Core Insurance, Risk Management

Article | August 4, 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.

Insurance Technology

Article | August 9, 2022

Underwriting has historically been one of the most data-intensive areas of insurance. But when it comes to looking at investments and results, data and information handling for underwriting at most carriers is still disjointed and disconnected. This is underwriting’s version of the digital divide we’ve been discussing in this series, and it leads to inefficiencies and ineffective underwriting. The divide exists because today’s underwriting platforms have not evolved to meet the needs of a modern digital carrier. To see why, let’s take a quick look at the history of these platforms. The first generation of underwriting platforms was built to provide rating systems and core policy management needed to price and administer the underwriting of policies. The technology they run on has changed from mainframe to servers to the cloud, but the platforms themselves remain focused on managing the least information necessary to price and maintain the policy.

Insurance Technology

Article | July 15, 2022

Environmental, social, and governance (ESG) considerations have increasingly entered the mainstream of investment discussions, both through routine incorporation into traditional investment processes and through distinct sustainable or impact investing styles. Recent and current global conditions, such as extreme weather events, the inequitable effects of the COVID-19 pandemic, rising distrust of government institutions, and geopolitical challenges to a rules-based world order, have accelerated this trend, emphasizing the direct relevance of ESG and sustainability to understanding long-term market risks and opportunities. Until recently, equity investors were more concerned with ESG and sustainability than their fixed-income counterparts. That is, however, beginning to change, and at a rapid pace. ESG and sustainability have gained significant traction among bond investors, particularly since the implementation of COVID-19, and are now widely regarded as essential components of fixed income investing. For example, global sustainable debt issuance reached a new high of over US$1.6 trillion in 2021 and is expected to rise further in the coming years. Notably, we believe that ESG integration and sustainable fixed-income investing require a very deliberate, thoughtful approach — one that varies significantly from one fixed-income sector to the next. ESG and sustainability: At a high level, researchers believe that increased awareness of ESG and sustainability benefits global markets in two ways: 1. ESG integration allows market participants to think more holistically about the types of financially material risks and opportunities — such as physical, reputational, and (geo)political — that should ideally be reflected in asset valuations and taken into account during the routine portfolio construction and management process. 2. Furthermore, the conversation about sustainable investing is encouraging more market participants to look beyond narrow, issuer-specific investment thesis to consider how market participants' behaviors affect the broader systems and structures (e.g., climate stability, institutional strength) whose long-term viability is critical for the long-term health of economies and markets. We, like many others, believe that a stable global climate, clean air and water for all, adherence to the rule of law, strong institutions with broad public legitimacy, and broad-based access to economic opportunity are valuable public goods from which market participants would benefit collectively over time. As a result, a central goal of sustainable investing is to assist markets in evolving toward rewarding participants for exercising responsible stewardship of these public goods, which are critical to pursuing favorable long-term outcomes for the real people who are the ultimate beneficiaries of markets. This framing of sustainability highlights why fixed income is so important in moving global markets and economies in a more sustainable direction.

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.