Article | July 13, 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.
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
New legal liabilities and reputational risks
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.
CORE INSURANCE,RISK MANAGEMENT
Article | August 4, 2022
The traditional insurance business has been resistant to technological change for a long time. However, the industry has made significant progress over the last decade due to the implementation of the innovative InsurTech solution, which disrupted long-held market patterns.
Technological changes have made insurers work intelligently through new strategies for attracting a new generation of customers. Embedded insurance is a trillion-dollar opportunity for insurers, giving them the chance to make new streams of money and lower their costs of distribution.
In totality, embedded insurance is a new frontier of product innovation in insurance based on rising customer use of digital services. It presents a $3 trillion market potential in the finance industry.
Narrowing the Gap that Existed
Embedding digital into insurance eradicated all the gaps that existed before. Earlier, many customers felt a burden or found it unnecessary to purchase a one-off insurance policy to protect a new possession. In contrast, at present, embedded insurance products for customers are covered with protection against losses. This has given customers the ultimate peace of mind.
InsureTech has provided insurers with improved data capture tools to conduct faster and more customized underwriting with applications. To reinvent insurance business models, embedded insurance as one of the InsurTech solutions has appeared efficient in filling the gaps in the insurance business.
Most insurance companies proactively recognize gaps such as irrelevant data capture, inaccurate customer information, and sluggish data retrieval processes. Thus, they are attempting to incorporate their products into an embedded structure where they can engage with digitally relevant consumers at their chosen time and place. Hence, embedded business intelligence for insurance creates a win-win situation for both the consumer and the insurer in the future.
Embedded Insurance Presents Opportunities
Why is embedded insurance becoming popular? Because it empowers customers the most.
Embedded insurance is beneficial to insurers seeking new ways to reach wider audience in one go. According to Bazaarvoice, a software technology company, 47% of consumers worldwide and 65% of US buyers now purchase online insurance products and services more frequently compared to the years from 2017 to 2020.
Today, with the help of technology, most insurance companies now embed their products virtually anywhere through open APIs. So, by integrating products into a virtual platform, insurers can deliver personalized products within a suitable period, perform real-time risk assessments, gain data, and calculate accurate pricing.
The insurers who gain this edge of benefit from technology need to be prepared to learn everything they can about their customers’ insights, behavior, requirements, and inclinations.
Embedded Insurance: Today and Beyond
Embedded insurance is a fantastic tool for insurers to enhance insurance penetration, particularly in the remote workspace model. However, to succeed with it, firms must find the correct balance between speed and efficiency of operations, detailed study of customer interests, and compliance with data.
Having mentioned that, it is emerging as a new way to distribute insurance services online efficiently, solving the protection gap to expand in the future.
Article | July 15, 2022
A quick Google Trends search on data reveals that data analytics, data and analytics, data analysis, and predictive analytics have steadily grown in popularity among businesses across industries.
These terms peaked when business leaders searched for ways to increase ROI and reduce business costs and tech-based investments. The insurance industry is amongst the industries actively leveraging data analytics.
The rising importance of analytics in insurance has made CMOS take note too. As agility became more important in the insurance industry, more than 85% of global businesses shifted to a data-driven model.
The purpose of taking you back is to emphasize that, as a CMO, now you need to churn accurate data and turn it into relevant information. This is a necessary model to practice to make the right decisions or will improve the decision-making process.
Without data analytics, you are deciding in a void, and that’s not considered good practice. Forrester reports that 41% of insurance companies faced challenges in extracting data and making decisions based on it in 2020.
Take a look at how and what you can do with insurance analytics to cater to better insights into your decision-making process and, finally, ROI generation.
Bring Data to These Key Levels of Departments
Analytics in insurance raises the bar in terms of marketing. As you know, marketing results frequently fluctuate, making data insights challenging to capture. CMOS who base their decisions solely on outcomes usually loses sight of making sound decisions due to unstructured data.
Therefore, it is essential to have an aligned platform for data analysis in insurance. To begin with, marketers must understand the various types of data analytics available. Most insurance marketers employ descriptive, predictive, and prescriptive analytics, among others. This will assist them in strategizing based on continuous data insights from various sources for any given initiative.
Sales leaders can also improve how they spend their time by using data analytics to create more accurate sales forecasts. However, the question is, how will they do it efficiently?
CRM software is the answer and solution to them. The software performs best because of its analytical capabilities in combination with data visualization, particularly predictive functions. It generates enormous amounts of data on customer interactions, which can then be used to inform decisions. You can assemble relevant data and use it to make some decisions, such as:
Acquisition and management of leads
Sales funnel optimization
There is enormous value in optimizing productive data by focusing on prospects likely to become loyal customers.
Utilizing data analytics in insurance boosts insurance operations. Small changes help to align a wide range of core processes. You can access data obtained from operations, observe key aspects of the overall processes, and make appropriate decisions. A targeted, timely, and data-driven approach will help you make decisions about these key functions, which can lead to business growth in the long run.
Bain's research in 2019 reports that seventy insurers were polled. They say data analytics will reach 58% in the marketing funnel and 45% in business operations.
Begin with Overcoming Barriers to your Decision-Making Process
Use Data to Identify Customer Patterns
Information from data can identify patterns. As mentioned above in the sales section, CRM's predictive modelling and the popular Google Analytics' descriptive overview are the two best platforms for identifying customer patterns.
What is the best way to get pertinent data? Data mining is the answer to it. Do you want to know about it? Then read data mining for pattern evaluation now!
As a CMO, you're probably aware that behavioral patterns are highly predictable and can sometimes result in unsatisfactory outcomes. This occurs when you are unable to obtain relevant data. And you end up performing ineffective marketing activities. To assist you in overcoming it, an AI-enabled platform can reduce the level of effort and provide the necessary data to study your customers' patterns in real-time. This is how you will notice a significant increase in sales.
According to research by McKinsey and Company, automation saves 43% of insurance employees’ time.
Segmenting Sales Plans
Following the establishment of your customers' patterns, segmenting the insurance sales plan is a necessary step. In this process, analytics provide detailed information about customers, allowing you to make decisions about sales functionalities. This will undoubtedly reduce the time, energy, and effort you previously spent.
Accurate customer segmentation and sales forecasting can also help tailor marketing efforts, improve the sales funnel, and keep sales strategies in check.
When Media 7 contacted Vishal Srivastava, Vice President (Model Validation) at Citi, here’s what he said about data segmentation through data analytics.
CMOs must ensure that adequate data quality checks have been performed, The goal is to ensure a scientific approach to data segmentation, sampling methodology, and data outliers, which can significantly impact revenue forecasts.”
Pricing & Savings
Analytics in insurance marketing can help CMOs make cost-cutting decisions and become more cost-effective in marketing efforts. It can set price ranges based on historical, current, and predictive performance. Also, analytics will help you figure out how to price things in the future, which will be good for ROI.
Keep Improving with Data to Stay Abreast with The Decision-Making Process
Better data organization in your business boosts productivity."
Warren Buffett, an American business magnate, investor, and philanthropist.
This phase is best suited to the current business environment. Implementing data analytics in insurance now will open up tremendous opportunities in the future. To make the most of them, you, as a CMO, must stick to a data-driven model for marketing actions.
Aside from that, it appears that the data analytics you select for your business must be capable of informing and driving performance. Performances ranging from risk assessment to sales forecasting and a plethora of actionable insights assist businesses in thriving.
Frequently Asked Question
How are data analytics used in insurance companies?
Data analytics empowers insurers to optimize each function and also assess risks. It also identifies trustworthy customers, which further boosts engagement.
What does data analytics mean in insurance?
Data analytics empowers insurance professionals by providing them with the business intelligence to understand their customers better, build better products and services, and thus, boost business growth.
How are insurance companies using data?
Insurers can use data to gain insights from customers’ profiles. They can review their history, behavioral pattern, and marketing needs to develop strategies and provide marketing services.
Article | May 13, 2022
When building a practical framework, AI holds tremendous potential for insurers. Insurance companies can use AI to make better business decisions and provide differentiated customer experiences. To take advantage of AI, insurers need to know and clear the air about what is possible to do with AI.
Insurance with AI: Understand, Learn & Respond
Here are the ways insurers must use AI in their workforce and build a workable model.
Language: Insurers can use natural language processing using AI to extract legacy unstructured data and convert it into structured data. As a result, organizations can extract information and automatically classify it into different sections. In addition, AI can even learn and guide users to make decisions using machine learning and curtail errors.
Management: AI has emerged as a game-changer in managing the workforce, risks, and insurance functionalities and augmenting flawless products and services. While we talk about workforce management, AI puts tasks in one place, organizes them, and stores them under a data-proof model. So, no more scattered documents and pilling of files! AI is here, and it will transform and respond to businesses more efficiently with solution-driven aspects.
Efficiency: Businesses need to be proactive by having a smart workforce that adds efficiency. Before, the insurance sector had a sloppy work platform. But now, with the passing of time, they need to overcome and be more efficient at work. Using AI in your business will save a lot of time, energy and money. It will lead to faster processes that are error-free, accurate, and predictive, encourage crystal clear communication, and have fewer chances of fraud.
Insights on AI’s Role in Insurance
Existing and start-up insurance businesses will be fortified with the help of AI use cases. Let’s get some insights into AI's potential for businesses.
The global AI market is estimated to grow at a CAGR of 42.2% to $733.7 billion by 2027. The inclusion of AI in insurance records a growth of 56% until 2021.
AI has the potential to save insurance companies up to $390 billion by 2023.
In 2021, more than 40% of insurance businesses increased their expenditure on AI use cases and projects.
These statistics show that AI in insurance is only going to get bigger. Investments in AI are high on the priority lists of decision-makers.
The Futuristic Hold
The insurance industry is under enormous pressure in terms of digital transformation. The rate of transformation is consistently accelerating. This paints the future of the insurance industry with AI to be more progressive with improved products and services, which will eventually host numerous opportunities for exponential expansion and reach globally.