Insurance gets a digital makeover

Keletso Mpisane, MiWay Blink

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Before launching Naked Insurance, Ernest North and his co-founders worked in traditional insurance businesses and had witnessed first-hand where these companies were failing consumers. The thinking around the move to start Naked, says North, was that consumers’ needs are changing and the industry needed to keep pace. “For a long time, we were advising insurers that a fundamental overhaul was needed. The more we worked with these traditional players, the more we realised that their gradual approach to the transformation of their legacy systems and processes was simply not going to cut it because technology was moving so fast that they’d never be able to keep up.”

Consumers don’t want to sift through paperwork, or wait several weeks for their cover to be approved. They also don’t want to pay a monthly premium for something they only use every other week. They want freedom, flexibility and transparency, and they want their cover to be suited to their unique needs, says North. Insurers are now able to offer consumers a bespoke, self-service experience and do so more affordably, he says, adding that much of Naked’s offering is automated. “Everything happens online, from risk assessments and issuing policies to claims and payments without any need for human intervention. This means that we can dramatically reduce our backend costs and then pass on these savings to our customers by offering them lower premiums,” he says.

Price is a big differentiator, he adds. When people want to cancel their policy, the call centre agent will try to persuade them to stay with the lure of reduced premiums. “Let’s be honest, a significant portion of the traditional insurer’s profit sits in this practice of purposefully overcharging the 90% who aren’t threatening to leave and then offering a marginal discount to the 10% who are.”

Because digital insurers put control in the hands of their customers, making it easier for them to pause their cover or cancel their policy, it’s essential that they charge the most competitive rates, or their customers will take their business elsewhere.

The shift in customer expectations is compelling the incumbents to overhaul their approaches so they can deliver personalised and data-driven solutions.

For Francois Petousis, CEO of Lumkani, technology is useful for identifying gaps in the market. According to the FinMark Trust’s 2023 consumer review, the formal insurance market has grown only 2.3% in the last 20 years, while the informal market has grown by 112% during the same period.

Lumkani offers a bundled product – a smart fire detector coupled with home and business insurance, with the goal of safeguarding people and businesses living and operating within informal settlements from losses caused by fires. But in order to make fire insurance more accessible to informal homeowners, Lumkani had to innovate on many levels, he says.

Understanding the complexities of insuring individuals and businesses living in informal settlements, Lumkani developed a networked fire detection system that is now installed in over 65 000 homes in South Africa. The fire detectors are connected, he explains, so when one picks up a fire that’s just started, it alerts fire detectors within a 60-metre radius to create a communitywide call to action to deal with the fire before it gets out of control.

Petousis says its system has reduced the loss of property, and the risk reduction allows Lumkani, underwritten by Hollard, to offer fire insurance at a more affordable premium. For its customers, he says, getting claims assessed rapidly and accurately is important because fire victims are often left with nothing but the clothes on their backs. To speed up the process, Lumkani uses multiple data points, such as fire detector alert data to assess how the fire started within the home, layered voice analysis to quickly manage fraud detection and pre-existing evidence of contents to speed up proof of loss and assets.

This drive to speed up the claims process is also something King Price is trying to do with its implemented data-driven write-off model. The model, says Erik Redelinghuys, predictive analysis partner at the company, predicts whether a car that was in an accident should be written off or not. The aim is to make the process simpler for clients and to utilise the organisation’s resources more efficiently. “By looking at the accident conditions and the damage, as well as the potential salvage value we can recover, the model predicts whether it’s smarter, faster and more cost-effective to write off a car sooner. Speeding up the process makes it easier for our clients to move on from an accident and start their search for a new car sooner,” he says.

A significant portion of the traditional insurer’s profit sits in this practice of purposefully overcharging the 90% who aren’t threatening to leave and then offering a marginal discount to the 10% who are.

Ernest North, Naked Insurance

Usage-based insurance products turn the stock-standard monthly insurance premium on its head by offering customers the option to pay lower premiums for items that they use infrequently. These policies are ideal for motorists who drive their cars only on weekends or travel short distances, or for the mountain biker who only takes his bike out once a month.

Blink is MiWay’s pay-as-you-drive offering, says Keletso Mpisane, head of MiWay Blink. The increased use of telematics made it possible for MiWay to launch the product, which monitors usage in real-time and then offers monthly cashback rewards for the kilometres customers don’t drive, she says. Using telematics, it also monitors driving behaviour and rewards good behaviour. MiWay has also streamlined the car inspection process so that new customers no longer have to visit an inspection centre when taking out insurance. Customers use their cellphone camera to do a self-inspection, following the steps on the Blink app.

King Price is doing something similar with its pay-as-you-farm agri insurance product, says Redelinghuys. By attaching a tracking device to each farm vehicle, King Price can monitor when assets are in use and then offer a rebate to farmers for the time that the equipment is sitting idle. So that harvester that a farmer only brings out for a few weeks of the year can still be covered, but at a lower cost.

Naked has uncovered some trends around when people search for insurance quotes and they can use these to inform how they communicate with, and sell to, existing and prospective customers. Says North: “With a digital provider, you can get a quote whenever it suits you. Of consumers who seek a quote from Naked, 54% do so outside of regular working hours when most insurers’ call centres are closed. And nearly 22% request a quote over the weekend. Around 7% are night owls or early risers who are searching for insurance quotes between 11pm and 6am.”

For modern insurers, this kind of data unlocks new insights. The magnitude of information they have about each customer allows them to make risk assessments that are more granular and accurate, says North.

This applies to onboarding new customers and when processing plans. When a traditional insurance company needs to make a decision to accept or reject a claim, the information it has is based on between 10 to 20 questions the customer answered when they were speaking to the insurer over the phone. “So they have 10 or 20 data points to work with. Because every single one of our customers interacts with us exclusively through our digital channel, we have hundreds of thousands of data points to work with. Every single micro interaction is stored as a data point,” says North.

For Naked, this information means it can evaluate claims more accurately. In being able to accurately identify the tiny percentage of clients trying to commit fraud, it can flag these for further investigation and can quickly approve all the legitimate claims without inconveniencing customers.

SMARTER INSURANCE

GenAI promises great potential for the insurance industry because it’s able to analyse massive datasets, write personalised interactions and automate complex processes. The ‘South African Insurance Industry Survey for 2023’, from KPMG, outlines several examples of how GenAI is set to transform the industry:

• Claims processing: When GenAI is trained on historical claims data, it can quickly process and evaluate claims. Its natural language processing capabilities can be used to parse and interpret written statements and reports, extracting important details and cross-referencing them with policy terms and conditions to accelerate the claims review process and minimise the risk of human error.

• Underwriting: When GenAI is used to analyse large datasets, it can identify patterns and risks that a human might overlook, leading to more accurate policy pricing and risk assessment. It can also help underwriters make policy decisions that are consistent and fair.

• Fraud prevention: GenAI is able to identify complex patterns that human investigators or rudimentary algorithms might miss. It can spot recurring anomalies in claim submissions from specific regions, detect improbable sequences of events, or flag claims that match known fraudulent patterns.

• Visual representations of policy information: A challenge faced by insurance companies is ensuring that customers fully understand the scope and limitations of their policies. Textto- image and other AI capabilities can change policy communication, producing animations or infographics to transform terms into tangible images and graphs that are easier to understand.

• Customer support: GenAI can assist a policyholder looking for an update on the status of a claim by retrieving the latest information. And because it can communicate in multiple languages and adjust to suit varied comprehension levels, it can cater to a global audience.

• Marketing: GenAI can analyse customer preferences, purchasing behaviour and market trends. Using these insights, insurers can develop targeted and personalised marketing campaigns and craft messages that are applicable to specific demographics.

• Customer acquisition, retention and upselling: Insurers can target prospects with greater precision, offering policies that cater to their specific needs. Once customers are onboarded, GenAI will monitor interactions, feedback, changing life circumstances and new competitor offerings to predict when customers might be looking for cover elsewhere and then pre-emptively address their concerns.

• Identifying new claim patterns: Datasets can be used to unearth previously unidentified commonalities. When insurers understand what influences claim patterns, they can make more accurate risk assessments, and better tailor policy offerings.