To keep up with the market trends, insurance companies increasingly adopt digital technologies. Forrester estimates that in 2025, the insurance industry’s spending on technology, including data analytics and AI, will increase by 8%. A McKinsey survey highlights a similar trend, reporting that more than half of respondents in the insurance sector expected generative AI to increase their business productivity by 10 to 20 percent.
In practical terms, insurance companies are transitioning from old (and sometimes outdated) legacy systems to modern digital platforms driven by data. In this post, we discuss why insurance data modernization is important, what benefits it may bring, which pitfalls await insurance companies on their digital transformation journey, and how to overcome them.
Why insurance companies must modernize their data
Data modernization for insurance companies and transitioning from legacy systems to advanced solutions can resolve a number of problems:
- Inefficient claims processing. Manual processes and slow legacy systems often cause delays in claims approvals and payouts. In a legacy process, insurers need to manage fragmented data, which is likely to contain errors resulting from manual entry. This prevents quick claims verification and risk assessment. Data modernization enables advanced automation and AI-powered analytics, streamlining claims processing workflows and improving accuracy.
- Security vulnerabilities. Insurance companies handle massive amounts of highly sensitive data: personal details, financial information, medical records. In a legacy system, the potential for data breach is usually higher due to outdated infrastructure and security mechanisms. However, with end-to-end encryption, real-time threat detection, multi-factor authentication, and strict access control, modernized insurance systems face much lower risks of compromising customer data.
- Compliance requirements. The insurance industry is heavily regulated. Many data protection and privacy laws such as HIPAA and the GDPR govern the way insurers handle customers’ personal data. Legacy systems often struggle to enable efficient compliance tracking and reporting mechanisms, exposing companies to the risk of penalties. Modern systems come with centralized data governance, automated reporting, and efficient auditing, ensuring transparency and accountability.
- Customer dissatisfaction. Customers want fast and efficient service. Outdated insurance systems generally fail to provide the level of service that today’s customers expect: instant quotes, mobile-friendly processing, real-time support. However, all of this is available in modern solutions that leverage advanced data technologies to enable hyper-personalization, omnichannel service, and various engagement techniques, raising overall customer satisfaction.
Key benefits of data modernization in insurance
Investing in cutting-edge data technologies and an effective data modernization strategy for insurance companies has many potential benefits, both short- and long-term.
| Insight-driven decision-making
Advanced systems enable real-time access to data, providing insurers with insights to improve the quality of business decisions:
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Data security and regulatory compliance
Modernizing data in insurance allows companies to implement effective security measures in conformity with data protection laws:
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Increased efficiency and cost optimization
Insurance data transformation removes manual processes and consolidates siloed data, accelerating processing through multiple digital improvements that help to optimize costs:
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| Improved risk management
Modern digital insurance systems have built-in AI-driven risk analytics and anomaly detection, helping insurers prevent fraud and minimize losses:
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Personalized customer interactions
Digital transformation of insurance data opens opportunities for seamless, hyper-personalized customer experiences:
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Dynamic scalability and future-proofing
Transitioning to modern insurance solutions provides a foundation for future integrations with emerging technologies in response to current market trends:
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Challenges of data modernization for insurance companies
Transforming data in insurance in order to migrate to modern systems may seem a daunting task. True, data transformation involves many steps with lots of details, all of which are critical for success. But with an actionable migration strategy and in partnership with a professional provider of data and analytics services, data modernization becomes a clear and logical process with achievable goals and tangible benefits.
Let’s look at the most common challenges that insurance companies face when planning modernization of their data management flows.
| Challenge | Solution |
|---|---|
| Integrating legacy systems may be difficult due to incompatibility with modern technologies. | Use cloud platforms with API-driven architectures that enable integration between modern and legacy components. |
| Data migration complexities may arise when data from multiple sources needs to be extracted and standardized. | Implement ETL (Extract, Transform, Load) processes that extract, cleanse, and validate data before loading it to a modern data warehouse or data lake. |
| Budget constraints may affect modernization of large-scale databases. | Adopt a phased migration strategy, prioritizing essential components. |
| Cybersecurity risks may arise due to potential data breaches during migration. | Implement strong security mechanisms such as end-to-end encryption and AI-powered threat detection. |
| Skill gaps may create difficulties in technology adoption for insurance company employees. | Invest in training programs for employees and partner with experienced data modernization consultancy companies. |
How to modernize the data management system in an insurance company
Effective data modernization includes the following key components:
- Cloud platform. By moving to a cloud environment, insurers get a scalable and flexible infrastructure that allows them to store and process large amounts of data. For some cases, the best solution might be a hybrid cloud platform combining on-premises and cloud capacities. Such a setup helps to balance costs and ensure the security of the most sensitive data.
- Data lakes and data warehouses. To enable centralized data management, the platform needs data lakes for storing raw data and data warehouses for structured storage. Data lakes receive data from multiple sources and provide access to analytical applications, while data warehouses enable quick data retrieval for decision-making.
- AI-powered analytics. Analytical applications using AI to process data and generate insights accelerate and optimize insurance processes, automating claims processing and supporting personalized customer relationships. Predictive analytics can help insurers assess risks and develop optimal pricing strategies.
- Real-time data processing. Cloud solutions that enable access to real-time customer data help insurance companies improve service and accelerate decision-making. At the same time, they raise the quality of risk assessment, enhancing the customer experience and protecting the insurer’s revenue.
- Data governance. Implementing a strong data governance framework can help insurers remain compliant with evolving regulations. AI-powered automation can take care of regular compliance verification, reducing potential risks.
Future trends in insurance data modernization
In the insurance industry, digital transformation and data modernization are underway. Companies are taking steps to accelerate and optimize their workflows with modern data-centric technologies. For example, Statista’s global survey of healthcare insurers shows growing adoption of AI, with as many as 75% of companies using it in customer service and 50% in claims management.
AI adoption by healthcare insurance worldwide, 2024
The role of other data technologies in insurance modernization is also growing:
- Streaming data platforms allow businesses to analyze real-time data coming from various sources, such as IoT devices, mobile applications, or social networks. Real-time data processing accelerates claims management and risk assessment, while IoT devices can improve quality and customer experience in health insurance.
- Cloud-based storage provides insurance companies with scalability and accessibility while creating opportunities for cost optimization. Leveraging cloud computing, insurers can dynamically adjust their storage volumes based on the current load.
- Data democratization supports access and use of data by non-skilled professionals. Modern analytical tools come with intuitive interfaces and present data in a clear format. This allows users with no technical background to work with data.
- Automated data flows and autonomous systems are gaining traction as technology takes over routine processing tasks. Many data operations, such as data entry and data validation, can be fully automated, increasing efficiency and reducing error rates.
- A data-driven culture has become a strong value for many insurance companies. Recognizing the importance of data as a growth driver, businesses prioritize data proficiency in their talent pool formation.
Client stories of successful data modernization
As an experienced provider of data and analytics services, Intellias is committed to assisting businesses in the financial services and insurance industries on their path to data modernization.
Data governance platform for a financial institution
For a global bank seeking to improve data management through a more effective method of integrating data from multiple sources, we designed a data governance solution that enables centralized data processing. Leveraging advanced data technologies, our engineers created a platform that connects various data streams into a unified repository with improved visibility, strong security, and high operational efficiency.
Data migration for a financial solutions provider
We collaborated with a provider of retirement management solutions to migrate their data flows from a legacy system to a cloud-based environment. Using the capabilities of Microsoft Azure, we helped the company redesign their data processing approach by implementing a fast, scalable, and accessible data management platform.
Analytical platform for a debt management company
In partnership with an international provider of a range of debt management services, we developed a new platform for ingesting, processing, and analyzing data. The new architecture includes centralized data storage and an advanced business intelligence framework that generates valuable business insights. An updated approach to data management gives the company full visibility into all processes and enables data-driven decisions.
Ready to modernize your data?
Today’s focus on data sends insurance companies a straightforward message: If you have not migrated to modern data management platforms, do it now. Tomorrow may be too late.
With data at the core of most insurance-related processes, upgrading to digital solutions using emerging technologies becomes vital. Contact us if you need professional consultation and assistance with propelling your insurance business into the digital future.
