Is it just me, or did the world we live in pick up the pace even more? Innovations and technological advancements seem to be popping up left and right across every sector.
Take insurance, for example. A while back, I discussed how Open Insurance and FIDA are reshaping the insurance field. This typically data-reliant industry is undergoing yet another radical shift. This time, the culprits are edge computing and edge AI.
Without further ado, let’s shed some light on these cutting-edge technologies that are shaking things up in insurance.
- Edge Computing and AI: A Powerful Duo in Insurance
- The Impact of Edge Computing and Edge AI on Insurance
- What Are Some Potential Cost Savings of Using Edge Computing in Insurance?
- Data Reliability Issues in the Insurance Industry
- How Can Edge Computing Improve Data Reliability in the Insurance Industry?
- How Edge Computing And Cloud Computing Complement Each Other in Modern IT Infrastructure
- Edge Computing & Edge AI in Insurance – Wrap-Up
Edge Computing and AI: A Powerful Duo in Insurance
What is edge computing in the first place? Edge computing refers to a technology model that entails processing data on nearby devices, including IoT ones or sensors, instead of sending it to a centralised cloud or data centre. In simple terms: edge computing is all about distance and speed, ensuring that data is processed as close to its source as possible.
Add artificial intelligence to this, and you end up with edge AI. Think of it as a seamless extension of edge computing. It integrates artificial intelligence algorithms into edge devices. And because edge AI can process data locally generated by IoT technologies, it spares us the need for constant connectivity. As a result, we get more precise, responsive, and customised insurance services.
The Impact of Edge Computing and Edge AI on Insurance
Data processing is not the only aspect of insurance that edge computing and edge AI reach. These technologies’ benefits go far beyond that, embedding themselves into the fabric of insurance operations. Why don’t we take a closer look at some of them?
Real-time Data Processing and Decision-Making
Processing data and making decisions has never been easier. Edge computing proves just that, allowing insurance companies to perform these tasks closer to the source without having to stay connected to the cloud all the time. Not only does this reduce reliance on cloud infrastructure, but it also boosts data processing speed and efficiency. In the end, this results in more agile and responsive operations.
Enhanced Operational Efficiency
Insurers surely appreciate edge AI’s usefulness in automating operations, be it risk assessment, claims handling, and other back-office processes.
Elevated Customer Experience
Along with edge AI, edge computing is also making an impact on customer service. With AI-powered chatbots and virtual assistants, we’re looking at a complete redefinition of customer interactions. These tools can handle inquiries directly on the device and even offer “smart coaching” to insurance agents to provide better service.
Revolutionised Claims Processing
Claims processing, once known for its tedious and time-consuming nature, is undergoing a major makeover courtesy of edge computing. By automating claim assessment and document processing, edge computing speeds up the resolution process a lot. Its accuracy in detecting inconsistencies and potential fraud is second to none. This leads to reducing operational costs and enhancing customer satisfaction.
Improved Risk Assessment
When it comes to risk assessment, edge computing probes massive datasets, recognising patterns and risks that traditional methods miss out on. Talk about precise predictions and tailored pricing.
Reinsurance Sector Transformation
Yet another aspect of the insurance industry where edge computing comes in handy is the reinsurance sector. This technology enables more thorough market analysis and risk evaluation by effectively managing large and diverse datasets. Thanks to this strategic use of edge computing, reinsurance companies can provide their clients with better solutions, keeping up with their changing needs and expectations.
Augmented Regulatory Compliance
Thanks to edge AI, regulatory compliance is also witnessing a transformation. Edge computing technology can help insurers tackle regulatory concerns about how AI models are interpreted and explained—a stepping stone to areas such as underwriting and pricing.
Reduced Costs and Improved Security
Within the insurance industry (or any other, for that matter), edge computing gives a significant boost to cost reduction and security enhancement. Processing data locally on edge devices allows insurers to cut down on bandwidth expenses, as well as improve data security by lowering the risk of sensitive information being exposed.
What Are Some Potential Cost Savings of Using Edge Computing in Insurance?
As shown above, one of the advantages of edge computing for the insurance industry is cost savings. How can this be achieved? No need to ask around. Here are some examples:
- Reduced Cloud Storage and Networking Costs: Since data processing occurs closer to its source on edge devices, insurers can trim the amount of data sent to the cloud for processing and storage. This is huge for cost savings on cloud storage and networking infrastructure.
- Lower Bandwidth Utilisation: With edge computing having their backs, insurers can sift through and process data locally before transmitting only the most crucial information to the cloud. This solution means reduced bandwidth usage; ergo, reduced costs for data transmission.
- Improved Energy Efficiency and Sustainability: Unlike traditional cloud-based processing, edge devices offer a greener alternative with their lower power requirements. This contributes to cutting down on carbon footprint, as well as energy bills for insurers. Promoting sustainability while saving costs—two targets with one shot.
- Faster Time-to-Market for New Services: Courtesy of the modular and flexible nature of edge computing platforms, insurers can swiftly introduce new offerings. This approach not only saves time but also reduces the costs and complexities of traditional IT setups.
- Reduced Reliance on Aftermarket Devices: Let’s take car insurance as an example. With vehicles’ onboard edge computing features, insurers can skip the extra step of using aftermarket devices (like OBD2 dongles) for usage-based insurance initiatives.
Data Reliability Issues in the Insurance Industry
In the insurance sector, ensuring data reliability is vital for effective operations. At the same time, it’s a significant concern since, in this field, data reliability issues occur quite commonly.
For example, within insurance companies, it’s common to find numerous legacy systems and databases, each storing identical data in different formats. This can lead to inconsistencies and discrepancies, particularly when integrating or cross-referencing the information.
Another issue is tied to insufficient client information. When it lacks accuracy, whether due to incompleteness or outdated records, it opens a door to hurdles such as fraudulent activities and inaccurate risk assessments.
Then, there are faulty claims investigations. Flawed or insufficient data poses risks to the integrity of claims investigations, resulting in misguided decisions and subpar customer experience.
That’s not all—numerous insurance companies operate without a solid structure for data governance and neglect routine checks on data quality. Consequently, inaccuracies and errors continue to plague their databases unchecked.
And that’s still not all—not when challenges with unstructured data haunt insurance companies. Insurers frequently grapple with large volumes of unstructured data, often stemming from paper-based forms. This poses obstacles to integration and validation, adding yet another layer of complexity to managing information effectively.
Alright, for our final example—difficulties in integrating external data. For insurers, standardising and integrating data from external sources like asset managers and reinsurers can pose quite a hurdle, translating to potential inconsistencies and reliability issues within their datasets.
How Can Edge Computing Improve Data Reliability in the Insurance Industry?
Since data reliability issues are such a hot topic in insurance, there must be some ways to address these obstacles, right? With edge computing, there sure are. Let’s shed some light on some:
- Improved Data Security: Processing data locally on edge devices allows insurers to improve its security. How? Since data doesn’t need to travel to a central cloud location, the exposure of sensitive customer data to security threats is reduced to a minimum. This approach benefits not only data security but also privacy.
- Continuous Data Processing: Thanks to edge computing, data processing can carry on smoothly even if the connection to the central cloud is lost. This way, the system stays up and running, which boosts the overall reliability of the data processing infrastructure.
- Reduced Bandwidth Constraints: With edge computing, insurers can sort through and manage data locally before sending only the most crucial information to the cloud. This lightens the load on bandwidth, ultimately making data transmission more reliable.
- Faster Response Times: By processing data closer to the source, edge computing significantly speeds up response times. This is paramount for time-sensitive insurance applications such as real-time risk assessment and claims processing.
- Scalability and Adaptability: By leveraging the modular and distributed nature of edge computing platforms, insurance companies have the freedom to easily adjust their data processing capabilities by integrating more edge devices. This enhances the system’s overall reliability, as well as performance.
- Compliance with Data Governance Regulations: Meeting data governance regulations had never been more effective for insurers. With edge computing, they can manage and store sensitive data locally, sidestepping the need for centralised cloud storage.
In an industry where data reigns supreme, incorporating innovative technologies that prioritise data reliability isn’t just a strategic move — it’s a must for thriving in the dynamic insurance landscape. And edge computing, along with edge AI, is the way to do it.
How Edge Computing And Cloud Computing Complement Each Other in Modern IT Infrastructure
I already explained that edge computing brings processing power closer to the data source compared to cloud solutions. And since I’ve mentioned cloud, why not toss it into the equation as well while we’re at it?
Both edge computing and cloud computing are potent and remarkable technologies in the digital realm. Each brings unique assets to the table while compensating for the other’s limitations.
For example, edge computing has the upper hand when it comes to low-latency processing and real-time decision making, crucial for applications like autonomous vehicles and industrial automation. But cloud computing may introduce higher latency due to data transmission to centralised data centres.
While edge computing reduces bandwidth consumption by processing data locally, alleviating the strain on network resources, cloud computing’s robust computing power and storage capacity take care of data-intensive workloads that edge devices can’t handle alone.
There’s also a matter of data security and privacy. Edge computing increases confidentiality by keeping sensitive information close to home, whereas with cloud computing, data is kept safe and sound in centralised centres.
What’s more, things like autonomous decision-making get a solid boost from edge computing. But cloud computing does its bit here, too, offering centralised management and coordination of distributed edge devices and applications.
By leveraging both edge computing and cloud computing, the sky’s the limit. Combine these two, and you’ll combine local responsiveness with centralised scalability to meet the diverse demands of modern computing.
Edge Computing & Edge AI in Insurance – Wrap-Up
Edge computing, along with edge AI, is experiencing a notable boom nowadays. As we look ahead, it’s clear that these technologies are not merely tools for navigating present challenges; they’re poised to revolutionise the way insurance companies operate, providing them with more efficient and superior solutions. I’m talking about more accurate, responsive, and personalised insurance services.
At Shaped Thoughts, we specialise in developing custom InsurTech solutions tailored to your unique needs. Partner with us to leverage the power of edge computing and edge AI and stay ahead in the competitive landscape. Reach out to us today and shake up your insurance operations and drive your business forward.