As part of the 'Businesses after COVID-19' webinar series, UCL FinTech Society interviewed Imam Hoque (CPO and COO at Quantexa).
Mo Safayat covers key discussion points about Quantexa’s business mission, the role of data in the pandemic and the shifting regulations on the use of data in this interview transcript.
1. What is Quantexa?
Quantexa works with a whole range of organisations helping them to make the most out of data and tackle all the problems that they are facing such as credit risk, financial crime and customers.
We are currently in the midst of a revolution like the industrial revolution. But this time the changes are happening faster because of three reasons. Data is everywhere, computer power is available everywhere and digital channels are spreading. These three things together are now enabling the AI revolution.
2. What is the role of data in this pandemic? How is its role changing?
The pandemic is a new challenge that shows how things are moving so much faster in the world. At first, all the health organisations gathered the data and communicated and shared the data. They then used statistical models to predict the trajectory of the pandemic. This is probably the first time that the general population is being dictated on what to do by these statistical models.
However there are still concerns and fears on data privacy but it is acceptable and balanced. Coronavirus is being so disruptive as data is increasingly being used to monitor if a city like Leicester should again be put in lockdown. However, the question is what is invasive use of technology and what is proportionate use of technology? Data can be very powerful in modelling if used correctly.
Some societies have traditionally accepted the use of greater control and it does not have to be communist countries. For example, Singapore is known to have a government with great power. The Norwegian response to the coronavirus also shows how a democratic government is using data to make decisions and achieve greater control.
Data is powerful if used correctly but the question is how to use it proportionally.
3. Do you think attitudes and regulations towards data use will impact how we fight Covid-19?
I would not say it is a hindrance, we always adapt to regulations. When we are doing big data projects, we are sharing our data with commercial entities all the time such as banks, supermarkets and social media sites but when it comes to sharing data with the government, we feel a sense of fear. This is because the government can put you in jail and maybe get something wrong that messes up your life.
Ultimately, I believe that countries that are overprotective over data will fall behind those that are more willing to use data. In the same way, countries that are using data to combat Covid-19 will come out of the pandemic quicker. Data can help governments in many ways such as find any possible shortage in the national health systems and how you can better service the public. It is a big mistake to not use data. Decisions need to be made by using facts, figures and models. Models need to be a combination of really intelligent input from humans with data.
4. Can you use machine learning with unstructured data?
Machine learning has many components, some of it are unsupervised and you can do a lot of clustering. You can use it on unstructured data but you have to have enough of it.
Always think about the input data and the context it provides you. Nothing is a set of single observations. You need to data quality clean up. Think about how you can optimise the model.
5. What went wrong with the UK Covid-19 tracing system compared to the ones in Singapore and South Korea?
You need an environment where people are willing to share data, and need discipline for adoption. Unlike Singapore, the UK population is not used to being told what to do.