RTICs & SIC

Finding companies hidden by SIC Codes

There is always a sense of joy when we discover a company hidden by SIC Codes here at The Data City.

We love finding companies that defy classic industrial classification in our databases of emerging economic sectors. We’ve previously covered Kanpai, the UK’s first craft sake brewery, and Satavia, an aviation-net-zero-AI mash up. Now we’ve unearthed a blockchain-cyber-security-autonomous-vehicles hybrid. As you’d imagine, there is no SIC code for this kind of business so it’s impossible to find them using SIC data.

Cube are a Korean autonomous vehicle security platform, based on blockchain, registered in London.

Autonomous vehicles and cyber security

Autonomous cars rely heavily on wireless communication techniques, such as vehicle-to-vehicle, navigation route information, GPS and other driving data. They continuously communicate with various sites to remotely monitor their internal and outside states. These various network accesses increase the risk of malicious attacks on autonomous vehicles.

There are an increasing number of companies who are countering this threat. It was recently highlighted by Poppy Gustafsson, chief executive of Darktrace. In a recent interview with The Guardian about their IPO plans she said;

“It really does feel like we’re in this new era of cybersecurity. The arms race will absolutely continue, I really don’t think it’s very long until this [AI] innovation gets into the hands of attackers, and we will see these very highly targeted and specific attacks that humans won’t necessarily be able to spot and defend themselves from.

“It’s not going to be these futuristic Terminator-style robots out shooting each other, it’s going to be all these little pieces of code fighting in the background of our businesses. In my time here at Darktrace, I’ve seen attackers try [to] use things like Teslas parked in the office car park, [internet-connected] fish tanks in casinos, and fingerprint scanners on the doors of warehouses, all as a sort of new and novel way into businesses.”

Introducing Cube Intelligence

Cube says that it has solved the problem of autonomous vehicle security by using blockchain technologies, AI-based deep learning and quantum hash cryptography. These are all sectors that we’ve mapped at The Data City. This is the first time we’ve seen them combined with autonomous vehicles. They claim to be the first user of blockchain-based security in the field.

Cube’s aim is to provide an autonomous vehicle security platform to automotive manufacturers and other tech firms such as Google and Uber.

Finding the companies hidden by SIC

Standardised Industrial Classification codes are out of date and don’t account for new sectors. They certainly don’t provide a good way of understanding tech sectors that are coming together in interesting companies like Cube.

We wouldn’t have found Cube using SIC. They’re registered in the UK at Companies House as Cube Intelligence Ltd (11052579) under SIC Code 82990 – Other business support service activities not elsewhere classified. In other words, in the absence of an adequate category to describe themselves, they simply ticked ‘other’.

Naturally there isn’t a code for blockchain-cyber-security-autonomous-vehicles companies. That would be far too niche, wouldn’t it? You can’t have a code for everything after all. But that’s exactly how the current SIC Code system works – it relies on having a code for every industry. And that’s why there isn’t a good code for new and innovative sectors like AI, AgriTech, cyber or net-zero. The system simply can’t keep up, and will always lag behind reality. The SIC Code system has made it difficult to define, explore and analyse emerging economic sectors, which in turn has meant that governments are unable to make effective policy decisions and investors cannot fully understand the size of the market they are interested in.

This is exactly why we’re on a mission to overcome the deficiencies in SIC. Our Data Explorer platform provides a new way of finding companies that defy classification, creating real-time data to support the emerging economy.

About the author

Fatima Garcia

Fatima’s background is in geography and the environment, after finishing her degree in Spain, Fatima decided to start a career in research in the UK. Fatima has a PhD in social and political sciences from Nottingham Trent University.