Case study

Applying AI to create a more efficient and scalable process for risk assessments without compromising on quality and air travel safety.

CPH is the largest airport in the Nordics and is looking to expand its yearly passenger numbers from 30 to 40 millions. To enable this, the airport is constantly undergoing changes to handle the increased number of flights, luggage and passengers.

Every change, from repositioning a gate pathway to changing the materials of the tarmac, requires a risk assessment of its potential impact on passenger and air travel safety, before it can be implemented.

Because of CPH’s high change level, there is a constant backlog of risk assessments, which, until now, have been handled manually by an experienced team of risk assessors with deep know-how resulting in long processing times. CPH needed a solution to support less experienced risk assessors in preparing satisfying reports in a scalable setup, without compromising on quality and air travel safety.

By applying artificial intelligence (AI), Netcompany has developed a cutting-edge module that uses text mining to classify which risks are relevant for a given change. Further, the AI offers context to the relevant flagged risks and resulting remedies by traversing existing risk assessment reports and presenting only the most relevant reports for the risk assessor.

The AI module bootstraps risk assessors by assisting them in creating more qualified and data-driven judgement calls about potential risks, creating a more efficient and scalable process. It is embedded directly into the existing risk assessment tool, maintaining one common workflow for the risk assessors. On the technical side, the module is built on top of standard, trusted open-source components – hence it can be released on any type of IT infrastructure.

The risk assessment reports can be processed faster and more efficiently, thereby reducing the number of inquires in the backlog to implement changes faster. Furthermore, the flagged risks and associated remedies are data-backed and more consistent.
 
Results:

• Risk assessment is handled more efficiently, reducing the backlog and enabling CPH to implement changes significantly faster
• The AI module enables risk assessors to conduct more qualified and data-driven risk assessments while removing the need for 10+ years’ experience
• The solution is embedded in the existing risk assessment tool meaning there is still only one common workflow for the risk assessors