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Build Trusted Data for Your Insurance Cloud Migration Initiatives

Authors Photo Precisely Editor | June 12, 2023

It is a challenge for insurance companies to increase organizational agility in the face of rapidly evolving business conditions and a changing regulatory environment. High inflation and an increase in claims have fueled escalating costs. The ongoing global pandemic has underscored the need for insurance carriers to be highly responsive and adaptable to change.

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Technology offers new ways for insurers to innovate, automate, and streamline. Insurance companies that use artificial intelligence and machine learning (AI/ML) technology, for example, are competing aggressively and winning market share.

An Accenture study estimated that underwriters are spending approximately 40% of their time on non-core activities. Automation and AI/ML are helping carriers to drive out those kinds of inefficiencies, which experts estimate will cost the industry between $85 and $160 billion over the next five years. The same Accenture study found that up to $170 billion in premiums is at risk, as customers who are dissatisfied with claims processing switch carriers.

The business case for modernization is very clear, but there’s a more important and even more difficult journey for mainframe modernization. New technologies are delivering transformational results.

As companies have modernized their systems to adapt, many have chosen to move to the cloud. According to McKinsey, businesses that have taken the lead on cloud migration tend to outperform their peers. They’re unlocking innovation, agility, and digital transformation, generating some $1 trillion in business value. That’s a huge opportunity, but that opportunity also comes with some risks and challenges.

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Read this eBook to learn best practices for modernizing data integration for the cloud, helping you to ensure project workloads, budgets, and timelines are within your target goals.

The Drive Toward Mainframe Modernization

Many companies in the insurance industry still rely upon mainframe systems to process their mission-critical transactions. This has created some especially difficult challenges:

Escalating operating costs: Increased usage and MIPS-based fees result in higher operating expenses than ever before. At the same time, mainframe companies rely on a shrinking base of customers, leading to annual price increases that drive costs even higher.

Shrinking pool of mainframe talent: To maintain and operate mainframe systems, insurance carriers need experienced specialists on staff. Many of the senior employees who know how to manage, build, and maintain the mainframe environments have retired in recent years. Many others will approach retirement age in the coming decade, and virtually no new college graduates are stepping in to replace them.

Lack of agility: To take advantage of the newest advances in technology, insurers must have the capacity to use their data efficiently and effectively. Data silos create significant barriers to cloud transformation. Mainframe modernization increases business agility and helps to secure a foundation for future technological transformation and maintenance. In this context, data integration is more critical now than ever before.

Making Cloud Transformation a Reality

As these mainframe challenges intensify, businesses of all sizes are moving to the cloud. Organizations must proceed with caution, however. While 55% of leaders cite data modernization as a key reason for migrating to the cloud, the move also comes with risks. According to McKinsey, approximately $100 billion of migration spend will be wasted over the next three years. Three-quarters of cloud migration projects are over budget, and 38% are behind schedule.

These statistics highlight the need for a different way of thinking about cloud transformation, prompting many organizations to choose a hybrid cloud approach. Hybrid cloud is the optimal choice in terms of flexibility, improved control, increased security, and data management practices that fully conform to local and regional regulations. The hybrid approach also lends itself to high levels of data availability. That, in turn, can drive data-informed decisions based on real-time information.

Modern techniques like change data capture (CDC) help companies replicate data across multiple databases and platforms in real time. CDC eliminates silos and opens the door to data-driven innovation. For companies that run mainframe systems, it’s critical to work with a CDC vendor that understands mainframes and the data they contain.

Freeing Siloed Data

Data silos in most organizations are growing. As a company onboards new applications, or as it engages in M&A activity, the company often inadvertently creates new silos. The goal isn’t necessarily to consolidate all those silos into a single system. Rather, it is to integrate mission-critical systems in a way that serves the needs of the business. That includes the ability to navigate successive waves of future technological evolution.

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This raises the topic of data integrity, which is a business imperative. Forbes, the Harvard Business Review, and Precisely’s own Data Trends Survey all indicate that data integrity is an enormous challenge for most companies. Two-thirds of executives say that siloed data negatively impacts their data initiatives. Almost half of newly created data records or data elements have at least one critical error. It’s no wonder, therefore, that 84% of CEOs say that they doubt the integrity of the data on which they make their decisions.

To achieve higher levels of data integrity without the associated risks of a big-bang cloud migration, companies should consider an incremental approach to cloud transformation. By using technologies like change data capture in conjunction with a broader suite of data integrity tools, companies can achieve the transformational results they seek with cloud migration.

Precisely Connect simplifies integration between mainframe systems and popular modern platforms such as Snowflake, Confluent, and Kafka. With the Precisely Data Integrity Suite, you can use a single solution to integrate, prepare, load, cleanse, and stream data from your mainframe system to AWS, GCP, Azure, or other popular cloud platforms.

That enables organizations running mainframes to continue operating those stable and reliable systems to process millions or even billions of transactions per hour. CDC integration keeps that data in sync with the cloud in real time, making it available for reporting, data augmentation analytics, warehousing, and more scalable and resilient data applications. Precisely Connect CDC offers high-performance replication that’s able to recover from network and database connectivity loss.

Read our eBook 5 Tips to Modernize Data Integration for the Cloud to learn best practices for modernizing data integration for the cloud, helping you to ensure project workloads, budgets, and timelines are within your target goals.