability and projected impact of each undesired event to calculate the level of risk. The HiLo model is made up of numerous interlinks between leading events and incidents. The resulting calculations create a risk ranking, enabling companies to focus on the areas that will really make a difference.

For example, for every 1000 failures of navigation equipment, using:

  • • 1% probability that this event leads to a collision, and
  • • 10% probability that a collision causes harm
  • • average projected impact of 1 fatality

  • the calculated risk would be 1.
    *all figures for illustration only

    With the largest database in the industry for leading events, we rely on our huge pool of data and statistical expertise to calculate risks and their impact. The predictive model creates a risk ranking, ensuring companies can focus on the risks areas which are most relevant to their own vessels and crew.

    The industry leaders who put HiLo to the test

    The HiLo model has been tested and reviewed at every stage of development to make sure it is as accurate as possible. The first prototype was developed by Shell and Maersk in 2015, built by LR Energy Consulting and peer-reviewed by experts at Imperial College London.

    In the second stage, the model was piloted by Gaslog, Maran Gas, Northern Marine, Stolt, Teekay, Torm, Tsakos Columbia Ship Management and V Ships and the statistics were reviewed by The Alan Turing Institute. As the model was confirmed as a powerful, effective tool, 20 further companies joined the HiLo fleet. The HiLo product was finalised in January 2018, with incorporation of the company in April 2018.


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