Brokers rethink tech buying habits
Insurance brokers often rely on long‑standing relationships when selecting technology, but that same reliance can push them into costly choices. Recent commentary from industry experts points to three patterns that brokers should question before committing to new platforms.
First, avoid assuming the cheapest solution is the best fit
Many brokers equate lower price with lower risk, yet the report notes that “the instinct to favor familiar, lower‑cost tools can quietly lead brokers into decisions that cost far more than they should.” A cheaper system may lack the scalability needed for multi‑country operations, forcing firms to replace it sooner than anticipated. The hidden expense of migrating data and retraining staff can outweigh any initial savings.
Second, scrutinize AI promises against real‑world needs
While generative AI has not created new fraud, it has made producing convincing false evidence easier, according to a recent analysis. This means a claims ledger that integrates AI must be robust enough to detect subtle inconsistencies. The article warns that “a connected claims ledger makes it easier for insurers to detect” fraud, but only if the underlying technology is designed with verification tools that are thorough. Brokers should therefore evaluate whether AI features genuinely address their specific risk detection challenges or simply add complexity.
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In practice, the difference between hype and utility often shows up in how a system handles data integration. This practical lens helps separate useful innovation from unnecessary features.
Third, consider long‑term durability over short‑term trends
Veteran tech builder Tobias Bergmann, founder and CEO of tigerlab, stresses that “technology that holds up over the long term” is essential for brokers. He also notes that AI should be positioned as a tool, not a replacement, for core processes that have proven reliable over decades.
When a broker evaluates a new solution, the decision should include a review of its upgrade path and compatibility with existing infrastructure. A platform that requires a complete overhaul every few years can become a financial drain, especially for firms that handle large volumes of policies across multiple jurisdictions.
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The insurance sector has often seen technology cycles that promise rapid transformation but fall short when regulatory changes arrive. The current focus on AI mirrors earlier attempts to digitize underwriting; both waves highlight the need for solutions that can endure beyond the next software release.
Brokers must weigh cost, AI relevance, and durability before signing on with a vendor.
