Insurers achieve an average improvement of 2–4 percentage points in their loss ratio using inca’s AI-powered loss ratio optimization. To do this, inca uses over 140 AI agents to review each claim for consistency, plausibility, and potential for optimization – before the final settlement – in order to specifically reduce claims costs through AI.

Internal controls and fraud department audits rely on random sampling and rule-based identification of suspicious cases. inca automatically checks every single case for consistency in its content – comprehensively, without fatigue, and detects patterns that rules or the human eye cannot see. At the same time, inca strengthens the evidence for already identified suspicious cases and makes them more enforceable.

inca performs four core checks: Coverage and liability validation (12 AI agents), automated fraud detection including document forensics and liability fraud detection (42 AI agents), expert opinion and invoice validation (63 AI agents), and subrogation detection (29 AI agents) – always as a comprehensive assessment of the claim, not as an individual check.

Unlike traditional tools that merely compare items against databases, inca checks the consistency of the entire claim: Does the repair item match the damage pattern? Does the extent of the damage correspond to the vehicle model? Duplicate items, paint areas inconsistent with the damage, and deviations from the original condition are automatically detected – with documented justification for every reduction.

For every case with cost-saving potential, inca prepares a comprehensive case report that includes a line of reasoning, supporting evidence, and the legal basis – along with communication strategies designed to facilitate implementation that also meet the requirements for the burden of proof. This gives the insurer everything needed to act with confidence and transparency.