Insurance Technology
Article | July 14, 2022
Through machine learning and deep learning, artificial intelligence (AI) can meet industry expectations.
As artificial intelligence becomes more deeply embedded in the insurance industry, industry leaders must position themselves to respond to the changing business landscape. Every day,various factors contribute to the industry's changing landscape. AI is becoming more assertive in insurance, particularly in cost savings, customer service and experience, product innovations, and marketing initiatives.
With this understanding, market leaders can develop appropriate revenue-generating strategies, embrace new AI horizons and implement them to develop the perspective required to succeed in the futuristic insurance industry.
AI-related Action for Better Forecasting
Among insurance executives who have already invested in AI, many new businesses are reaping significant benefits. They have gained the advantages of using AI to improve the customer experience (CX). According to a Deloitte study, approximately 65% believe AI assists in decision-making. Furthermore, according to PwC specialists working with insurers on AI initiatives, businesses are increasingly using AI to:
Customize products and services for consumers and other businesses
Establish a loyalty framework and upsell among customers
Automate more data from social media and other sources for better forecasting
Automate more aspects of claim processing
Improve fraud detection methods
Beginwith customer segmentation to target
As a result of these findings, AI investments will benefit insurance companies more than ever before.
How Insurers Can Accelerate AI
The following points can help insurance businesses accelerate AI and achieve faster ROI.
Centralize Business Functionalities
Deploying AI into the process aids in the automation of resources, the alignment of tasks, the use of analytics to nurture data, the improvement of governance, and the scaling of solutions.
Focus On Data
AI in insurance aids in collectingand combining relevant data from consumers and future customers. AI-assisted data collection is faster and more accurate at the appropriate time. In this manner, marketers can plan for future marketing campaigns that will increase engagement and bring in more money.
Reduced Risks
AI is the most effective at reducing business risks. Also, AI works best for insurers to minimize risks such as data breaches, fraud detection, correct cost segmentation, and budgeting hazards.
Some Insights into AI Investment: A Key Decision to Make!
As technology continues to empower the insurance sector, let's take a look at how other insurance companies are investing in AI so that you may make the vital decision to incorporate AI into your organization as soon as possible.
65% of businesses found better ways to establisha customer experience base with the help of AI post-2020
49% of businesses have improved their internal decision-making process after adopting AI
56% of businesses were able to reinvent their products and services through AI
47% of businesses operated their business functions more efficiently with AI and increased productivity.
45% of insurance businesses saved substantial costs using AI algorithms
35% ofinsurance businesses have successfully reduced risks associated with their businesses after the deployment of AI.
53% of insurance companies have seen a significant revenue increase by incorporating AI into their processes.
These figures are based on a Deloitte’s research study conducted by insurance industry specialists worldwide.
Some Possible AI Risks for Businesses
Every technology helps businesses gain benefits, but technology installation has to be done correctly to avoid consequences. As a result, insurance companies must exercise caution when implementing AI in their business processes. The possibility of faulty AI implementation could lead to:
New cyber hazards
New privacy threats
Workforce shortages
New legal liabilities and reputational risks
Customer distrust
More complex business modules
The lack of AI abilitiesismore challenging, which can affect the entire business sphere, especially the functions that are associated with AI.
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Core Insurance, Risk Management
Article | September 22, 2022
As AI becomes more deeply integrated into the industry, carriers must position themselves to respond to the changing business landscape. Insurance executives are expected to understand the factors driving this shift and how AI in insurance will impact claims, distribution, underwriting, and pricing. They can start to learn the skills and talent they need, embrace new technology in the insurance industry, and build the culture and perspective they need to be successful in the future insurance market with this grip.
While there are four types of levers that might help with productivity efforts—functional excellence, structural simplification, business transformation, and enterprise agility—insurers typically focus on the first two. Those levers are the foundation of efficient and effective operations, it isn't easy to leapfrog them. Traditional industry barriers are dissolving while technology advances and customer expectations vary dramatically. Ecosystems, which are groups of services that work together in a single integrated experience, are becoming more common across industries. Platforms that connect offerings from different industries are also becoming more common.
In an interview with Media 7, Darcy Shapiro, COO of Americas at Cover Genius, talked about the changing expectations of consumers in the insurance industry.
“Consumers expect brands to provide the same high-quality day-to-day experiences directly within the digital platforms they use most. Insurance should be no different.”
Darcy Shapiro, COO of Americas at Cover Genius
The Increasing Acceptance of Parametric Insurance
In contrast to traditional policies, which are paid based on actual loss incurrence, metric insurance has been around for a while, providing payouts when a specific event exceeds an agreed-upon threshold. Previously being used specifically for natural disaster coverage and supplied to countries and large corporations, parametric insurance is making a comeback today. Advancements in sensor technology, data analytics, and Artificial Intelligence (AI in insurance) create broader information indexes on various levels, which opens up parametric risk applications in novel ways.
A reinsurance company recently introduced a parametric water-level insurance product to shield businesses from the financial consequences of high or low river water levels. The program considers measured water levels at specific river gauges and agrees to pay a fixed amount for each day that the index remains below a predetermined threshold value. Other new-generation parametric solutions include terrorism protection for cities and airports, protection for retailers when transit strikes cut down on pedestrian traffic, and help for hotels when there are outbreaks.
The advantages of parametric insurance include faster delivery and avoiding lengthy claims investigations. Furthermore, since parametric products have less uncertainty than traditional insurance, premiums can be significantly lower. In terms of technology, parametric insurance is best suited to blockchain technology, with smart contracts that pay out automatically when certain parameters are met.
A Flood of Data from Connected Devices
Fitness bands, home assistants, smartwatches, and other smart devices are rapidly becoming a part of our daily lives. In addition, smart clothing and medical devices will soon join the fray.
Sensor-equipped equipment has long been common in industrial settings, but the number of connected consumer products is expected to skyrocket in the coming years. Existing gadgets (such as automobiles, fitness trackers, home assistants, smartphones, and smartwatches) will continue to grow. In contrast, new and expanding categories (such as clothing, eyewear, home appliances, medical devices, and shoes) will join them. According to analysts, interconnected devices will reach one trillion by 2025.
The data generated by these devices will result in a flood of new data that carriers can use to understand their customers better, resulting in new product categories, more customized pricing, and an increase in real-time service delivery.
The insurance industry can mine the data generated by these smart devices to better understand their customers’ preferences. This information can also assist insurers in developing new and more personalized product categories.
The Rise of the Insurance Ecosystem
According to McKinsey, insurance ecosystems will generate 30% of global revenue by 2025.
With an expanding array of data sources and a data-driven culture, many insurers will soon be able to plug into and exploit data from complementing firms. These agreements are evolving to involve traditional insurers as well as technology companies. For example, an insurance firm in Europe teamed up with a smart-home technology vendor to improve its home insurance. The latter's technology can detect smoke and carbon monoxide, preventing losses. In addition, a global initiative of a major reinsurance company is developing an ecosystem for InsurTech start-ups and digital distributors. Recent McKinsey research also shows that the insurance business has been having a hard time making efficiency gains for a long time.
Moreover, the operating expense disparity between the best and worst performers in P & C and life has widened over the last decade. Functional excellence, structural simplicity, business transformation, and enterprise agility are four productivity levers that insurers often focus on. Those levers are essential to efficient and productive operations. Ecosystems, which are groups of services that work together, are formed across industries and platforms that connect offerings from different sectors.
Insurers may use ecosystems to integrate their products into seamless client experiences. Ecosystems are essential in today's interconnected world, whether you want to build direct relationships with customers or work with companies that act as the customer interface.
Advancements in Cognitive Technology
Cognition is a critical component of AI in insurance. AI cognitive technologies mimic how the human brain functions. In addition, new technology may make it easier to process huge amounts of data, especially from active insurance products that are linked to specific people.
Carriers can constantly learn and adapt to the world thanks to cognitive technologies. As a result, it can enable insurance companies to introduce new product categories and engagement techniques and respond in real-time to changing underlying risks. In addition, convolutional neural networks and other deep learning technologies, which are currently used primarily for image, audio, and unstructured text processing, will be used in various applications in the future of insurance industry.
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Core Insurance, Risk Management
Article | August 4, 2022
Amid COVID-19, banks began offering mortgage deferrals and slashing credit card interest rates in half for cardholders who need relief. Home and auto insurance companies COVID-19 plans are now being released. How will this impact your insurance right now? How can you save on insurance during COVID-19, while making sure to stay protected?
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Risk Management
Article | July 11, 2022
Online shopping is quickly becoming the new norm in the wake of the COVID-19 pandemic. Most retailers had to migrate their businesses to the cloud in order to meet the current demands of highly tech-savvy consumers, and the use of POS software has become more important than ever. A cloud-hosted POS solution is no longer an option for small and large businesses, but rather a requirement.
POS systems have provided retailers with a more efficient way to track inventory and manage sales, replacing the old cash register and traditional methods of selling. As ecommerce grows, POS solutions play an important role in increasing convenience for online customers and providing a customer-centric experience.
To keep up with the latest POS system developments, there is a list of the most important POS software trends to watch for. By understanding current POS software adoption reports and key insights, you can maximize the potential of your existing POS solution or, better yet, have better ideas on financing trends by POS that can bring value to your retail business.
Consumers had to reorient their purchasing toward needs like food, medicine, and other home items as the viral pandemic threatened everyone's health and safety. The US Census Bureau recently released a report that found that throughout the pandemic, retail stores providing food and beverages saw the biggest monthly growth in retail sales.
To better understand how POS systems are assisting retailers in overcoming the challenges posed by the rapidly changing retail landscape, here’s a list of the most recent and important POS software trends:
Cashless Transactions via Mobile POS Systems
Adoption of Cloud-Hosted POS Systems
Multichannel Commerce
Customer Layout Programs
Personalized Shopping Experience
AI Integration in POS Systems
Use of POS Data Analytics
Simple POS Hardware
Investing in modern POS systems and maximizing their rich feature sets can help your retail business go a long way, from attracting new customers to retaining a loyal customer base that can drive sales and support your long-term growth.
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