The "boiling frog syndrome" describes a situation in which gradual small changes go unnoticed until they lead to big snowballing consequences requiring radical solutions. The insurance industry is suffering from this syndrome. Compared to other sectors, investing in insurance software development and implementing new technologies has been slow. Facing challenges like changing customer expectations, economic crises, new regulatory reporting standards, and evolving threats, insurers are reaching a point where insurance digital transformation is critical.
Digital transformation begins with the question, "How can organizational processes be designed today to maximize efficiency and customer satisfaction?" This approach differs significantly from asking, "How to digitize or digitalize manual processes?" or "How to improve a specific pipeline?" A comprehensive redesign is crucial because it ensures that all aspects of the organization are aligned with digital-first and data-driven principles, leading to more cohesive and efficient operations. Simply translating manual processes into digital forms often perpetuates existing inefficiencies and fails to leverage the full potential of digital technologies. This article will delve into the three primary phases of digital transformation in insurance: the collection of data, the utilization of this data, and the implications for the organization's strategic direction.
Let’s learn what insurance digital transformation entails and how enacting change helps insurers overcome major industry challenges.
New way to work: Automation
The first step of digital transformation involves reorganizing workflows within the organization, fundamentally changing how data is collected and stored.
Financial services are currently the second least trusted industry (social media takes the first place) [1]. Customers lack accessibility and transparency in the services provided. While other industries pushed their interfaces to be intuitive and the experience smooth, insurers tended to stay behind. This is particularly problematic for Millennials and Gen Z, who constitute 42% of the US population today. These younger generations frequently feel overwhelmed and confused when dealing with insurance, forming life-long negative associations. 29% of Millennials admit they refrain from purchasing insurance while recognizing its importance due to the complexity of the process [2]. Insurers today do not speak the language of the new generations, which hinders their ability to market to this growing demographic.
Digital tools can streamline and simplify the insurance purchasing process. User-friendly interfaces, online applications, and instant quotes can help customers understand and purchase insurance products without the traditional paperwork and complexity. Insurers can offer clear, detailed information about policies, coverage options, and terms through digital platforms. Interactive tools like chatbots, FAQs, and educational resources can help demystify insurance products and make information more accessible.
User interface
90% of the requests received by insurance call centers could be addressed through a web page [3]. On average, 55% of requests are information-related, indicating that customers are not receiving the necessary information through existing channels. 35% involve transaction execution, where employees act as intermediaries between customers and the systems that perform the actual transactions. This inefficient approach leads to massive unprompted costs; only 10% of the personnel are performing the work that a machine could not perform better.
So, where and how do you reroute so many requests? Well-designed self-service portals can help customers easily access information, manage policies, and perform transactions independently. Allow customers to perform transactions such as policy renewals, payments, and claims submissions directly through digital platforms, ensuring accuracy and speed. Integration across all systems and a good UI/UX design of a web and mobile application will significantly decrease the need for operators’ assistance.
Chatbots are great at assisting customers in finding answers to their questions quickly or categorizing their requests to boost the efficiency of the call center.
Read more: Current use cases of conversational AI in insurance
However, creating the user-facing side is only part of the solution. It has to be matched with insurance digital transformation and automation behind the scenes.
CRM system
A CRM system that meets modern standards should be established as a central, integrated platform that consolidates all customer interactions and data. This system should provide a comprehensive, 360-degree view of each customer, offering insights into their preferences, behavior, and history with the company to meet any need. Modern CRMs are typically cloud-based, providing scalability, flexibility, and accessibility from anywhere. These cloud solutions minimize the need for on-premises infrastructure, reduce maintenance costs, and offer enhanced security and compliance features. With a centralized system where all customer data is stored, there is a significant opportunity to automate various processes based on this data.
Underwriting & claims processing
Automated underwriting and claims processing save time and improve accuracy. These systems can quickly account for vast amounts of data, including medical records, financial information, and other relevant personal details, to determine applicants' risk profiles and specific claims and make informed decisions about policy approval and pricing. Automated underwriting significantly reduces the time required for underwriting from weeks or days to mere minutes, enhances consistency and accuracy in decision-making, and lowers operational costs.
Modern claims processing systems utilize ML algorithms to integrate data from various sources, such as cameras, IoT devices, telematics, and external databases, to provide a comprehensive view of the claim. In contrast, older systems rely heavily on manual processing and basic rule-based automation, which can be time-consuming and prone to errors. A well-defined claims management data pipeline enables the development of self-service options through mobile apps and web portals. This empowers customers to easily submit claims, track their status, and receive real-time updates. However, automation does not have to mean that a machine makes the final decision. Algorithms can assign scores to each variable or case to assist the underwriter.
Document workflow
According to Verizon's Data Breach Investigation Report [3], the second most common cause of security breaches in insurance is internal—document misdirection. Physical documents often end up with unintended recipients, and digital versions can be misdirected. A well-managed document processing system is crucial for seamless operations, security, and data integrity.
Document workflow automation in insurance streamlines and optimizes documents' management, routing, and processing electronically. This automation aims to reduce manual tasks, increase efficiency, and enhance accuracy in handling documents such as claims forms, policy applications, endorsements, and customer communications.
- Electronic handling: Documents are created, managed, and processed electronically, eliminating the need for physical handling.
- Automated data entry: Information is automatically extracted from documents using optical character recognition and AI, reducing manual data entry errors.
- Digital routing: Documents are automatically routed to the appropriate departments or individuals based on predefined rules and workflows, speeding up the process.
- Enhanced accuracy: Automated validation checks ensure data accuracy and consistency, reducing errors.
- Real-time tracking: The status of documents can be tracked in real-time, providing visibility into the workflow and enabling better monitoring and management.
- Efficient storage and retrieval: Documents are stored electronically in centralized repositories, making them easy to search, retrieve, and manage.
Compliance monitoring
Traditionally, compliance officers track regulatory changes manually, often relying on spreadsheets, emails, and paper documents. Much staff time and resources are required to monitor compliance manually, perform audits, and generate reports. The reliance on manual processes increases the likelihood of missing critical compliance deadlines or overlooking regulatory changes, leading to potential fines and reputational damage.
With automated compliance monitoring tools, the system continuously monitors regulatory changes and automatically updates compliance requirements. It sends alerts and notifications to relevant stakeholders about new regulations or upcoming deadlines. It ensures uniformity across departments, simplifies document processing, reduces the time and resources required for compliance monitoring, and identifies potential compliance risks and issues before they become significant problems.
New organizational design: Going data-driven
The second stage of digital transformation in insurance involves properly collecting and storing data and building systems that transform it into actionable insights, new services, more effective systems, and other benefits for the organization. Going data-driven as a part of insurance digital transformation involves restructuring decision-making processes regarding underwriting, marketing, customer service, and product development to be informed by data analysis, leading to more accurate and effective outcomes.
Read more: Big Data in Insurance: a game-changer for the future growth
Business intelligence
Business intelligence is a set of data analysis tools and technologies that collect, integrate, analyze, and present information about the processes within a business. Insights produced with these tools can be used to:
- Recognizing market trends and customer needs toguide the development of new insurance products, ensuring relevance and competitiveness.
- Identify inefficiencies and bottlenecks to implement targeted improvements, reduce costs, and enhance productivity.
- Support strategic decision-making by providing a data-driven foundation for business planning. It helps insurers forecast market trends, set strategic goals, and measure progress.
Personalized insurance
According to a large-scale McKinsey study, companies excelling in delivering superior customer experiences have shown a remarkable outperformance in total shareholder return. Specifically, life insurers with strong CX were 20% ahead, while property and casualty insurers brought up to 65% higher return [4]. CX leaders not only increase their top-line revenue but also improve their profitability. These insurers also experienced lower expense ratios by two percentage points. Lower expense ratios suggest more efficient operations, as they spend less on overhead and administrative costs than their income.
After developing comprehensive customer portals with intuitive UI/UX and redesigning processes with the customer in mind, the next significant improvement to CX is personalization. Personalized experiences can enhance customer satisfaction by tailoring interactions and services to individual needs and preferences. One of the most impactful and straightforward use cases of personalization in insurance is varying communication channels, styles, and content based on demographic data.
Much of the frustration and confusion in the CX comes from trying to distinguish which information applies and which is irrelevant. Around half of millennials state they might refrain from buying insurance since they don’t trust themselves enough to solve this puzzle [5]. Machines are much better at matching customer and product information to deliver only what the customer needs to know. This reduces the cognitive load on customers, making them more likely to stay with their insurer, purchase additional products, and recommend the company to others.
Risk assessment models
89% of policyholders in the US are willing to share more of their data in exchange for lower insurance premiums [6]. This shows consumers' readiness for a data-driven future in the insurance industry. This openness to data sharing, coupled with technological advancements, enables insurers to employ advanced analytics and ML to develop more sophisticated and accurate risk assessment models.
- In auto insurance: Telematics devices installed in vehicles can collect data on driving behavior, such as speed, braking patterns, mileage, and time of day.
- In health insurance: Wearable devices like fitness trackers and smartwatches collect health-related data such as activity levels, heart rate, sleep patterns, and other biometric information.
- In home insurance: IoT devices in homes, such as smart smoke detectors, water leak sensors, and security systems, provide real-time data on potential risks.
Another new tool brought by digital transformation in insurance is predictive modeling. The algorithm takes historical data, finds patterns, and iterates different scenarios to predict possible outcomes. It can forecast claim frequencies, assess risk levels, and determine optimal pricing strategies. By leveraging predictive models, insurers can enhance underwriting accuracy, reduce fraud, and tailor products to better meet the needs of individual policyholders.
Fraud prevention
Advanced fraud prevention approaches in insurance digital transformation are a crucial aspect of digital transformation in insurance, leveraging new technologies and tools to detect, prevent, and mitigate fabrication more effectively. Essentially, data analytics models can differentiate between normal and potentially fraudulent claims with much higher accuracy than human operators. These models can process vast amounts of data in real-time, identifying patterns and anomalies that might go unnoticed by manual reviews.
NLP tools can analyze textual data, such as claims forms and customer communications, to detect inconsistencies and red flags indicative of fraud. For instance, it can identify narrative discrepancies, unusual word choices, or repeated phrases that often signal fraudulent intent. Computer vision tools can analyze images of reported damages. These tools use machine learning algorithms to assess the authenticity of images, determining the likelihood that the damage is as reported by the customer.
Cybersecurity
The number one data breach scenario in insurance is unauthorized access to systems using methods that are primitive by today’s cybersecurity standards [7]. Yet, these methods still prove effective.
This effectiveness is due primarily to poor cybersecurity hygiene practices among users and insufficient security measures by organizations. Many insurers lack robust security protocols such as multi-factor authentication, password updates, and access controls, leaving systems vulnerable to even the most basic cyberattacks. Insurance digital transformation and going data-driven allow the implementation of ML tools that will distinguish normal user behavior from potentially fraudulent. Automated tools can continuously monitor and analyze network traffic for signs of credential stuffing or brute force attacks, allowing immediate mitigation efforts. Encrypting sensitive data and using data masking techniques ensure that even if data is intercepted, unauthorized individuals cannot easily read or use it. Using automated tools to regularly scan for and address vulnerabilities in the system helps maintain a strong security posture. All these practices and tools reduce the risk, response time, and damage an attack might cause.
New business strategy
Reworking foundational processes through insurance digital transformation opens new sales strategies and market positioning opportunities. Leveraging data, insurers can offer personalized, usage-based, and on-demand products that more effectively cater to individual customer needs. This transformation also allows companies to embrace socially responsible practices, differentiating themselves in the market and appealing to a broader, values-driven customer base.
Dynamic pricing modeling
Dynamic pricing modeling utilizes data to tailor insurance premiums more accurately and responsively to individual risk profiles based on driving behavior, health metrics, or property usage. Offering dynamic pricing that rewards safe behavior can become a significant competitive advantage. It can attract low-risk customers looking for fair and personalized pricing, enhancing customer acquisition and retention.
Another forward-looking approach to pricing unlocked by insurance digital transformation is usage-based insurance (UBI). It applies to policies that cover a particular asset and relies specifically on the actual usage and behavior of the insured asset or individual. Auto insurance, which is the most popular, includes driving behavior, mileage, and usage patterns collected through telematics devices.
Modern insurers should proactively educate and help their customers be safer and healthier. For example, they can reward annual health screenings and vehicle maintenance checks or offer discounts for installing home security systems, smoke detectors, and carbon monoxide detectors. These initiatives improve customer well-being and reduce the risk of claims, fostering a more sustainable and beneficial relationship between insurers and policyholders.
Embedded insurance
According to the Swiss Re report, by 2033, 15% of all insurance sales will be embedded [8]. Embedded insurance is a model where insurance coverage is seamlessly integrated into purchasing products or services, offering customers instant and contextually relevant protection without needing a separate insurance transaction. This approach leverages digital platforms, APIs, and partnerships with various industries, such as retail, travel, and technology, to provide insurance at the point of sale. For instance, when buying a new smartphone, customers can simultaneously purchase insurance coverage for damage or theft. This convenience enhances customer experience by simplifying the acquisition of insurance, increasing accessibility, and ensuring that coverage is tailored to the specific needs associated with the purchased item or service. Embedded insurance also benefits insurers by expanding their reach, improving customer engagement, and creating new revenue streams.
Read more: What defines a successful embedded finance integration
Embarrassing corporate responsibility and ESG
44% of insurance executives state that investing in ESG improved their company's financial performance [9]. This result might seem paradoxical initially, but there is a clear explanation. Firstly, investing in ESG projects requires overall improvement and optimization of the company's processes. Secondly, corporate responsibility is increasingly recognized by younger generations. 30% of Gen Z and Millennial consumers research a company’s ESG policies before making major purchases, and 44% consider these practices a deal-breaker when evaluating potential employers [10]. This shift in consumer and employee priorities underscores why ESG investments can improve financial performance for companies that commit to these values. ESG criteria and insurance digital transformation are complementary forces that drive the insurance industry toward a more sustainable, socially responsible, and well-governed future, improve social impact, and ensure robust governance practices, aligning with the evolving values of customers and stakeholders while achieving operational excellence and risk management efficiency.
Conclusion
Digital transformation in insurance is about fundamentally reshaping the industry by integrating advanced technologies and data-driven approaches. This transformation focuses on enhancing efficiency, accuracy, and personalization while aligning with modern society. It encompasses many initiatives, from improving customer experience with intuitive digital interfaces and personalized services to leveraging AI, machine learning, and IoT for better risk assessment, fraud prevention, and dynamic pricing.
How N-iX guides insurers through digital transformation
N-iX offers comprehensive digital transformation services, helping insurers navigate the evolving financial landscape. Our services include in-depth assessments of business transformation readiness, business and tech consulting, and full-cycle implementation. We help insurers modernize their solutions, implement new initiatives, and future-proof operations.
We provide end-to-end development services with over 2,200 tech consultants and over 21 years of experience. Our experts specialize in product design, cloud, data and analytics, AI and ML, IoT, RPA, and more. At any stage of insurance digital transformation, N-iX can offer valuable input on solving existing problems or advancing.
References:
- Edelman Trust Barometer: Insights for the Financial Services Sector, 2024
- 1 in 2 Millenials don’t have life insurance, Insuranks.com 2023
- DBIR, Verizon 2023
- Elevating customer experience, McKinsey 2023
- Insuranks.com
- Global Insurance Survey, Capco 2023
- Verizon
- World insurance market developments in 5 charts, Swiss Re 2023
- ESG in insurance, KPMG
- 2024 Gen Z and Millennial Survey, Deloitte
