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Cloud Computing Featured General Insurance

Cloud computing is a game-changer in redefining business operations and consumer interactions as the insurance industry undergoes considerable transition due to digitalization and client demands.

This article examines cloud computing’s potential in the insurance industry, going over its innovations, drawbacks, and possible advantages for both policyholders and insurers.

Innovations fueled by cloud technology

Numerous advantages of cloud computing are drastically changing the insurance industry. The following are a few of the biggest innovations:

Improved agility & scalability

Because of the adaptability of cloud infrastructure, insurers can modify IT resources in response to urgent demands, which saves money and improves their capacity to manage spikes in activity.

Simplified processes

Insurance procedures are streamlined by cloud-based solutions, which lower operating costs and frees up staff for higher-value jobs including underwriting, processing claims, managing policies, and providing customer support.

Better analytics & data management

Large volumes of data may be securely and centrally stored via cloud storage, which gives insurers the ability to create customized products, spot fraud trends, assess risk profiles, and launch focused marketing efforts.

Customer experience without barriers

Because cloud technology makes it easier to access policies, file claims, and handle payments, it may be used to create easy-to-use online portals and mobile apps that increase customer satisfaction and loyalty.

Working together & inventing

Cloud platforms provide open, creative environments for the rapid testing and implementation of new ideas, enhancing collaboration both within insurance businesses and with external partners.

Uncovering possibilities for a more positive future

The short-term difficulties are outweighed by the long-term advantages. By adopting cloud computing, insurance companies can take advantage of numerous advantages:

Tailored insurance items

Using consumer data and analytics, insurers can develop customized insurance products that support usage-based insurance models, in which premiums are determined by real risk exposure or behavior.

Instantaneous risk evaluation

Through the analysis of immediate information from connected gadgets and sensors, cloud-based solutions allow insurers to continuously assess risk, improving their capacity to provide accurate rates and even offer discounts for responsible conduct.

Quicker processing of claims

Cloud-based claims management solutions facilitate shorter resolution times and higher levels of customer satisfaction by automating repetitive operations and encouraging cooperation between adjusters and policyholders.

Improved fraud identification

Algorithms powered by artificial intelligence and machine learning can swiftly spot patterns of fraudulent claims, lowering insurer losses and helping policyholders with cheaper premiums.

Integration of emerging technologies

Cloud computing enhances risk evaluation, claims processing, and client service by integrating blockchain and IoT technology into insurance products.

The impact

Cloud computing is being embraced by the insurance sector to foster creativity, effectiveness, and customer-centricity. Driven by agility, data-driven knowledge, and value generation, this offers policyholders a secure, adaptable experience as well as a competitive advantage.

 

April 25, 2024
Business Featured General Insurance

Visualize all the grains of sand on beaches across Earth. It’s a number so big – roughly 2.5 quintillion to be exact – that we can’t imagine it in any meaningful way. But it’s also the amount of data that we generate every single day. That data, hidden in documents or flowing through the internet, is akin to the oil that revolutionized the 20th century; it drives our economies and powers our technological advancements.

And just as oil needed engines to transform raw power into usable energy, data requires analytics to unlock its potential. These analytics, the combustion engine of our era, turn vast, inert numbers into insights that propel us forward, shaping everything from daily decisions to global policies.

The insurance industry is no exception here. Big data and analytics have been fundamentally transforming how policies are priced, risks are assessed, and claims are managed. By harnessing vast amounts of data—from driving records to real-time health monitoring—insurers can tailor policies more precisely to individual risk profiles, enhancing both customer satisfaction and operational efficiency. With this in mind, let’s look at precisely how data and analytics are driving improvements in underwriting.

The challenge for underwriters

Underwriters face the daunting task of accurately assessing and pricing risks in a highly complex and ever-changing world. Traditional methods rely heavily on historical data, and while historical data has worked well enough for a long time, it’s not ideal. It’s far less useful at accurately predicting future risks due to emerging technologies, new medical advancements, and shifting social norms.

For example, how can historical data on human drivers anticipate the challenges and uncertainties presented by the rise of autonomous vehicles? Similarly, advances in genetics and personalized medicine are rapidly changing health profiles, which impacts life and health insurance industries in ways that past data cannot adequately forecast.

Furthermore, the sheer volume and complexity of data now available can overwhelm traditional analytical processes, making it challenging to identify relevant insights quickly and efficiently. These limitations can lead to imprecise risk assessments, mismatched premiums, and ultimately, financial losses.

How underwriters are leveraging big data & analytics today

So, that’s the challenge – historical data alone limits accuracy and efficiency in underwriting, but what’s the solution? You guessed it – big data and advanced analytics. Insurers are leveraging big data to assess a far bigger range of data sources and leveraging AI-driven analytics solutions to turn that data into meaningful insights.

More accurate risk assessment

Insurers can now access vastly more data sources than in the past, including public records (like driving violations and property details), data from connected devices (such as telematics for car insurance and wearables for health insurance), and social media insights. This rich, diverse dataset allows for a more detailed understanding of an applicant’s risk and offers many benefits, including:

● Fairer pricing: More accurate risk profiling leads to lower premiums for lower-risk individuals, making insurance more affordable for those less likely to file claims.
● Better risk selection: Enhanced data analysis helps identify high-risk applicants, allowing insurers to better manage their risk pool.
● Reduced risk of fraud: Cross-referencing data points helps uncover inconsistencies in applications, thereby mitigating potential fraud.
● Predictive modeling: Advanced analytics can go beyond static profiles and predict future behavior. For example, telematics data might indicate a driver with a higher risk of accidents, allowing insurers to offer targeted safety resources or adjust premiums accordingly. This can help prevent accidents and ultimately reduce costs for both insurers and policyholders. And these models become even more accurate over time as more data is fed to them.

Automated underwriting decisions

Big data and analytics go hand in hand with automation. Here, automation and AI are primarily used in decision-making processes for straightforward, low-risk cases. This automation not only speeds up the underwriting process but also allows human underwriters to dedicate more time to complex or unusual cases where personalized attention is crucial. The result is a more efficient overall process with improved turnaround times for customers.

And statistics back this up. A study published in McKinsey found that leading insurers who built advanced data and analytics underwriting solutions saw business premiums increase 10 to 15 percent. They also saw loss ratios improve by three to five points, and retention in profitable segments surge up to 10 percent.

Staggeringly, it’s estimated that with advanced automation (ones that leverage machine learning models), an eye-watering 95% of policies go straight through processing without underwriter involvement. No more waiting weeks for a decision.

Dynamic pricing

Dynamic pricing models allow underwriters to adapt premiums based on a customer’s current behaviors or circumstances. For example, usage-based car insurance policies leverage telematics data to offer a “pay-as-you-drive” model. Premiums are adjusted based on actual driving behaviors, rewarding safe driving and creating financial incentives for risk reduction. This not only makes insurance pricing more personalized but also encourages better behavior among policyholders.

Benefits for underwriters, but benefits for customers too

Here’s the bottom line. Big data and analytics undoubtedly help insurers avoid financial loss. More efficient profiling through data analysis means more time and less human error for underwriters. They can focus on complex cases and customer service, rather than getting bogged down in manual data processing.

However, that’s not to say the benefits lie solely with underwriters. Customers also reap significant advantages. More accurate profiling means fairer pricing for policyholders. Insurers can identify lower-risk individuals quickly and accurately and offer competitive premiums, reflecting their actual risk profile.

And big data also opens the doors for highly personalized coverage. Data allows insurers to offer tailored insurance products that better meet individual needs. For example, a homeowner with a robust security system might qualify for a discount on their property insurance.

Final thoughts

Big data and analytics are no longer a futuristic vision, but the essential tools driving the insurance industry forward. By harnessing the power of vast datasets and sophisticated analytics, insurers can create a win-win situation for both themselves and their customers.

April 23, 2024
Featured General Insurance

In 2023, heatwaves that broke records hit the US and the EU, wildfires tore across Mediterranean countries, and East Africa was hit hard by flooding. $250 billion is the overall cost of the losses and damages.

The Loss and Damage Fund (L&D), which was established in 2022 during the United Nations Climate Change Conference (COP27) was designed to help developing nations recover from climate-related calamities. But barely $700 million had been promised by COP28 in 2023. By 2030, the L&D Fund is expected to have an annual shortfall of up to $400 billion due to the growing speed of climate change, with promises covering less than 0.2% of losses.

The need to create financial frameworks that can invest in catastrophe and climate resilience while reducing recovery costs and dependency on underfunded L&D structures is thus becoming even more imperative.

There remains a gap in the funding required to engage in mitigation and adaptation strategies compared to the insurance systems in place today. Increased coverage across all industries is widely required, as seen by the surge in premiums caused by rising climate-related risk.

Home insurance

The average rate for home insurance increased by over 24% over the previous year while big insurers like State Farm and Allstate left California and Florida.

Utilities wildfire insurance

With the ability to pay only $11 billion of the $30 billion in damages it was liable for during the height of the 2019 wildfires, Pacific Gas & Electric Corporation (PG&E) filed for bankruptcy protection. The California Commission granted PG&E permission to establish two Risk Transfer Balancing Accounts, one for general liability and the other for wildfire liability, in response. While Southern California Edison chose to self-insure rather than renew its customary $1 billion policy, PG&E insured around 80% of its assets, valued at up to $750 million, to prevent a repeat of the financial turmoil of 2019.

Marine insurance

Drastic weather has drastically decreased the load capacity of Neopanamax, or larger ships, even with the $5 billion upgrade of the Panama Canal in 2016. The entire insured value of cargo traveling through the canal has decreased because of the capacity restriction, which has prompted a spike in container rates from $300 to $500 per container. Longer wait times and delays in the delivery of goods have resulted from this, which has influenced the entire supply chain.
The globe will see huge changes in risk and what is insured while new sustainable technologies are implemented, countries urbanize quickly, and the effects of climate change get worse. Insurance businesses have a special chance to organize fresh and creative funding sources that encourage resilience investments, resulting in increased stability over the long run and a variety of income sources.

In what ways may insurers improve their own long-term resilience by utilizing digital strategies?

Addressing challenges on a national level

Because of the hazards associated with climate change, major house insurers have pulled out of Florida and California, each state experiencing unique difficulties. Florida faces flooding risks, whereas wildfires are the main cause of risk in California. Furthermore, even within the same state, there can be large local variations in the hazards and long-term benefits of mitigation initiatives.

Insurers may find the best localized resilience alternatives on a national level with the use of new AI-driven digital tools that offer a shared toolbox of options made possible by unique customization capabilities at scale. With the use of these technological tools, insurers can recognize hazards and determine amounts of coverage that are both profitable and appropriate for hyper-local environments.

Additionally, as laws, financial models, and technology advance, digital Systems of Record become increasingly important to the upkeep of these national-level programs. The cost of resilience-enhancing and sustainable technology is falling dramatically, so investments might go from being unprofitable to being extremely profitable very quickly.

Enhancing risk evaluation

Better methods for gathering data can increase the accuracy of risk assessment because climate risk is a localized phenomenon.

The marine industry, for instance, frequently undervalues risks and uncertainties in particular regions due to present climate approaches. Ship operations in the Panama Canal are exposed to considerable climate-related dangers due to the increased frequency and unpredictable warmer temperatures that accompany El Niño periods. In contrast, ports in Asia might encounter fewer typhoon-related events, which would allow insurance companies to instantly modify rates to reflect increased risks.

Insurers can take into consideration regional differences in climate-related risks and modify premiums as these risks evolve by regularly collecting data and reassessing risk models during seasonal cycles.

Addressing and responding to climate challenges

Insurance firms can significantly impact how resilient assets are in certain areas, even if they decide to leave markets and geographic locations. Insurers can increase long-term profits by protecting income from these assets and drastically reducing costs associated with climate disasters by investing in adaptation measures in markets they would otherwise leave.

Insurers may be able to make significant investments outside of their typical coverage areas with the help of cutting-edge digital tools. For example, hundreds of miles away, people may suffer serious respiratory damage from wildfires, which can result in significant expenses for health insurance companies. But health insurers might benefit greatly from investing in wildfire mitigation, which is made possible by AI-driven geospatial tools that enable thorough area analysis.

These kinds of creative expenditures necessitate close coordination between companies that have historically operated in isolation. These barriers can be removed with the help of digital multi-player collaboration tools, which enable specialists from many fields to communicate with regulatory and financial stakeholders about a common plan and swiftly come to an agreement.

Both the public and commercial sectors must work together to reshape financial systems to increase investment and promote cooperation that will help us move closer to a future free from climate change. By enabling policyholders to invest in resilience and adjust to risk, insurers have a rare chance to develop new financing models that will improve long-term revenue streams and the viability of entire communities.

April 18, 2024
Automation Cloud Computing Featured General Insurance

As society embraces the digital age, the surge in data usage presents challenges for companies to maintain their vital information, programs, and systems on in-house servers. However, the solution to this dilemma, which has persisted since the internet’s inception, has only recently gained widespread adoption.

In recent years, cloud computing has transitioned from being a strategic technology to an essential one. The COVID-19 pandemic accelerated the adoption of a “cloud-first” approach across various sectors, including financial services and insurance. 

While insurers were initially skeptical about cloud computing, they now recognize its value and actively integrate cloud solutions into their practices.

Cloud computing in insurance

According to a recent study by Gartner, 78% of insurance companies have adopted cloud technology in some form. 

Cloud computing involves the utilization of remote servers hosted on the internet to store, manage, and process data, as well as to deliver computing services specifically tailored to meet the needs of the insurance industry. 

This approach replaces traditional on-premises infrastructure with scalable, on-demand resources accessed through the internet. 

Benefits

Cost efficiency

Cloud computing eliminates the need for upfront investments in hardware and infrastructure, allowing businesses to pay for only the resources they use on a pay-as-you-go basis. 

Add to that, Insurance-as-a-Service has gained popularity nowadays, as traditional insurers have turned to insurtechs like LenderDock to leverage the cloud computing capabilities to adopt new insurance environments. 

This helps in reducing capital expenses and converting them into predictable and manageable operational expenses.

Scalability & flexibility

Insurance companies can easily scale with the help of cloud-based solutions. This flexibility ensures optimal resource allocation, preventing over-investment during slow periods and enabling efficient management of peak periods. 

Additionally, cloud services allow flexibility in insurance processes and accessibility of business data and applications from any location which fosters collaboration and remote work, enhancing productivity.

Disaster recovery & business continuity

Cloud providers offer robust data backup and disaster recovery solutions, ensuring secure data backup and accessibility in case of disasters or outages. This minimizes downtime and maintains continuity of operations.

 Unlike traditional recovery methods, which are often complex and time-consuming, cloud-based systems streamline recovery with automated backups and rapid data replication.

Greater innovation & insight

With data stored in the cloud, insurance companies can implement tracking mechanisms and generate customized reports for organization-wide analysis. 

Cloud infrastructure also empowers insurers to swiftly develop and launch new products and services, eliminating the need for lengthy IT setup times. 

This agility is crucial in a competitive landscape where the speed of bringing products to market is of utmost importance.

Taking the initiative 

The post-COVID era we are now in has seen insurance companies and other service providers accelerating the shift to cloud computing.

Lemonade

Originally based in Israel, the insurance unicorn opened an office in USA but has now shifted most of its core operations to the cloud, hosted by Amazon Web Services (AWS). 

Cloud computing, coupled with their AI-powered chatbot, Jim, has enhanced customer interactions.

Allstate

Allstate has leveraged Microsoft’s Azure AI platform to adopt cloud-based solutions. By employing AI-based virtual assistants and predictive analytics, the insurance company has improved claim processing, personalized service recommendations, and risk assessment practices.

To sum it up

Cloud computing doesn’t just mean moving to the cloud. 

As you have seen in earlier paragraphs, for the potential of cloud computing to be realized, complementary technologies like Artificial Intelligence, Advanced Analytics, and Machine Learning should be developed in tandem with the approach. 

April 16, 2024
Automation Featured General Insurance

Insurance is defined as the pooling of resources by many to compensate the few faced with named risks. In legal terms, it is a contract in which the insurer agrees to indemnify the insured upon the occurrence of a specified event, in return for a payment called premium. 

Like many contracts, terms and conditions are stipulated to govern it. But with the advent of technology, today, the insurance contract can be entirely digitized. This allows for entire processes like claims to be done autonomously. The technology making all this possible is blockchain.

Smart contracts in insurance

From policy issuance, claims settlement, and even premium payments, smart contracts can automate all insurance processes with the help of blockchain technology. 

This is because they are self-executing, meaning they perform a task, like releasing insurer’s funds for a claim settlement, upon satisfaction of a pre-coded condition, like approval of a claim upon evaluation.

Smart contracts are coded on a distributed ledger system like Ethereum, making it possible for anyone to verify the transaction. How? The record of all transactions is replicated in full on each participant’s computer. This makes them highly transparent, as everyone has a complete, traceable record of every transaction recorded on the blockchain.

Insurance can benefit from smart contracts through:

 1. Automated claims

Smart contracts streamline the claims process by automating it based on predefined conditions. For example, in homeowner’s insurance, if an earthquake occurs, the smart contract can trigger the claims process without manual intervention. It verifies coverage, assesses damage, and can even facilitate claims settlement.

 2. Enhanced risk assessment

Smart contracts, with the help of blockchain, predictive analysis and IoT devices, can greatly improve the process of identifying potential risks posed by prospective customers. 

Some health insurance programs today utilize smart contracts to monitor policyholders’ real-time health data from wearable devices. If certain health metrics indicate an increased risk, the smart contract can adjust the premium accordingly or trigger preventive measures such as health counseling or lifestyle recommendations.

 3. Streamlined policy administration

Smart contracts can automate various aspects of policy administration such as issuance, renewal and modification. For example, when a customer purchases an insurance policy, a smart contract can automatically generate the policy document, record the transaction on the blockchain and initiate premium payments. 

Similarly, at the time of renewal, the smart contract can assess the policyholder’s claims history and adjust the premium accordingly.

 4. Better customer experience

By leveraging smart contracts, customers’ experience can be greatly enhanced, offering transparency, efficiency, and convenience. Clients can easily access their policy details and track claims status in real-time through a user-friendly interface. 

Furthermore, automated processes enabled by smart contracts ensure faster response times and resolutions, ultimately leading to increased customer satisfaction and loyalty.

Beyond the proof of concept

The implementation of smart contracts in the insurance industry is gaining momentum. With the potential to revolutionize traditional insurance practices, smart contracts represent a significant step forward in modernizing the industry.

Chainlink Labs

ChainLink enables blockchain-based parametric insurance applications to access real-world data, automating claims processing and reducing operational expenses. In instances like severe weather events, Chainlink retrieves pertinent weather data to validate and automate compensation disbursements through an insurance provider’s smart contract.

Lemonade

Last year, 7000 Kenyan farmers received insurance payouts via the Lemonade Crypto Climate Coalition. Smart contracts on the blockchain were created upon enrollment in the parametric crop insurance program. At season end, yield data transmitted to smart contracts triggered instant payouts for crop failures due to adverse weather conditions. This has expedited claim settlements, eliminating the need for filing or human adjusters, thus reducing costs and processing times.

Insurwave

Insurwave is the world’s first blockchain solution for marine insurance, utilizing the Corda Blockchain. It connects clients, brokers, insurers and third parties via distributed ledgers, storing comprehensive data on identities, risks, and exposures. Seamlessly integrated with insurance contracts, Insurwave facilitates asset data management, links data to policy contracts, enables real-time processing of pricing and business changes, and validates up-to-date loss data notifications.

Bottom line

Smart contracts have revolutionized the insurance industry, transforming slow claims processing and lack of transparency in insurance into streamlined, automated operations. This transformation is exemplified by bold initiatives from major firms like Lemonade and IBM.

However, as with any emerging technology, it’s crucial to ensure that the benefits outweigh the drawbacks. Proper utilization of smart contracts requires smart and proper investment in understanding the underlying technology, namely Blockchain. In addition, thorough market research is essential to gauge readiness and reception.

April 10, 2024
Automation Featured General Insurance

Location intelligence and aerial imagery are relatively new ideas, but they are already proven to be very useful in helping insurers better understand what their customers need.

This technology uses geospatial information to give a more accurate picture of danger, going beyond simple zip code data. For example, real-time level data can help insurers figure out how likely it is that a property will flood or find infrastructure that has been updated or damaged. Putting together geospatial data with advanced analytics makes it easier for insurers to do their jobs by combining better underwriting and claims handling into a single framework.

Besides these improvements, new technologies offer something more to help insurance than just analyzing data. They allow consumers to get personalized safety advice, see changing claims visualizations, and keep an eye on risks all the time. It works out well for everyone: customers get better security and lower premiums, and insurers learn more about how their business works.

Property & casualty division

The P&C industry is about to go through a big change. Due to inflation, rising labor costs, staff shortages, and bad weather, premiums around the world are expected to rise to $10 trillion by 2030. Because of this upcoming financial milestone, insurers are putting money into new technologies like location intelligence to help them write more accurate plans. This method uses location data and pictures taken from above to see things that the human eye can’t. This gives us a complete and more correct picture of property risk, and it also encourages insurance companies to correctly price and quote property risks, which sets them up for success right from the start.

With location intelligence, insurers can control risk ahead of time to find properties that are likely to be damaged by natural disasters, crime hotspots, and other dangers. Think about flames as an example. For example, the defensible area around a property, the materials used on its roof, or the distance between buildings are all things that help insurers figure out how much risk a property is exposed to. When they have these exact insights, they can change policies, set prices and rates more accurately, and maybe even lower losses or stop them from happening. Ultimately, giving insurance accurate risk assessments leads to better customer service, more efficient operations, and higher profits in the future. More importantly, though, it becomes important for building a strong future.

Enhancing efficiency in underwriting & claims procedures

Underwriters can make sure they don’t miss any important areas by using specific location intelligence and checking to see if secondary structures change the risk criteria. Using geospatial data and aerial imagery together in this way speeds up the screening and claims management processes that are usually very slow. When underwriters learn about property risk, they learn about things like flood zones and how vulnerable the property is to bad weather like hurricanes, wildfires, and tropical storms. For example, when insurers use location intelligence, they don’t have to rely on old images and bad data to reevaluate the risk of flooding in coastal areas. After that, they can change the prices of their policies by combining current images, elevation data, and old storm records.

Also, this makes insurers work on loss control more effectively, making it an important part of the lifecycle of an insurance policy. When it’s time to renew, location intelligence can give insurance up-to-date information on properties, which makes it easy to spot any new risks. Innovative AI systems can find all of these new risks by pointing out things like property repairs, roof and property damage, and any additions or secondary buildings to properties.

Location intelligence is a very useful tool for adjusters who deal with claims. Location data can be used by adjusters to check details about an incident, like where a property is located, what features the land has, or how the weather behaves during a weather event. Insurance companies can easily compare pictures taken before and after a disaster to figure out how much damage was done and send help to the places that need it the most. This speeds up investigations, gets rid of pointless delays, and helps agreements be finalized faster in the end. It also adds a new level of openness and provides objective proof during the claims process, which is good for both the insurance and the insured.

Revolutionary technologies transforming the insurance industry & policy management

At the center of change in the insurance business are machine learning (ML) algorithms and generative AI. What do these tools have to do with location intelligence, though? One thing is that these algorithms can now quickly and accurately look at huge geospatial location records to predict possible risks. This feature makes it easier for location intelligence to make predictions. Location intelligence uses machine learning and generative AI to give real-time information about important property features like debris, roof state, and roof age.

Moving beyond traditional “one-size-fits-all” models, this process lets insurers make policies that change based on each person’s wants and habits. Moving from risk assessment to claim handling, for example, large language models (LLM) can speed up the claims process by automating the tedious tasks that come with it. A LLM can go through a portfolio and automatically take out data, which can then be put together into a full risk assessment. Because it handles administrative chores, speeds up document analysis, and makes communication with policyholders better, this automation lets insurers focus on the more strategic parts of their work. In addition, this automation increases the trust and accuracy of insurers throughout the whole lifecycle of a policy.

Nearly a trillion devices will be connected by 2025, according to experts. These technological advances are not only bringing the industry up to date; they are also changing what insurance means in a fundamental way. A change is happening from “repair and replace” to “predict and prevent” for more personalized risk management. These tech-based innovations can make insurance more useful, easier to get, and better for everyone.

There is no doubt that location intelligence is a powerful force that is shaking up the insurance business. When insurers use geographic data and advanced analytics, they not only improve their financial health, but they also make key processes run more smoothly and set a new standard for proactive, data-driven industry practices. As location intelligence and the technologies that go with it keep getting better, the insurance business will be more flexible, data-driven, and proactive in the future.

April 8, 2024
Featured General Insurance

In auto insurance, risk assessment has traditionally relied on demographics and statistical data. While this approach provides a snapshot of customers’ risk profiles, it’s not highly accurate as it relies on generic factors and historical data.

However, with advancements in technology, accessing real-time data and various risk-related information has become feasible.

Telematics, special sensors that collect and transmit driving behavior data in real-time, facilitate this process. Metrics such as driving speeds, braking patterns and cornering are transmitted at low latency to insurers, forming the foundation for risk assessment.

The mechanism behind

There are mainly two kinds of telematics technology used today.

Telematic-based devices uses special fitted devices to a vehicle’s OBD port while App-based telematics use special mobile apps developed by the insurer to capture data from a smartphone’s many sensors. Choosing one over the other depends on the insurer’s technological capabilities and financial resources.

Telematics technological aim to capture the driver’s habits and vehicle usage through:

Data Collection: Telematics devices gather driving metrics directly from the vehicle’s OBD-II port, including speed, acceleration, braking and GPS location.

Data Transmission: Collected data is transmitted via cellular networks to the insurer’s systems, enabling immediate access for analysis.

Data Analysis: Advanced algorithms analyze the collected data to create a detailed profile of the driver’s behaviors and associated risks like speeding or harsh braking.

Underwriting: Based on this analysis, insurers assess the level of risk posed by each driver they’ve insured for. Safer driving habits translate to lower premiums while riskier behavior may result in higher rates.

By customizing premiums based on individual driving habits, this results in more accurate risk assessment, leading to what is known as Usage-based insurance – where you only pay based on your usage – a trend that is really catching on nowadays!

Benefits of telematics to the insurance industry

 1. Risk assessment precision

Telematics allows insurers to assess risk with greater accuracy by evaluating individual driving behaviors. This enables them to offer personalized insurance premiums that reflect the actual risk posed by each policyholder.

 2. Promotes safe driving habits

By providing drivers with feedback on their driving performance and offering incentives for safe behaviors, telematics encourages safer driving habits. This not only reduces the likelihood of accidents but also leads to lower claim frequencies and costs for insurers.

 3. Fraud detection and prevention

Telematics data can be instrumental in identifying fraudulent claims by providing comprehensive insights into the circumstances surrounding an incident. Suspicious activities like sudden changes in driving patterns or discrepancies in reported incidents, can be flagged for further investigation, thereby reducing insurance fraud.

 4. Enhanced customer engagement

Telematics empowers insurers to engage more effectively with their policyholders by offering value-added services such as personalized driving insights, maintenance alerts and emergency assistance. This fosters stronger customer relationships and increases overall satisfaction.

Real-time examples of telematics implementation

Progressive Insurance – Snapshot

Progressive Insurance offers Snapshot, utilizing telematics to analyze driving habits. This innovative initiative allows policyholders to receive lower premiums for safe driving practices while adjusting rates for riskier behavior.

Allstate Insurance – Drivewise

Allstate Insurance has the Drivewise program, a telematics-driven initiative aimed at promoting safer driving behaviors among customers. Through real-time feedback and incentives like cashback rewards, Drivewise encourages policyholders to adopt safer driving habits, thereby contributing to improved road safety.

Travelers Insurance – IntelliDrive

Travelers Insurance introduced IntelliDrive, which customizes insurance prices based on individual driving behaviors. By offering savings for safe driving habits and adjusting rates for riskier behaviors, IntelliDrive aims to promote safer driving practices among policyholders while providing potential financial benefits.

In summary

Through the use of telematics, insurers can now personalize insurance premiums based on actual risk profiles, leading to the rise of Usage-based insurance.

With this trend, more audiences can be convinced to buy insurance, especially Gen Z and Millennials, since it not only promotes safe driving but also rewards policyholders with benefits like loyalty programs and discounted rates.

April 5, 2024
Featured General Insurance

Insurance has always been a game of data, and rightfully so! It operates on the principle of pooling risks, whereby various homogeneous risks from different individuals and properties are combined to compensate those who encounter losses from actual perils.

However, since risk is not certain, data (big data) is collected and analyzed to assess the likelihood of such events occurring.

Having vast amounts of data can be both a blessing and a curse for the insurance industry. With data analytics ingrained in core functions like underwriting, claims, and finance, it poses a significant challenge to utilize the data effectively and ensure that it yields valuable insights for decision-making.

This is where advanced analytics comes in.

Advanced analytics defined

Advanced analytics refers to the application of sophisticated computational techniques and algorithms to analyze large and complex datasets to extract valuable insights, patterns, and trends.

With the aid of machine learning, predictive modeling, data mining, natural language processing, and even statistical analysis, advanced analytics goes even further to forecast outcomes and recommend actions.

Top 4 uses of advanced analytics in insurance

  • Better customer experience

Advanced analytics allows insurance companies to gain deeper insights into their customers by analyzing customer data, including past interactions, preferences, and behavior patterns.

This enables them to personalize their offerings, tailor communication strategies, and provide more relevant and timely services.
For instance, predictive analytics can anticipate customer needs and proactively offer recommendations or solutions, enhancing overall satisfaction and loyalty.

  • Reduced fraud

Many insurers estimate that 10 to 20 percent of claims are fraudulent, yet they can detect less than 20% of these.

By analyzing vast amounts of data from various sources, including claims history, transaction records, and external databases, advanced analytics can identify suspicious patterns and anomalies indicative of fraudulent behavior.

Machine learning algorithms can continuously learn and adapt to new fraud schemes, enabling insurers to stay one step ahead of fraudulent activities and minimize financial losses.

  • Streamlined internal process

Advanced analytics streamlines internal processes within insurance companies by automating repetitive tasks and optimizing resource allocation. For instance, predictive analytics can forecast future demand for insurance products, enabling insurers to adjust their pricing strategies and underwriting guidelines accordingly.

Additionally, process mining techniques can analyze workflows and identify bottlenecks or inefficiencies, allowing insurers to reduce costs.

  • Data-driven decision making

Last but not least, advanced analytics empowers insurance companies to make data-driven decisions across various business functions like marketing, product development, and operational planning. By analyzing customer behavior, market trends, and competitor insights, insurers can identify growth opportunities, optimize product offerings, and allocate resources effectively.

Real-time analytics dashboards and reporting tools provide actionable insights to decision-makers, enabling agile responses to changing market conditions and customer needs.

Examples of advanced analytics in insurance

  • LexisNexis Risk Solutions

The software company, based in Alpharetta, Georgia, offers advanced predictive models and rules-based analytics that leverage vast data assets to help drive more objective underwriting and pricing decisions.

The firm works with several industries, most notably the insurance sector, and offers predictive underwriting, geospatial intelligence, and driver behavior scoring.

  • American Family Insurance

American Family Insurance uses Networked Insights which it acquired in 2017. Utilizing audience research, Networked Insights offers analytical insights that empower companies to make informed, data-driven marketing decisions, enhancing media efficiency in the process.

  • American Insurance Group

AIG’s Advanced Injury Analytics employs more than 100 time-sensitive formulas to consistently assess
claims as they develop, updating every 30 days to provide regular, timely insights into intricate cases.

It swiftly identifies severe injuries and directs the appropriate adjuster toward achieving the best possible outcome at each stage of the process.

Final thoughts

As insurance operates on the bedrock of data, the application of advanced analytics becomes indispensable in navigating the complexities of risk assessment, fraud detection, and enhancing customer experience.

Through the integration of emerging technologies like machine learning, predictive modeling, and many others, advanced analytics stands as a transformative force within the insurance industry, offering insights behind mere numbers.

April 2, 2024
Featured General Insurance

Knowing and being ready for the effects of natural disasters depends on a networked ecosystem based on reliable data and analytics. To better address the most urgent requirements in the event of a crisis, restorative measures can be implemented more successfully.

With its path of devastation across the United States, Hurricane Idalia last year caused around $2 billion in total insured losses on the private market, not to mention thousands of people’s hardships.

In 2023, the United States had numerous costly natural disasters, Hurricane Idalia being only one of them. There have been 28 documented weather-related or climate-related disaster incidents in the United States so far in 2023 that have resulted in losses more than $1 billion. This contrasts with the previous five years’ average of eighteen events per year that resulted in losses surpassing $1 billion.

The financial cost of these occurrences is enormous: this year’s catastrophes resulted in insurance claims totaling $92.9 billion in losses from, among other things, 19 strong storms, two floods, one tropical cyclone, one wildfire, and one winter storm.

Insurance companies all around the United States are vital to the process of rebuilding communities and reducing the actual and relative magnitude of damage that follows natural catastrophes, especially as the business deals with the aftermath of more and more weather-related incidents such as Hurricane Idalia. Insurance companies can no longer successfully respond to rising demand and workloads using traditional techniques.

The restoration efforts of insurers can be impeded by the time-consuming and difficult nature of legacy operations. They frequently entail laborious or repetitive work, which is particularly difficult given the severe labor shortages and high employee turnover that the property insurance and repair industries are currently facing as a group.

Additionally, as more insurance companies deal with a lack of workers and an increase in storm-related claims, they must be able to rely on cutting-edge solutions from throughout the ecosystem to help them accomplish more with less. In addition to compensating for a deficiency of human resources throughout the insurance supply chain, contemporary solutions allow carriers to concentrate more on assisting the individuals making the claims.

Cutting-edge advancements

To fully integrate their processes for best performance, carriers and contractors work together to resolve claims. To this end, all parties require advanced technologies. If carriers and contractors don’t have access to the newest advancements, they run the danger of using antiquated practices and ineffective technologies, which can prolong restoration project cycles and leave impacted folks without help.

Alternatives to the conventional status quo technologies, which frequently call for extensive human interaction, are becoming more and more popular. The most recent technologies offer AI-enhanced, data-driven strategies that help impacted communities recover more quickly. By collaborating with insurtech firms, insurance providers, and restoration contractors who are pursuing these more cutting-edge approaches, they can better navigate the changing landscape that is rife with issues like staffing shortages, employee turnover, and an increase in the frequency and intensity of natural disasters. For instance, carriers can control resource deployment to reduce fraud, increase efficiency, and shorten claims life cycles by utilizing extensive data assets and intelligent AI-driven technology.

High-quality data-enabled technology also makes it possible to forecast extreme weather events more accurately, allowing property owners to better protect their properties from the effects of natural catastrophes by identifying high-risk locations.

In any situation, carriers and contractors may fulfill their commitments to policyholders and achieve their business objectives with the support of an appropriate digital environment. Professionals in insurance and restoration are not only more productive and efficient thanks to technology; it also increases their ability to provide policyholders with individualized client experiences at critical times.

The essential human element

People encounter insurers during their most trying moments. Insurance professionals who deal with the public must put people first. A human-centered insurance industry uses the most recent advancements in artificial intelligence (AI), machine learning (ML), and data analytics to provide customers with streamlined services both before and after an occurrence, including quick, focused restoration. AI-driven technology and automation also free experts from manual, repetitive chores, giving them more time to concentrate on the people who create the policies. Professionals can spend more time assisting people in rebuilding their lives if they spend less time on tedious duties like updating records, discovering networks of contractors, and going through papers.

Insurers need to provide individualized client experiences and human engagement based on specific demands when communities are devastated. This can only be accomplished by utilizing cutting-edge, contemporary technical advancements.

To have a functional integrated ecosystem, insurance carriers need to strategically implement cutting-edge technologies. To ensure that all users and stakeholders have access to the most recent information regarding each policy and claim, an integrated ecosystem is a digital architecture made up of technologies that link and share data. In addition to helping communities recover and rebuild after disasters, this helps insurers to focus their efforts and show compassion while offering individuals consistent, straightforward experiences during otherwise confusing periods. What advantages do homeowners receive from tech-forward insurance specifically? They provide innovative services.

To provide families with the prompt confidence and support they require after a tragedy, forward-thinking businesses can provide explicit service level agreements with well-defined objectives and timetables.

Preparing for disasters and mitigating losses

As crucial as it is to mobilize efficient recovery mechanisms, property owners and the insurance companies also need to be proactive in anticipating and mitigating the extent and magnitude of any severe weather-related disaster. Insurance companies with risk-aware staff members are better able to build policyholder trust and proactively prepare them for catastrophe. By comprehending risk and property vulnerability, carriers can also better design their catastrophe response protocols.

Risk reduction is aided by an abundance of property data. Examples of data from which actionable insights can be extracted are market listing, geographic, building permit, occupancy, crime, demographics, mortgage transaction, construction cost, natural hazard risk, and catastrophe modeling data.

For insurers, assembling, integrating, and validating the numerous underlying data sources is a greater difficulty than simply gaining access to the data. This is the situation when obtaining the degree of detail in data needed for individual property insurance.

Data analytics businesses have created risk models with the required level of granularity and regular updates using AI and ML, making them dependable sources of information for insurers. Insurance companies can use this information to proactively contact policyholders who are literally in the line of fire.

Insurers can obtain detailed information about the risks associated with areas by adopting a data-led approach. Having the required quick reaction mechanisms in place allows them to underwrite policies more successfully. Using AI and ML-powered technology, insurers can more effectively evaluate risk and related mitigation measures at the property level, automate and streamline workflows for maximum efficiency, maintain open lines of communication with policyholders, and comply with regulatory requirements with ease.

Prioritizing people

Meeting the evolving needs of homeownership will fall to those operating throughout the insurance ecosystem as climate risk rises. Despite the common misconception that technology is impersonal, the truth is that with the correct data and technology, providers may devote more time and resources to their clients, resulting in a truly human-centered experience.

March 26, 2024
Business Featured General Insurance

As the insurance sector enters the Insurtech 2.0 age, carriers need to create a flexible, innovative business environment.

As more and more consumers become tech-savvy, the insurance sector has witnessed a shift in consumer preference toward self-service portals. Over the course of the last five years, the percentage of claims processed digitally through automated processing and through mobile apps has climbed from single digits to 55%.

Insurance firms are faced with an evolving trend that requires them to retain personal engagement with clients during crucial moments while optimizing the benefits of digital tools. In addition to facilitating their workflows, digital solutions enable insurance agents to enhance their client experience services.

To meet customer expectations as the insurance industry enters the era of Insurtech 2.0, a journey driven by digital experiences, insurers should construct a strong digital system, make use of cutting-edge capabilities from ecosystem partners, and optimize their distribution channels.

Embrace digital platforms for investment

Using digital platforms, insurers may improve accessibility and convenience by enabling customers to purchase, renew, and manage their policies online. The Gen Z and millennial populations are accustomed to this kind of frictionless, user-friendly, and streamlined service from their insurers. Gen Z, who are digital natives with 95% of them possessing mobile devices, exhibit tech savvy in how they interact with insurers and buy plans.

With a templated approach to allow varying degrees of customization, low-code and no-code solutions on the backend of these platforms are accelerating the delivery of digital apps for insurers. Companies can create customized platforms by simply dragging and dropping the features they require to meet different needs.

Collaborate with pioneers in the Insurtech ecosystem

Insurtech ecosystem partners have caused a major upheaval in the insurance industry by bringing their creative and agile digital-first solutions into fundamental systems to meet changing client expectations. Insurtech platforms, for instance, facilitate the easy access, integration, and analysis of data across many business lines by insurers through their data analytics capabilities.

Precision in risk assessment and management for properties is made possible by geospatial data, while actionable insights are unlocked and improved emergency management and decision-making are facilitated by radar and satellite data.

A further illustration would be the expanding use of embedded insurance. In response to the growing gig economy, some businesses are providing insurance to drivers via meal delivery apps so they can reach their clients wherever they are. Consumers’ daily lives are impacted by the use case. Over 30 percent of insurance transactions will take place through embedded channels in the next five years.

In addition to improving customer satisfaction, insurers can open new growth potential by partnering with insurtech businesses in ways that benefit both parties.

Enhance traditional distribution channels using digital technology

By utilizing digital tools, insurers may improve their current distribution channels and enable agents and brokers to provide noticeably better client service. Online quoting and policy binding is one such tool that helps insurers stay efficient even as they transition to the self-service model.

Simplified communication between clients, brokers, and agents is made possible by digital tools, which enhances customer satisfaction and may even raise retention rates. Insurance companies that provide digital tools to their intermediaries are better positioned to hold onto their market edge.

Anticipating the future

Older customer generations won’t be left behind in the shift to digital self-service. To help customers navigate this new digital self-service paradigm, insurers must offer customer education and support. They also need to place staff members in the best possible positions to assist those customers who need to speak with an expert.

Insurers may contribute to the development of an innovative and adaptable insurance market as digital transformation progresses and cutting-edge technologies such as generative AI gain traction. Digital tools enhance the human element of insurance by comprehending the needs of policyholders and offering customized coverage, creating an experience that is streamlined and motivated by empathy.

March 22, 2024
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