Insurance executives worldwide face increasing challenges, including rising combined ratios, mounting claims costs, and extended claims resolution cycles—all of which erode profitability. Compounding these issues is the reality of an aging workforce, with many experienced professionals set to exit the market within the next 3 to 5 years. To mitigate these pressures, insurers are turning to technology solutions to streamline their operations, enhance customer service, and reduce costs.
While core systems like claims and policy administration have become relatively standardized, insurers now seek incremental value from peripheral technology solutions that can automate and differentiate their offerings. These value-added systems, however, represent a more fragmented market with fewer well-established products or dominant vendors. This uncertainty can make selecting the right solution challenging, as insurers worry about achieving a strong and reliable return on investment. Additionally, the hesitation to share valuable intellectual property can create resistance to adopting commercial off-the-shelf (COTS) solutions.
Given this complex landscape, the option to build in-house may appear attractive. It promises tailored solutions, internal expertise, and control over sensitive data, all while leveraging emerging technologies like generative AI. However, in-house projects come with significant risks—especially when artificial intelligence is involved. AI initiatives are notorious for their high failure rates due to complex data requirements, integration challenges, and the need for constant updates to stay competitive. As the market rapidly evolves, insurers may find themselves struggling to maintain pace with technological advancements, incurring steep costs while losing out on innovations that are now widely accessible.
In this context, buying a ready-made solution presents a compelling alternative, offering insurers access to the latest technologies, quicker implementation, and lower risk. To help you navigate this decision, we’ve provided a detailed infographic comparing the pros and cons of building versus buying AI-based solutions.