Workshop: insurtech

Berna Ataç Ökten, Chairman of the Board at Marm Assistance, began the session by highlighting 11 of the current insurtech trends that are making waves in the industry. These include: automation, which MCI says will replace 25 per cent of insurance jobs; chatbots, with a digital chat experience being preferred to email dialogue for many people today, especially millennials; AI and machine learning, with Digital Insurer stating that 80 per cent of insurance underwriting is likely to be done using such technology in the near future; on-demand protection; personalisation, which leads to greater customer retention; and blockchain.
Next, Berna looked at how assistance companies can support insurers using insurtech through three key areas: health and safety, medical and roadside. Key points made by Berna were that when it comes to health data on employees (insureds), this can be taken with them onto different projects if kept in an interactive database, which can lead to the prevention of unnecessary costs.

working with new technology is essential. The savings are significant, efficiency is maximised, and errors are minimised

It can also readily highlight the fact that a pre-existing medical condition might make them unsuitable for a particular assignment. When it comes to medical assistance, smartphones and apps have proved very useful, especially with regards to patient direction, which can ultimately enhance customer satisfaction; but there is a need to be aware of app overload. Wearables, however, are becoming increasingly important monitoring devices and can be used by assistance companies to monitor insureds’ health and alert emergency contacts in case of inactivity by the wearer. In conclusion, said Berna, working with new technology is essential. The savings are significant, efficiency is maximised, and errors are minimised; but the human touch is an integral and irreplaceable component.

Agustina Razetti, Data Scientist at Shift Technology, took to the podium next to give attendees an insight into how her data-driven company uses AI to automate claims and detect and prevent fraud. For each insurer the company works with, it collects data on claims and policies, which is updated all the time, as well as historical data, and tailors a solution to that company. 
The key benefit of such a system is that it gives insurers a tool that pulls in all the company’s data and detects potentially fraudulent cases extremely quickly, whereas a human would take much longer to carry out the same tasks. In fact, the technology carries out processes that humans can’t do, such as sifting through vast amounts of data to detect similarities in different claims that might be a fraud indicator. The software maps connections between policyholders, doctors, tour companies, and so forth, and reveals networks that might be promoting fraudulent activities. It also looks for inconsistencies in meta data, so it can tell, for example, if a camera used to take a picture of a receipt is actually the camera being claimed for as stolen. 

Similarly, social media is integrated into the system to uncover cases of fraud; for example, if someone on holiday posts pictures of themselves participating in activities while claiming their journey was delayed due to injury. Using these elements, each case in the system gets a fraud score and lists what the suspicions are, whether that’s hidden medical tourism, a fake or exaggerated baggage loss or if a claim amount is inconsistent with the alleged treatment. The inclusion of various external data, as well as its network analysis, are just some of the things that differentiate Shift’s system from others, said Razetti.