Core Insurance, Risk Management
Article | September 22, 2022
With the major impact of the COVID-19 outbreak, contractors appreciate the need for insurance coverage even more. You may be safely covered by Force Majeure and pandemic clauses in your policies. However, you may still be wondering how to deal with the associated costs related to the COVID-19 outbreak risks. In this article, let’s look at some of the steps you can take to handle your insurance position during the pandemic.
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Insurance Technology
Article | August 9, 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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Insurance Technology
Article | July 19, 2022
Despite economic pressures on reinsurers and cedants, nearly all buyers were able to secure coverage during the reinsurance renewal period. However, attachment levels and the cost of ceding risk were higher than most buyers desired, and supply constraints in some lines and territories caused stress not seen in years. As a result, according to Gallagher Re's latest 1st View renewals report, the reinsurance market has maintained its firming trend.
Despite mostly positive H1 2022 results, the combination of inflation and rising interest rates has caused reinsurers to adjust their balance sheets and reserves while also taking into account how a recessionary environment may increase claims frequency.
These economic factors, combined with sustained loss levels, allowed reinsurers to maintain upward pricing pressure as they sought to reduce their appetite for volatility.
Key Contributions to Understanding:
Natural disaster capacity decreased overall as reinsurers continued to shift away from low-level layers, which differed by country and region.
Reinsurers were seen assessing cedants' inflation-related actions and applying carefully calculated loadings to relevant treaties.
The Russian invasion of Ukraine increased interest in cyber and war contract provisions.
Long-tail casualty placements remained popular among reinsurers, but there was more debate about ceding commissions than in recent renewals.
Higher ILS risk transfer prices have attracted net new capital, but this has not resulted in market softening.
The inflation discussions have been detailed and technical, with reinsurers eager to challenge cedants' model outputs. Most reinsurers are assessing reserve adequacy as interest rates rise, in addition to their concerns about primary rate adequacy in the new inflationary environment.
They are experiencing effects simultaneously on the asset and liability sides, which has strengthened their resolve to maintain the pricing momentum of the previous two years.
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Insurance Technology
Article | August 18, 2021
There is no doubt that we are living in an era in which insurers have been called to transform their business offerings, infrastructure and operations. Successful transformation translates into new revenue opportunities, stronger customer relationships and sustained brand relevance. However, this need to evolve cannot be addressed through superficial changes. Leading insurers are transforming their core offerings to completely reimagine their role in the insurance landscape. As the nominations and winners for the Efma-Accenture Innovation in Insurance Core Insurance Transformation award show, leading insurers are starting their core transformation at the top, and applying it to every touchpoint of the business.
Nine pioneering nominees
The nine nominees in the core insurance transformation category lead core insurance transformation in various innovations across their value chain. The nominations were:
AXA for A.Iconic Claims
Discovery for AI Quote
RBC for their conversational AI Platform, driven by Personal Insights for Life Insurance Application
Generali for their fund transaction through blockchain innovation
FWD for the AI-Everywhere Smart Insurance Framework
China Life Insurance for an intelligent value evaluation system for salesforce
Multiasistencia for MACARENA, an innovative AI voicebot that provides100% automated First Notice of Loss in home insurance claims
Humania for their ground-breaking income insurance for accident and disability claims
Mapfre for Verbatims, a cognitive behavioural model that integrates live customer feedback
As can be seen, by the nominees above, AI is a leading technology in core insurance transformation. In fact, every innovation used technology in fresh, structured ways to create a lasting impact on their business. Let’s look closer at the winners, and what their innovations say about how to lead core insurance transformation in 2021.
Gold: Discovery
Discovery are transforming the way brokers and clients engage with them through the introduction of their AI Quote service. Users are able to upload a PDF or pictures of competitor insurance and investment documents via phone or computer, and receive an equivalent Discovery quote in seconds. The entire journey can be completed in under a minute. Brokers can take the quotes to their clients and where a client has completed the direct journey, they will be called by a sales agent to discuss the specifics of the quote and close the sale.
Romek Sadowski, Discovery Life’s Head of Technical Marketing says, “Ultimately, AI-powered optical character recognition (OCR) technology has been able to equip us with a seamless journey for clients, advisers and employees of the business as a whole. For clients, benefits include receiving a comparable quote in less than a minute and an improved understanding of Discovery’s products relative to the market. For advisers, key benefits include more accurate and consistent competitor comparisons, as well as a reduction in sales and quoting frictions. By automating the process of extracting data from policy documents and then converting it into comparable Discovery Life benefits, our advisers are able to spend less time on manual work and more time assisting our clients.
AI Quote has also created opportunities for Discovery Life to incorporate digital tools into many of our existing processes and create a single, seamless, digital journey for advisers and clients alike. Additional innovations, such as Virtual Underwriting which allows clients to undergo underwriting from anywhere they choose, have been developed and are being refined in order to make this goal for a seamless digital journey a reality.”
This is an important innovation in the South African insurance and investment landscape, which is highly developed and innovative, and characterised by frequent product updates and enhancements. While products are fine-tuned to meet customer needs, it’s difficult for brokers to keep track of various products in the market and how they compare from one competitor to another. Clients are also not in the position to understand how exactly their financial products compare against competitors.
“The South African insurance industry is a complex environment with a vast array of sophisticated products. Financial advisers are faced with numerous competitors each with multiple products and options, resulting in countless different quoting combinations. By automating the comparison process, AI Quote simplifies the new business experience for both advisers and clients, increasing conversion rates and improving stakeholder satisfaction. AI Quote ensures that clients who have existing policies with our competitors are quoted comparable Discovery benefits and gives advisers confidence that they are providing clients with the best possible advice when comparing policies.”
By removing sales frictions and automatically carrying out comparisons, Discovery’s AI Quote aims to enhance the company’s exposure to potential clients, attract brokers to sell Discovery products, improve the accuracy of replacements and promote Discovery’s brand as a market-leading innovator. With an efficient client- and broker-centric platform, Discovery has taken quoting to the next level.
The potential for AI, however, is just beginning to be untapped. Romek concludes, “The insurance landscape is evolving, and we have seen an influx in microinsurance providers, direct-to-customer insurers and niche players in the market. When it comes to life insurance, clients are faced with a dauntingly large number of options – and that number is increasing. Within such complexity, manual processing of data in order to generate benefit comparisons is simply inefficient. A key benefit of AI is that it can complement or replace manual processes and allows for a far more streamlined user experience.
Outside of the new business process, AI has displayed immense success in other areas such as customer service, underwriting and claims. Chatbots are now commonly used by insurers around the world to assist clients and answer their questions. Car insurance has been fundamentally changed through advancements in telematics. Big data is more readily available and, with the help of AI, can be utilised to make faster and more accurate pricing and underwriting decisions.”
Silver: Generali
Generali conducted a deep transformation in the way they transact with their counterparts and custodians through the use of blockchain technology.
Generali France currently processes 250 thousand orders on funds (to cover unit-linked policies) per year through classical schemes via custodians. The aim is to generate a direct link with asset managers for trading shares of funds without using the costly transfer agent of custodians.
With this transformation in mind, Generali France invested in a startup called Iznes, developing a trading platform on funds based on blockchain technology. With this as a foundation, Generali has begun to connect its IT and operations to the innovative platform.
The innovation can serve all middle and back offices of investment departments and asset management companies. It crunches transaction costs and creates a direct link between the buy-side and the sell-side. The total cost of Generali Unit-linked orders is expected to drop by half, supposing that 50% of counterparts join the platform.
Bronze: FWD
Led by their customers’ needs and vision to change the way people feel about insurance, FWD Group Data developed a ‘Smart Insurance Framework’ which sees the business embarking on a ‘AI-everywhere’ approach. The platform has transformed the entire insurance journey for both their customers and employees with the use of advanced technologies and AI power.
To create a simpler and smoother insurance experience for customers, FWD created a modern data architecture framework that improves operation efficiency internally and convenience externally. The Group Office Data Platform (GODP) streamlines and integrates all data into a single platform that is smart, secured and scalable. This platform allows business users to harness data, insights and run analytics across all our markets, to help support a spectrum of initiatives in FWD with data. The clever use of data allows FWD to evolve and predict customer responses more accurately, develop a better understanding of customer needs and behaviour, and in turn serve them better.
As the nominees and winners show, the insurance industry is embracing technology to pre-empt, analyze and streamline customer, broker and employee experiences. We would love to hear how you are transforming your core insurance operations. Submit your core insurance innovation to the Efma-Accenture Innovation in Insurance Awards for 2022.
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