
보험
AI Adoption and the Insurance Industry
Today’s insurance companies are embracing AI and using more data science across different applications. In the process, these companies are improving profitability, becoming more efficient, and delivering an enhanced customer experience.
Today’s insurance companies are embracing AI and using more data science across different applications. In the process, these companies are improving profitability, becoming more efficient, and delivering an enhanced customer experience.
AI와 보험
DataRobot provides insurers with unrivaled power to optimize their market selection, underwriting, pricing, and claims management operations. Using DataRobot in insurance enables you to deploy analytics in a fraction of the time it usually takes, delivering enhanced speed to market, more accurate machine learning pricing, reduced loss ratios, and higher conversion rates.
전략적 리스크 선택
- Identify the most profitable prospects
- 전환율 가속화
- 견적 정확성 개선
- Increase renewals while reducing “churn”
- Inculcate “best practices”
정밀한 보험료 및 예치금 설정
- 최첨단 머신러닝 알고리즘 활용
- 재프로그래밍없이 보험료 설정 모델 배포
- 손실 비용의 정확성 향상
- 5 – 15배 빠른 요율 산출
- 청구 건별 개별 손실 산출
- 수익금으로부터 정확한 예치금 설정
청구 관리 최적화
- 자동 또는 수동 처리를 위한 청구 식별
- 부정 청구 가능성 표시
- 대위변제 가능성 파악
- 청구 심각성 및 대형 손실 가능성 예측
- 결과 기반의 업무 분배로 손해사정사 성과 향상

보험 산업 사례 연구
There is no function in insurance that will be unaffected by the adoption of artificial intelligence and machine learning. Besides automating and informing traditional processes, AI and machine learning create new capabilities that empower insurers to optimize every function in the insurance value chain.
Check out all Insurance use cases