In response to the current landscape, the emergence of insurtech solutions, facilitated by secure APIs, aims to address the persistent challenges and inefficiencies in the insurance market.
By leveraging advanced technology such as data analytics, automation, AI, and IoT devices, insurtechs are set to disrupt the traditional insurance model–to the benefit of insurers and consumers–by making it more streamlined and efficient.
Automation in Insurance Underwriting
One of the main challenges of the traditional insurance model is that it is highly inefficient. Particularly with insurance processes that are resource-intensive and tedious, like underwriting, slow turnaround times can frustrate consumers and cause them to seek out a competitor who can offer them a quote much faster. Efficient and accurate risk assessment adds time-consuming manual calculation to the process. For providers, this means the premium-to-yield ratio remains low.
With automation, insurers can make more accurate, data-driven underwriting decisions in a fraction of the time. These digital capabilities can help streamline insurance operations, reducing the manual efforts required to collect customer information, process applications, enter data into the proper systems, and perform risk assessments. Not only does this help insurers work faster and reduce operational costs, but it also helps assess risk more accurately and price premiums appropriately.
Big Data Analytics
Access to large amounts of customer data doesn’t provide much value if insurers don’t have the tools to efficiently process and analyze it. Data analytics makes it possible for insurers to derive insights from large, unstructured datasets in ways that would otherwise be impossible to do manually. It also allows individual user data to be used for making real-time decisions on offers and experiences to engage those particular policyholders.
As insurers begin to collect digital data from an increasingly large array of sources, such as social media, IoT devices, and more, identity solutions will enable better decision-making, more personalized offerings, fair premiums, and enhanced risk management capabilities.
AI and Machine Learning
The possible use cases of artificial intelligence (AI) and machine learning (ML) in insurance are growing by the day–from enhanced fraud detection to quicker claims processing. These technologies can help insurers automate routine tasks, power predictive modeling, and enhance decision-making through all workflows.
Overall, insurtechs that leverage AI and ML help insurers be more efficient with their resources, no longer reliant on manual efforts to aggregate, enter, and analyze data, process claims forms, or field general inquiries and requests that AI-powered chatbots can handle effectively. For policyholders, AI-powered identity solutions enable a more seamless, personalized, and convenient experience that can strengthen their loyalty to their insurance provider.
Embedded Insurance
Embedded insurance is a quickly growing market that’s helping to make the insurance uptake process much more straightforward and efficient for consumers.
Signing up for insurance can be a confusing and complex process that might deter potential customers. But, insurtech solutions partner with providers across different industries to embed insurance at the point-of-sale (POS) into existing purchase processes for products and services.
Embedded insurance bundles insurance add-on options into purchase experiences, making secure insurance coverage more accessible and streamlined. In practice, this might look like the option to add travel insurance to your purchase when booking a flight or when a property management company lets you opt-in to paying for renter’s insurance with your monthly rent payments.
Telematics and IoT Devices
The integration of telematics and IoT devices has been a significant evolution in insurance, powering real-time data collection. This includes advancements such as connected vehicles, smart home sensors, wearable devices, and more.
In turn, this technology enhances insurers’ abilities to create accurate policyholder risk profiles and tailor their premiums to their specific behaviors. It can also work to mitigate risks and prevent potential property loss. For instance, door or window sensors installed in a policyholder’s home can detect if they’ve been opened or closed, alerting the homeowners that there’s been a possible break-in attempt to help prevent the theft of their property and valuables.
Web 3.0
Web 3.0 technologies herald a new era in insurance, marked by decentralization, interoperability, and enhanced security. Decentralized platforms, powered by blockchain and smart contracts, automate insurance processes, from secure data collection & analysis, to policy issuance and claims settlement. Removing intermediaries streamlines critical processes like claims settlement and disbursement, policy issuance, and fraud detection without any human intervention. Tokenization adds another layer, enabling fractional ownership and increased liquidity of insurance assets.
Threat Identification & Mitigation
As technology becomes more embedded into modern insurance operations, insurers confront more risks such as malware, phishing, and insider breaches. There is a growing need for robust threat detection & mitigation solutions to ensure sensitive customer data remains secure and help insurers stay compliant with industry regulations.
By nature, the data insurers collect, use, and store is highly sensitive, including policyholders’ financial data, health information, and in the case of telematics, their geolocation. A potential data breach would be devastating for insurers, so the deployment of advanced identity-enabled fraud prevention solutions are vital to safeguard customer data, ensure compliance, and maintain trust in the digital insurance ecosystem.