Insurance Technology
Article | July 15, 2022
Insurers of the future will play more of a risk avoidance role and less of a risk mitigation one.
The seemingly effective yet simple ideas of Netflix, Uber, Ola, Amazon, and many other ideas have forever transformed their industry segments. Digital transformation in the insurance industry is embraced in various ways to address the complex challenges posed by consumers, regulatory, and digital landscapes.
To keep up with insureds' demands, insurers have had to digitize various aspects of their operations. Any company that wants to stay competitive in today's market must meet customers where and when they need it. Insurance's digital transformation, powered by artificial intelligence, machine learning, predictive analytics, mobile services, live chat, and other technologies, enables insurers to do just that and will continue to change the industry for years.
Insurance Companies to Look at Value Chain through a Digital Lens:
Gain First-Mover Advantage:
Product introduction to gain a potentially sustainable competitive advantage. To achieve the first-mover advantage, the insurer should have two crucial capabilities: the ability to pinpoint unmet customer needs to guide product development and quickly adapt existing products to market forces.
Reduce IT costs to fund innovation:
When insurance companies refactor monolithic applications into modular micro services, application maintenance costs are reduced.
Grow revenue by differentiating the customer journey:
Electronic document capture and processing, robotic process automation (RPA), and robo-advisors improve serviceability and help businesses gain a competitive advantage.
Despite market participants' claims that the insurance industry was not an early adopter of digital transformation, new players, business models, and demanding customers are forcing the industry to embrace digital technologies. As a result, the global insurance market is expected to grow by 45% between 2022 and 2025.
Modern digital engineering does not occur in a vacuum; new products must be compatible with existing technologies and processes. Ascertain that the development team understands legacy insurance applications and the data required to integrate them with new, digitally engineered products.
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Automobile Insurance, Insurance Technology
Article | December 19, 2022
Automated claims processing, price comparison platforms, mobile bill paying—these are just some of the digital services that insurance customers expect and insurers want to provide. As the demand for digital skyrockets, so does the need for insurers to invest in IT. In the past seven years, the share of IT in total operating costs of property-and-casualty (P&C) insurers increased 22 percent. The rise of digital means technology is no longer a cost center. Rather, it is an asset that, if managed well, can increase growth and profitability.
But do these IT investments pay off? As the COVID-19 pandemic exacerbates already increasing cost pressures, insurers’ IT budgets are under scrutiny; they want to see the business impact of their IT investments.
Insurers with targeted IT investments achieve better growth and performance
Data from McKinsey’s Insurance 360° benchmarking survey provide strong evidence of the positive business impact of targeted IT investments. In fact, insurers that invest more in technology outpace competitors that don’t pursue targeted investments in business measures such as gross written premium (GWP) growth, return to shareholders, and expense and loss ratio (exhibit).
As an example, in life insurance, companies that invested more in IT saw a greater reduction in expense ratios (by 2.0 percentage points) and higher returns on technical reserves2 (1.7 percentage points) when compared with insurers with lower IT investments. Insurers achieved these outcomes within three to five years of making their investments.
For P&C insurers, those with high IT investments achieved approximately twice the top-line GWP growth of low IT investors. High IT investments also produced a greater reduction in combined ratios when compared with those with low IT investment.
Four areas for targeted IT investment
So what kinds of technology investments can help insurers achieve growth and improve productivity and performance? Investments in four areas are critical:
Marketing and sales: Marketing technology solutions can increase sales and processing efficiency, improve the quality of core customer-facing processes such as policy inquiries and policy applications, and improve customers’ overall experiences. McKinsey’s Insurance 360° benchmarking data show that tech investments in this category can facilitate top-line growth for P&C insurers by up to 20–40 percent; for life insurers, that growth could be 10–25 percent over a three- to five-year period.
Underwriting and pricing: Automated underwriting fraud detection can improve the likelihood that insurers correctly identify fraud and set accurate prices. A pricing tool kit that analyzes pricing across competitors and enables a flexible, more segmented market versus technical pricing further improves profit margins. Insurers that deploy these and other product, pricing, and underwriting technologies have seen improvements in their profit margins by 10–15 percent in P&C insurance and 3–5 percent in life insurance.
Policy servicing: Workflow automation, artificial intelligence–based decision support, and user experience technologies in policy servicing and within IT can improve the customer self-service experience and automate back-office processes, thus reducing IT and operations expenses. And state-of-the-art self-servicing options will reduce processing times and even improve customer experience. An analysis of programs for large-scale insurance IT modernization finds that insurers that deploy these and other product, pricing, and underwriting technologies have seen improvements in their profit margins by 5–10 percent in P&C insurance and 10–15 percent in life insurance.
Claims: P&C insurers can use automated case processing—machine-learning technology trained to process basic claims cases—to segment more complex cases and significantly improve claims accuracy. Combined with better partner integration and steering technologies embedded in a transformation of the claims operating model, such technologies can help P&C insurers improve profit margins by 25–40 percent, according to McKinsey analysis of large-scale IT modernization programs.
To realize the full value of IT investments, insurers must strategically allocate their resources and view tech as an asset, not a tool.
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Core Insurance, Risk Management
Article | August 4, 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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Insurance Technology
Article | May 20, 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
Marketing
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
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
Lead segmentation
Sales funnel optimization
There is enormous value in optimizing productive data by focusing on prospects likely to become loyal customers.
Operations
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.
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