Insurance executives worldwide face increasing challenges, including rising combined ratios, escalating claims costs, and prolonged claims resolution cycles—all of which undermine profitability. Adding to these issues is the reality of an ageing workforce, with many experienced professionals set to leave the market within the next three to five years. To address these pressures, insurers are turning to technology solutions to streamline their operations, enhance customer service, and reduce costs.
While core systems such as claims and policy administration have become relatively standardised, insurers are now looking for additional value from peripheral technology solutions that can automate processes 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 remain concerned about achieving a strong and reliable return on investment. Additionally, reluctance 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 offers tailored solutions, internal expertise, and control over sensitive data while leveraging emerging technologies such as generative AI. However, in-house projects come with significant risks—especially when artificial intelligence is involved. AI initiatives are notorious for high failure rates due to complex data requirements, integration challenges, and the need for constant updates to remain competitive. As the market evolves rapidly, insurers may find themselves struggling to keep pace with technological advancements, incurring steep costs while missing out on widely accessible innovations.
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 have created a detailed infographic comparing the pros and cons of building versus buying AI-based solutions.
