Company Profile: Virtual i
Network Middle East profiles Virtual i, a provider of AI-powered insurance risk engineering
Please describe virtual i
Virtual i is a risk engineering and data analytics start-up that enables the insurance industry to assess risks it is currently unable to see due to time, resources, geopolitical and technological constraints. We are developing capabilities enhanced by artificial intelligence (AI) and machine learning (ML), seeking to transform the way the industry carries out risk engineering assessments.
We collect and train data, allowing computers to visualise the critical components of risk assessment. Computers can catch what the human eye misses and extract valuable information from data that humans would ordinarily overlook.
That said, the human element remains crucial; AI will never replace the value of human cognitive skill. Computers do the visual analytics scoring and then recommend to the human end user on the likelihood of risk based on that profile. AI here becomes an enabler of humans to make better decisions, and not a replacement.
What is your company’s history?
The idea behind virtual i came about when working for an insurance company based in the UAE that had a client based in Yemen. After conflict broke out in the country, it became too dangerous to send anyone out there to assess the risk, although we had a USD 50 million cover on their industrial facility. It baffled me that in the 20th Century, we still do not have visibility of assets we have insured. I wanted to change that.
I believe you should see every risk should, review it and then, and only then, should you provide insurance risk transfer. At the moment, the risk management process is a luxury service that only large corporates can afford. However, business continuity is even more critical to small enterprises than larger ones. Our objective is to make this service affordable and accessible to SMEs.
Earlier this year, the Dubai International Financial Centre (DIFC) announced that its financial technology accelerator, FinTech Hive, would expand to include insurance, Islamic finance, and regulatory technology services. We applied for and were accepted to the FinTech Hive, becoming the first insuretech company at the hub. We now have operations in Turkey and the Middle East, and planning to expand into Europe and USA.
The DIFC, in particular, is doing a fantastic job in creating a fertile environment for innovators. The next step should be to accelerate this process and create global success stories out of Dubai; I hope that virtual i becomes one of the first global technology titans to emerge from the region.
What is your company’s core competence?
Our key focus is to enable the insurance industry to see more risks, leveraging artificial intelligence and machine learning tools.
Currently, SMMEs (small, medium and micro-sized enterprises) generally lack access to the risk engineering services that larger enterprises do . Even though SMMEs play a vital role in any economy, contributing almost 40-55% of the GDP and even higher employment. While risk engineering has up to now been a luxury enjoyed mostly by large enterprises, we provide secure, fast and affordable risk engineering and data collection for the SMME sector.
Another of our key offerings is data and visual analytics. For years, the insurance industry has been collecting data of immense value but are frequently unable to utilise this information due to archaic data management methods. The data they collect is not structured and is static. Virtual i uses proprietary technology to collect data, and then deliver insights via interactive dashboards, plot risks on Google maps, measure the distance from one risk to another, as well as provide COPE analysis to clients, among other services. This information is of immense value to an underwriter not just at the time of making the underwriting decision, but in overall portfolio management.
The AI-powered machine learning algorithms that we are developing will, I believe, eventually change the way the industry carries out risk engineering.
What industry challenges are you looking to solve?
In insurance, you typically have a spectrum between two types of clients - clients with a reasonable risk profile and clients with a bad one. Unfortunately, the good ones end up paying for the bad apples since there’s no useful model of differentiating between the two. Ultimately, upright customers get fed up, a situation that has hindered deeper penetration of the insurance industry. In the past fifteen years that I have been working in the industry, the penetration rate has pretty much remained stagnant. We are therefore losing our relevance to customers as an industry.
Our solutions aim to maintain relevance in this turbulent industry landscape and provide the critical service of risk management to help businesses and the broader economy. We enable insurance companies to identify and avoid unscrupulous customers who end up hurting the broader industry.
Please discuss the future of artificial intelligence in your industry
For AI to develop, you first need organic intelligence. This intelligence is based on facts. Facts are based on numbers, which are based on structured data. As an industry, we do not have structured data, making it very difficult to develop AI tools. That's the reason we are putting boots on the ground, using video to capture various data points in a structured way. Structured data eliminates the need for collecting mountains of irrelevant information.