Automobile Insurance, Insurance Technology
Article | December 19, 2022
It is common knowledge that there is virtually no industry that has been immune to the effects of COVID-19. The global pandemic has caused massive shifts in individual and industrial behavior and will continue to do so in the months, if not years, to come. The P&C industry, like many others, is reeling from the effects of the virus. Amidst all these events, it is important to assess how the insurtech industry is going to be affected by COVID-19.
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Insurance Technology
Article | July 13, 2022
The rise in remote work during and after the pandemic has increased cyber vulnerabilities significantly.
Cyber insurance protects your company from the financial consequences of cyber threats or data breaches involving computer systems and data. Credit card numbers, social security numbers, account numbers, health records, and driver's license numbers are examples of sensitive customer information.
According to a recent SBA survey, 88% of small business owners believe they are vulnerable to a cyberattack. If your company is a victim of cybercrime, the cost of recovery can be prohibitively expensive, including specialized repairs and legal fees.
One of the most difficult challenges is quantifying cyber risk. Although approaches and frameworks like NIST CSF, CIS 20, NCSC Cyber Essentials, and ISO 270001 aid in the development of cyber security capabilities, they do not provide the tools to quantify risk. As a result, leaders frequently overestimate their cyber maturity while underestimating cyber insurance premiums.
Potential Cyberattack Types are:
Breach of data: A breach occurs when critical information, such as personal financial information, is stolen.
Cyber-attacks on computers:Your computer system is hacked and compromised in this type of cyberattack.
Extortion via the internet:During an extortion threat to your company's computer system, thieves may demand ransom payments.
To address these issues, a variety of approaches can be used, ranging from zero-trust models to multi-factor authentication (MFA) and end-point detection and response (EDR) (EDR and XDR). Protective monitoring, encryption applied to the most critical aspects of your network, and patch management processes can also provide insurers with the assurance they require.
There are options for both small and large amounts of cyber liability coverage. A small cyber liability insurance policy could be added to the policy of a business owner. A larger cyber liability policy with higher limits would necessitate its own policy.
Furthermore, they provide a real-time view of compliance through a risk-based approach that is consolidated, consistent, and aggregated across the entire organization. Workflow automation can help the IRM system become more efficient.
By consolidating your risk management processes, you can ensure that controls continue to deliver on their objectives and demonstrate compliance with policies, standards, and regulations while having a lower impact on your day-to-day operational demands. All of this will make it easier to meet cyber insurers' requirements and give organizations confidence that their policy will protect them when they need it.
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Core Insurance, Risk Management
Article | September 22, 2022
In the insurance industry, artificial intelligence (AI) has become a buzzword. Nonetheless, despite the fact that we are still in the early stages of AI implementation, the industry has made significant progress.
The Need for AI in Insurance
Insurance is a long-established and highly regulated industry. Perhaps as a result, insurance companies have been slower to adopt technological change than other industries. Insurance is still dominated by manual, paper-based processes that are time-consuming and necessitate human intervention. Even today, customers must deal with time-consuming paperwork and bureaucracy when filing a claim or enrolling in a new insurance policy. Customers may also pay more for insurance if policies are not tailored to their specific needs. Insurance is not always a pleasant customer experience in an age when most of our daily activities are online, digitized, and convenient.
Having said that, we are beginning to see a global push by insurance companies to enhance their technological capabilities in order to do business faster, cheaper, and more securely. There have been several notable examples of insurers investing heavily in Artificial Intelligence solutions in recent years.
If AI technology is fully applied to the insurance industry, McKinsey estimates a potential annual value of up to $1.1 trillion.
How are insurers implementing AI?
There are numerous examples of insurers around the world using AI to improve both their bottom line and the customer experience. There are also a slew of start-ups offering AI solutions to insurers and customers. I'll discuss a few interesting cases here.
The Future of Artificial Intelligence in Insurance
AI has the potential to transform customers' insurance experiences from frustrating and bureaucratic to quick, on-demand, and more affordable. Customized insurance products will attract more customers at lower costs. If insurers apply AI technology to the mountain of data at their disposal, we will soon see more flexible insurance, such as on-demand pay-as-you-go insurance and premiums that adjust automatically in response to accidents, customer health, and so on.
Insurance will become more personalized as insurers use AI technology to better understand what their customers require. By accelerating workflows, insurers will be able to save money. They will also discover new revenue streams as artificial intelligence-driven analysis uncovers new business and cross-selling opportunities.
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Insurance Technology
Article | July 14, 2022
The world is changing at a rapid pace, and no industry is immune to the need to evolve, upgrade, and innovate. The effects of mass digitization, artificial intelligence, machine learning, climate change, and the rise of financial-based cybercrime are all being felt in the business world. At the same time, consumer expectations have shifted dramatically, thanks in large part to companies like Netflix and Amazon, which have the technology and business models to provide the instant access to products and services that today's consumers have come to expect. When these changes are considered, it becomes clear that no industry, not even one as traditional, robust, and stable as the insurance industry, can afford to stand still.
Trend 1: CARE-Based Distribution Channels
Insurance companies are engaged in a "digital arms race," rushing to equip their distribution channels with digital tools to improve customer experiences. While CARE is the core experience that most insurance companies strive to provide in both distribution and sales, few achieve it consistently.
Trend 2: Quicker Payouts
Pay cycle time is fast becoming one of the most important differentiators between insurance companies. The winners of the future will use insurance technology to help them resolve claims quickly, at the touch of a button.
To this end, companies are adopting AI-enabled tools to automate both estimation and inspection. Telematics insurance solutions are expected to provide greater levels of contextual information that will support the smoother, faster, and more comprehensive settlement of claims.
Trend 3: The Rise of Usage-Based Models
As the pandemic made consumers aware of the waste involved in paying for insurance on cars that sit unused in driveways, interest in usage-based insurance products skyrocketed in 2021. As the nature of work changes and many people's daily commutes become obsolete, winning insurance companies will offer products that are more in line with how their customers live today. Telematics devices will allow insurers to offer products based on how and how far users drive.
Trend 4: Intelligent Automation
For a long time, the insurance industry has been experimenting with automation. The first phase was robotic process automation (RPA), which was viewed as a way to speed up processes and reduce costs without requiring significant changes to the underlying applications. While this was effective at capturing low-hanging fruit—those ubiquitous repetitive steps that were an unnecessary feature of so many insurance processes—it never really attacked productivity and core functions that required automation.
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