Technology relevant to InsurTech

Many broader technological developments and innovations underpin many of
InsurTech developments. Some technologies are interrelated, and a brief review helps establish a shared understanding of their nature.

Mobile technology and applications (apps)

The network effect of mobile phones and the development of applications for these devices
("apps") has allowed many companies to reach a bigger audience than was previously
possible. Mobile technology may be working in different ways for InsurTech, depending
on the generation of mobile networks available and the types of handsets that are most
widely used.

Smartphones and internet access enable innovations based on the use of
apps. For this, mobile networks that allow short messages and pre-paid mobile phones,
as well as large data transfers, would be necessary. This is particularly relevant to
emerging markets that have low insurance penetration and do not have a well-established distribution network. As in the example of BIMA (Box 7), mobile phones can notify individuals via SMS on anything from insurance coverage to
reminding them of the imminent withdrawal of airtime for premium payments.

Artificial intelligence (AI), algorithms and robo-advice

AI is intelligence exhibited by machines. A machine would be considered "intelligent"
when it feels its environment and takes action to maximize the
possibility of achieving its goal. It is widely used when computer programs are
developed to have cognitive functions such as learning and problem-solving. AI research
involves reasoning, knowledge, planning, learning, natural
language processing, perception, and moving/manipulating objects. 

Algorithms are part of AI, where there is a set of steps for a computer program to achieve a task under certain conditions. Well-known algorithms include route navigation systems or computer chess games. In the financial sector, algorithmic trading, such as high-frequency trading, is widespread, with pre-programmed trading instructions to execute large trading orders. The algorithm would follow conditional instructions for placing a trade order at a speed and frequency impossible for a human trader. 

Robo-advice, or automated advice, is becoming prominent, particularly for online investment and savings platforms. It can cover a broad spectrum of services but is essentially an "online automated advice model that can deliver advice in a more cost-efficient way" (HM Treasury and FCA, 2016). For the insurance sector, roboadvice is being developed for investment management and is now being increasingly used for quotes with automated advice and offerings calculated through algorithms. Instead of or combined with face-to-face advice, robo-advice can provide automatic guidance and execution on various financial decisions. Automated advice could assist pockets of the population that do not have access to financial advice to gain input in a more cost-efficient way than a human advisor. However, depending on how the algorithm to provide advice is structured, it could also lead to inappropriate advice being made inadvertently. 

Smart contracts

"Smart contract" refers to any contract capable of executing or enforcing itself. They are written as programming code, which can be run on a computer or a network of computers rather than in legal language on a printed document. This code can define strict rules and consequences that emulate a traditional legal document, stating the obligations, benefits, and penalties due to either party being in various circumstances. Smart contracts enable people to trade and do business with strangers, usually using the internet, without needing a sizeable centralized authority site to act as an intermediary. The limitation of a smart contract is that a program may not know what is happening in the physical world or react to unforeseen events, thus being unable to execute an action that was the basis of the contract. Smart contracts often run on blockchains or distributed ledger technology (DLT). An example of a smart contract using DLT is a cryptocurrency, such as Bitcoin. Ethereum is one of the largest platforms for smart contracts and blockchains. 

Blockchain/distributed ledgers technology (DLT) 

Blockchain or distributed ledger technology (DLT) is a protocol for exchanging values or data over the internet, which does not require an intermediary. The protocol of blockchain technology is to create a shared, encrypted database of transactions and other information. Examples of ants and flocks of geese have been given to demonstrate what a perfect blockchain society would be like: decentralized yet coordinated. The technology is to establish an ever-lengthening chain of blocks of data. Each block has a compact record of validated transactions by participants in the blockchain, and the premise of the blockchain is that the information in the blocks is accurate. Once the transaction is validated and recorded, the stored record is irreversible. Blockchain initially referred to the database where all Bitcoin transactions are recorded and stored.


Innovation driven by new technologies is a fundamental catalyst for change within the financial sector, despite the initial apprehension it can provoke. The insurance industry is no exception to such transformative trends, embracing the concept known as "InsurTech." This report compiles a range of pertinent technologies poised to revolutionize the insurance landscape. It delves into the funding aspects of InsurTech, unveiling the active markets investing in start-ups and how insurers are collaborating with these emerging companies. The report includes case studies of pioneering insurance start-ups and explores the influence of blockchain technology, the sharing economy, robo-advisors, and data aggregation on the insurance sector. Furthermore, it investigates how insurers leverage technology to enhance compliance with regulations.

Innovation and new technologies have the potential to impact the market value of insurance companies and raise concerns related to competition policies. Tailored coverage and simplified claims procedures can extend financial protection to segments of society that previously lacked access. Regulatory frameworks, such as the regulatory sandbox concept adopted by various jurisdictions, may strike a balance between promoting competition and upholding prudential requirements. Nevertheless, ensuring equitable competition as solutions transition to the total market requires careful consideration.

Several areas warrant more excellent regulatory dialogue, especially as technology's transparency and effects on policyholder choices and rights remain unclear. The surge in personal data handled by insurers calls for scrutiny by regulators as the intended use of this data becomes increasingly blurred. Data aggregation introduces the possibility of specific population segments becoming uninsurable, making it crucial to consider how data is harnessed. The treatment of algorithms is another topic necessitating further discussion to ensure the validity of built-in assumptions and prevent unintended consequences. This is particularly relevant in ongoing risk management and internal controls for insurers. The overarching objective should be to ensure the fair treatment and adequate protection of policyholders in the face of uncertain implications brought by innovations and technologies.

Emerging markets, characterized by less established insurance distribution networks, may experience the most profound impact from innovation and technology. However, whether the market is developed or emerging, rigorous regulatory oversight is essential to safeguard policyholders' interests. Various regulatory approaches could be explored for InsurTech, not only within this context but also in the broader realm of FinTech.


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