Core Insurance, Risk Management
Article | September 22, 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 19, 2022
The rise in remote work during and after the pandemic has increased cyber vulnerabilities significantly.
Cyber insurance protects your company from the financial consequences of cyber threats or data breaches involving computer systems and data. Credit card numbers, social security numbers, account numbers, health records, and driver's license numbers are examples of sensitive customer information.
According to a recent SBA survey, 88% of small business owners believe they are vulnerable to a cyberattack. If your company is a victim of cybercrime, the cost of recovery can be prohibitively expensive, including specialized repairs and legal fees.
One of the most difficult challenges is quantifying cyber risk. Although approaches and frameworks like NIST CSF, CIS 20, NCSC Cyber Essentials, and ISO 270001 aid in the development of cyber security capabilities, they do not provide the tools to quantify risk. As a result, leaders frequently overestimate their cyber maturity while underestimating cyber insurance premiums.
Potential Cyberattack Types are:
Breach of data: A breach occurs when critical information, such as personal financial information, is stolen.
Cyber-attacks on computers:Your computer system is hacked and compromised in this type of cyberattack.
Extortion via the internet:During an extortion threat to your company's computer system, thieves may demand ransom payments.
To address these issues, a variety of approaches can be used, ranging from zero-trust models to multi-factor authentication (MFA) and end-point detection and response (EDR) (EDR and XDR). Protective monitoring, encryption applied to the most critical aspects of your network, and patch management processes can also provide insurers with the assurance they require.
There are options for both small and large amounts of cyber liability coverage. A small cyber liability insurance policy could be added to the policy of a business owner. A larger cyber liability policy with higher limits would necessitate its own policy.
Furthermore, they provide a real-time view of compliance through a risk-based approach that is consolidated, consistent, and aggregated across the entire organization. Workflow automation can help the IRM system become more efficient.
By consolidating your risk management processes, you can ensure that controls continue to deliver on their objectives and demonstrate compliance with policies, standards, and regulations while having a lower impact on your day-to-day operational demands. All of this will make it easier to meet cyber insurers' requirements and give organizations confidence that their policy will protect them when they need it.
Article | July 13, 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 | April 13, 2020
Artificial intelligence (AI) has changed the insurance industry – and customer service is no exception. One of the most common forms of AI are the use of chatbots, which Forbes defines as “software functionality that is designed to receive conversational input through text of voice and then generate a response that is also in natural language.” In other words, instead of interacting with a human, you’re “chatting” with a bot that’s programmed to understand your questions and direct you to the right place.