Keeping up with InsurTech

Keeping up with InsurTech

Similar to other industries, the insurance industry is subjected to a wide array of changes driven by both business and technological forces fueled by innovation. This wave of change and innovation in the insurance industry, commonly cited as InsurTech, refers to the use of technology to squeeze out cost savings and effi ciency from the current insurance industry business model.

The emergence of InsurTech is mainly centered around the property and casualty (P&C) and health segments. InsurTech targets these segments due to the vast amount of policyholder data available, for example policyholder age, type of car, accident history and so on. Companies can now develop more analytics-based approaches to improve existing processes by combining this information with external data (social media, weather, etc.)

The surge of InsurTech startups prompted significant change in the insurance industry; companies are applying new technologies to the insurance value chain and incumbent insurers are reacting to changes in the competitive landscape. As a result, it is a burden to keep up with all these developments. This article sheds some light on the evolving industry and provides some background.

Meet the startups

In general, InsurTech startups apply advanced technology (e.g. smartphone apps, artificial intelligence/ AI, and cloud computing) to redefine the insurance/ risk management process and gain competitive advantages.

Furthermore, these startups exploit the traditionally poor customer experience by focusing on   highly engaging online acquisition and focused claims management that improve user perception and loyalty.

A barrier to entry for potential newcomers in the insurance industry is the high capitalization requirements.

Furthermore, capital is locked in for a longer period before obtaining the actual gains due to the nature of the business. As a consequence, startups are focusing on specific areas within the insurance value chain, instead of the entire value chain.

Startups are particularly targeting the non-risk-bearing areas of the insurance value chain. For example, optimizing front-end policy services and reducing interaction makes it easier, faster and more understandable for customers to find and select a suitable insurance product.

Streamlining back-end claim services and claims fulfillment by automating the claims handling process decreases the burden to submit, adjust, and pay claims. Startups that apply advanced fraud detection algorithms also decrease the chance of paying out erroneous claims.

Most importantly, startups want to improve the customer experience in order to maximize policyholder retention. Unlike front-end policy services, the focus is to encourage customer loyalty rather than loss mitigation.

Similarly, business intelligence innovation is used to reveal insights relevant for the insurance industry by analyzing existing and new data sources. The rise of InsurTech firms increased the importance of how companies provide insurance beyond the specific coverage.

Newcomers also reshape the existing business models

These companies improve the insurance value chain by incorporating new technology to provide a seamless customer experience. Moreover, these companies are reimagining insurance as part of the daily lives of customers.

This is in contrast to traditional insurance products that characterized insurance only as buying a policy at the beginning and submitting a claim at a later date. A majority of InsurTech companies believe that the biggest impact to the industry will come from creating new products in order to address the changing needs of the customer. As a result, they are introducing a vast array of products, such as a system that warns ships of nearby pirates or an app offering to buy sleepy drivers coffee on the highway, in an effort to decrease the cost of the insurance claims.

Below are two companies that illustrate how InsurTech reshaped the existing business model:

  • Lemonade is a P&C insurance company that uses AI and chatbots to deliver insurance policies and handle claims for its users. Proclaiming ‘instant everything’, Lemonade insures a customer in 90 seconds and pays a claim in three minutes.In addition, Lemonade’s  pricing scheme differs from traditional insurers as they keep a flat fee of 20% of the customer’s premium while setting aside the remaining 80% to pay claims and purchase reinsurance. Furthermore, unclaimed premiums go to non-profit organizations of the customer’s choosing in an annual ‘giveback’.
  • Metromile offers a ‘pay per mile’, or usage-based insurance, in which users are charged a flat monthly fee plus a fixed rate per mile fee. The fixed rate per mile fee varies according to location, driving experience, and other factors. The pricing model is intended to benefit low-mileage drivers. Metromile also has an automated claim service, which allows policyholders to file a claim entirely from their mobile phones or an online dashboard.

How disruptive technology is a key enabler

Insurers have long turned to predictive modeling as a means to maximize their profitability. As competition and price transparency increase, the penalties for pricing errors also rise.

These penalties include failing to attract new business, which can be due to overpricing or also due to attracting a block of unprofitable customers due to underpricing. Besides more accurate pricing, insurers are reducing costs by applying predictive modeling to fraud detection, claims handling expenses and loss reserving.

Many insurers acknowledged that both supervised or unsupervised machine learning (ML) can be used to build new types of high-quality models, leverage data, and identify new relationships between variables.

As a result, insurers are investigating the benefits of artificial intelligence compared to the traditional generalized linear models.

Currently, insurers are exploring the capabilities of more advanced models within the non-regulatory space. The non-regulatory space includes fraud detection, customer acquisition and customer turnover.

In order to fully explore the extent of machine-learning applications, insurers are transitioning to these new technologies and IT infrastructures, which entails investments in servers and cloud computing.

Furthermore, insurers are also aware of the need to ‘stay in control’, hence they are also enhancing their governance framework.Insurers are also considering how to construct a compliant and interpretable framework of advanced models within the regulatory space. Lately, they started applying advanced models as a starting point to determine the most relevant explanatory variables.

Afterwards, these explanatory variables are then used in the existing generalized linear models for estimation.

What about blockchain?

As in other sectors, many in the insurance space believe blockchain technology¹ (in essence a distributed ledger) has a huge potential for insurers. Applications in the form of smart contracts based on blockchain technology extends to multiple objectives for insurers, such as innovating insurance products and services, increasing the accuracy of fraud detection, and reducing administrative costs.

A customer-controlled blockchain for identity verification or medical information would tremendously simplify the customer acquisition and onboarding processes. Blockchain could also record and validate contracts and claims within a blockchain network to verify policyholder identity and confirm only valid claims are paid.

An auditable registration of claims and data from third parties, and pay-outs for claims via a blockchain-based payment infrastructure or smart contracts, would enable reinsurers to have access to claims and claims histories registered on the blockchain. This improves the transparency for the reinsurers in an automated and auditable way.

The implementation of blockchain within the insurance industry has a long-term horizon. Because blockchain functions in a distributed system, its added value mostly depends on collaboration with competitors, suppliers, or others.

Old dogs, new tricks?

One of the main advantages established insurers have is large amounts of detailed risk data collected over many years used for underwriting and pricing. However, this competitive advantage is diminishing, as the type and amount of alternative, readily available data relevant to insurers continues to increase.

In response to these developments, many incumbent insurers are shifting their consideration of InsurTech startups from competitors to partners. Insurers are teaming up with startups and players outside the insurance sector to accelerate digital innovation through in-house incubators, accelerators, and innovation labs. The startups benefit from established technical support, guidance, and connections to industry experts.

Aside from partnering with startups, other incumbent insurers are putting their capital to use by forming corporate venture capital arms to invest in InsurTech firms. Investing relatively small amounts in multiple startups gives incumbents access to potential breakthroughs in numerous areas of interest to them.

While many insurance companies are jumping into InsurTech investments, many also are not. Some companies, especially small- to mid-size insurers, do not have the funds to invest and will have to wait until the innovations are proven and widely available. By then, of course, it may be too late for them to gain any advantage.

Conclusion

Disruption is frequently used in conjunction with innovative developments. Most of this hype is centered around the latest technologies and applications, however, these innovative solutions have yet to gain noteworthy traction. In order to truly disrupt the industry, being new and innovative is not enough.

Disruption requires adoption at scale. The insurance industry has taken notice of these developments and insurers are mobilizing their efforts and capital accordingly. Insurers are considering developing capabilities internally, partnering with startups or acquiring these smaller companies.

As insurers are slowly assimilating to the changing environment, they will become more data and technology driven. A consequence of digitalization will be an expansion of the model landscape for insurers, as new (AI) techniques enable insurers to improve their service offerings and internal processes, while achieving cost reduction. This creates a demand for a range of services, such as IT solutions, model development, advanced governance and model frameworks.

¹ A distributed register to store static records and/or dynamic transaction data without central coordination, i.e. by using a consensus-based mechanism to check the validity of transactions.