Article | July 20, 2022
Insurtech is advancing, and the significance of an effective policy management system cannot be underrated. Policy management professionals understand the payoff it offers to an organization. On the other hand, a policy management system that just isn’t a good fit can prove to be a lot more expensive than previously budgeted.
So what is it actually costing you? Is your policy management software updated, or are you still using an old version? Do you know how much it is hampering your financial productivity? Even then, often, an outdated system may not be affecting your process significantly but damaging it in other intangible ways that are just as crucial to business success. Analyze your current system for the following:
Financial Implications of the Current System
Manual processes for policy creation and management make up the costliest part of running a policy management system. Paper-based solutions incur high costs that can be easily avoided by using digital systems that use automation extensively. With thousands of policies and compliance procedures for your team to manage, costs can add up quickly, especially with printing and distribution costs.
In addition to these expenses, manual processes are also responsible for policies being misplaced or lost. It may also result in a large fine for noncompliance if some policies are accessible to unauthorized employees.
Organized policy management procedures are critical for high operational efficiencies. Policy management systems that require manual supervision can prove to be expensive over the long run as they require employees to monitor them constantly. However, automated policy management systems enable policy teams to optimize their resources better and direct team members to speed up other more crucial processes.
Furthermore, modern policy management systems don’t need constant monitoring and require only a one time set-up. This enables teams to allocate resources where they are urgently needed.
If you have an outdated policy management system, chances are it takes a lot more micro-managing than it needs to. Businesses must be able to optimize their resources better but with old and outdated systems, it ends up cutting into the productivity and performance on an everyday basis.
In addition, it puts undue stress on employees to keep up with compliance norms and changing regulations and policies. Policy management often requires various employees to pitch in with their inputs, and using an old system that doesn’t offer the option to collaborate can take away a huge chunk of productivity daily.
What’s the Bottom Line?
Automated policy management systems can undoubtedly save you a lot of time and resources. If you’re facing sky-high costs just to maintain your policy management system, it might be time for a rethink. From automating the lifecycle of policies and procedures to streamlining the management of policies by your agents, consolidating a policy management process with software is one of the best insurtech trends to look out for in 2023. It is probably what your organization needs to move the needle.
Core Insurance, Risk Management
Article | August 4, 2022
The COVID-19 pandemic has caused unprecedented disruption to the insurance industry overall, dramatically curtailing business activity, upending the everyday lives of employees and customers, and more. However, companies that derive a substantial portion of their business from motor insurance have enjoyed stronger bottom-line results during the pandemic than in previous years. That’s because when sudden lockdowns kept drivers at home and off the road (see exhibit), claims plunged by 60 to 80 percent almost immediately. As restrictions began to lift, claim volumes subsequently bounced back, although they remain 20 to 30 percent lower than they were before the pandemic. The corresponding drop in payouts for claims was only partially offset by the refunds on premiums that insurers paid to customers to compensate them for traveling fewer miles.
Are motor claims in Europe about to rebound?
As of mid-2021, motor claims volume remains suppressed—at least for the time being. For insurers, this offers a short-term window to pursue or accelerate strategic initiatives aimed at establishing claims excellence, a key driver of profitability. These initiatives include transforming claims processes to improve customer experience, building digital capabilities, leveraging advanced analytics to improve decision-making, and reducing long-standing sources of leakage. Acting now will help insurers be prepared when vaccination rates across Europe accelerate, economies reopen, and both mobility and motor claims rebound.
Even as the pandemic recedes and business returns, insurers are likely to confront three persistent challenges that can be addressed—at least in part—by transforming claims management to improve profitability.
Top-line pressure will continue. Pandemic-related top-line pressure will likely continue for the foreseeable future. If history serves as a guide, commercial lines, which suffered from a temporary halt in business activity in the tourism, aviation, entertainment, and local business sectors, may be slow to recover. During the 2008 financial crisis, for instance, commercial lines took significantly longer to recover than personal lines. As for personal lines today, declines in everyday commuting have altered customers’ perceptions of the value of insurance: if they drive less, they expect to pay less. As noted above, some insurers have proactively offered their customers premium paybacks for reduced car usage—a change that could endure.
Digital is here to stay. Because of the pandemic, people shifted many everyday activities to remote channels and adopted new digital tools. For example, across Europe, 60 to 70 percent of consumers moved some of their shopping online, and most intend to perpetuate the new habit after the pandemic ends. This shift in customer behavior extended to engagement with insurers. In the United Kingdom, claims notifications filed via digital channels doubled during the pandemic, and insurers received 30 percent more digital inquiries than in the past. However, customers’ growing expectations for an end-to-end digital experience—with 24/7 service, instant feedback, and a user-friendly interface—still place most insurers in the position of playing catch-up. The large majority of customers still prefer to place a call rather than use digital self-service; in Europe, for example, more than 50 percent of claims are initiated when a customer contacts an agent. This preference could indicate that insurers have yet to fully digitize the claims handling process.
Inflation will affect claims costs. Insurers anticipate increased pressure on claims costs from multiple sources. First, car repair shops have suffered the knock-on effects of the COVID-19-induced drop in claims volume. Many received government help, but they also responded by increasing labor rates and margins on spare parts. The claims inflation rate currently sits at 4 to 5 percent. Ongoing cost pressure means repair shops are unlikely to reinstate their pre-COVID-19 price levels without some restructuring in the sector. In one scenario, insurers could step into the role of ecosystem orchestrators, significantly consolidating repair volumes and offering strong incentives—including extending insurance services to include maintenance and offering negotiated prices for parts and labor—to repair shops to participate. Meanwhile, insurers can analyze increased volumes of claims data to continually assess the performance of repair shops and then use those insights to guide customers to the best deals.
Even before the pandemic, insurers had made strides in improving the bottom line by increasing productivity and optimizing technical excellence, particularly via pricing. Now is the time to tackle claims. Claims organizations can use this period of lower claims volume to plan their strategic investments in advanced analytics transformation, to devise new digital talent strategies, and to improve their understanding of customer needs and expectations.
A complete suite of analytics and updated process automation—prerequisites for accurate, end-to-end automation—constitute the backbone of the new claims and customer experience model. The tools are evolving, driving automated decision-making along the entire claims handling process: routing, triaging, liability negotiation, cost estimating, deciding to repair or write off damaged vehicles, cash settlements, and fraud detection. All these areas will increasingly use digital and analytics as opposed to manual labor, changing the entire claims operating model.
Responding to customer demands for a seamless claims experience is a top priority. The pandemic has proved that customers are eager for and accepting of new digital experiences. They expect full transparency throughout the claims journey; minimal effort on their part (for example, very little engagement back and forth with the agent to get the claim resolved and receive payment); faster resolution of claims, perhaps including automated payments; and the ability to move seamlessly between the digital and physical worlds.
Furthermore, insurers can work to reduce leakage and improve the bottom line. Leakage takes many forms, including replacing rather than repairing a vehicle, offering a luxury replacement vehicle rather than a car that matches the customer’s vehicle class, and incurring costs for in-person loss assessments even in obvious cases for which pictures would suffice. Tackling leakage will entail enabling efficient detection of anomalies, selecting claims for detailed review, and empowering the claims organizations to efficiently close claims that cast no doubt.
Accomplishing these critical objectives will entail a shift from a scattered and often siloed approach using unintegrated digital and analytics tools to end-to-end digital- and analytics-enabled claims processes. On the front end, insurers will need to establish tools on par with the top digital services their customers use every day (for example, ride-hailing apps, social media, and digital banks).
On the back end, claims organization will need to invest in a suite of analytics engines to support automated decision-making to cut costs. The opportunity starts with claims prevention—using telematics and the Internet of Things to issue safety warnings and damage prevention tips—and continues throughout the claims processing journey, from providing customers with an easy digital first notice of loss interface and improving claims cost accuracy, to digital selection of a repair shop and automated payment processing and invoice checks. This relative lull in activity also gives insurers a good time to provide teams handling claims with the training they need to learn new processes and operate new digital tools.
Claims are already rebounding, so the clock is ticking for insurers. Building end-to-end digital and analytics solutions requires significant investment and will take substantial time. For claims organizations, it is critical to act now or risk missing the opportunity to emerge from the pandemic stronger than competitors.
Article | July 15, 2022
The world is changing at a rapid pace, and no industry is immune to the need to evolve, upgrade, and innovate. The effects of mass digitization, artificial intelligence, machine learning, climate change, and the rise of financial-based cybercrime are all being felt in the business world. At the same time, consumer expectations have shifted dramatically, thanks in large part to companies like Netflix and Amazon, which have the technology and business models to provide the instant access to products and services that today's consumers have come to expect. When these changes are considered, it becomes clear that no industry, not even one as traditional, robust, and stable as the insurance industry, can afford to stand still.
Trend 1: CARE-Based Distribution Channels
Insurance companies are engaged in a "digital arms race," rushing to equip their distribution channels with digital tools to improve customer experiences. While CARE is the core experience that most insurance companies strive to provide in both distribution and sales, few achieve it consistently.
Trend 2: Quicker Payouts
Pay cycle time is fast becoming one of the most important differentiators between insurance companies. The winners of the future will use insurance technology to help them resolve claims quickly, at the touch of a button.
To this end, companies are adopting AI-enabled tools to automate both estimation and inspection. Telematics insurance solutions are expected to provide greater levels of contextual information that will support the smoother, faster, and more comprehensive settlement of claims.
Trend 3: The Rise of Usage-Based Models
As the pandemic made consumers aware of the waste involved in paying for insurance on cars that sit unused in driveways, interest in usage-based insurance products skyrocketed in 2021. As the nature of work changes and many people's daily commutes become obsolete, winning insurance companies will offer products that are more in line with how their customers live today. Telematics devices will allow insurers to offer products based on how and how far users drive.
Trend 4: Intelligent Automation
For a long time, the insurance industry has been experimenting with automation. The first phase was robotic process automation (RPA), which was viewed as a way to speed up processes and reduce costs without requiring significant changes to the underlying applications. While this was effective at capturing low-hanging fruit—those ubiquitous repetitive steps that were an unnecessary feature of so many insurance processes—it never really attacked productivity and core functions that required automation.
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
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.