Insurers Target AI and Modern Systems Amid Compliance Struggles

The 2024 Earnix Industry Trends Report reveals that, despite an ambitious plan by 70% of insurers to deploy predictive AI models within the next two years, fewer than 30% have managed to fully implement AI technologies to date, reflecting the significant challenges involved in transitioning from traditional to advanced systems. The slow progress underscores the ongoing difficulties faced by the insurance sector, often hampered by outdated infrastructure and the complexities associated with integrating new technologies.

The potential benefits of AI for real-time decision-making are well-recognized within the industry, yet the integration is made complicated by prevalent legacy technologies that many insurers still rely on. Compliance pressures present another major concern, particularly for European and Australian insurers who are subject to strict regulations such as Solvency II. Nearly half (49%) of insurers have incurred fines due to compliance issues, turning attention towards strengthening regulatory frameworks and making necessary investments to avoid such penalties in the future.

Siloed systems compound these difficulties, with 47% of insurance executives highlighting them as significant obstacles to innovation and collaboration. Additionally, the lengthy implementation timelines pose further challenges; 58% of executives noted it takes over five months to make rule changes, which is especially disadvantageous within a rapidly evolving market. Modernizing underwriting rules is similarly cumbersome, with just 30% of insurers able to update them within three to four months.

The findings indicate a growing consensus among insurers regarding the necessity to adopt modern technologies in order to maintain a competitive edge in the market. The Earnix report emphasizes the importance of overcoming these barriers to achieve effective integration of AI and improved compliance management, ultimately enhancing the overall efficiency and responsiveness of the industry to market demands. This detailed analysis highlights key points and trends, providing a roadmap for insurers to address existing inefficiencies and meet regulatory demands while modernizing their operations.

Explore more

How B2B Teams Use Video to Win Deals on Day One

The conventional wisdom that separates B2B video into either high-level brand awareness campaigns or granular product demonstrations is not just outdated, it is actively undermining sales pipelines. This limited perspective often forces marketing teams to choose between creating content that gets views but generates no qualified leads, or producing dry demos that capture interest but fail to build a memorable

Data Engineering Is the Unseen Force Powering AI

While generative AI applications capture the public imagination with their seemingly magical abilities, the silent, intricate work of data engineering remains the true catalyst behind this technological revolution, forming the invisible architecture upon which all intelligent systems are built. As organizations race to deploy AI at scale, the spotlight is shifting from the glamour of model creation to the foundational

Is Responsible AI an Engineering Challenge?

A multinational bank launches a new automated loan approval system, backed by a corporate AI ethics charter celebrated for its commitment to fairness and transparency, only to find itself months later facing regulatory scrutiny for discriminatory outcomes. The bank’s leadership is perplexed; the principles were sound, the intentions noble, and the governance committee active. This scenario, playing out in boardrooms

Trend Analysis: Declarative Data Pipelines

The relentless expansion of data has pushed traditional data engineering practices to a breaking point, forcing a fundamental reevaluation of how data workflows are designed, built, and maintained. The data engineering landscape is undergoing a seismic shift, moving away from the complex, manual coding of data workflows toward intelligent, outcome-oriented automation. This article analyzes the rise of declarative data pipelines,

Trend Analysis: Agentic E-Commerce

The familiar act of adding items to a digital shopping cart is quietly being rendered obsolete by a sophisticated new class of autonomous AI that promises to redefine the very nature of online transactions. From passive browsing to proactive purchasing, a new paradigm is emerging. This analysis explores Agentic E-Commerce, where AI agents act on our behalf, promising a future