Trend #2: Analytics Turn Data into Actionable Risk Management Strategies
Claims success was once measured by speed and fairness. Today, leaders are looking for more and expect their claims professionals to be proactive, predictive and aligned with broader risk management strategies.
Data and advanced analytics help meet this need. For organizations with large volumes of loss data, these tools can extract meaningful insights that improve outcomes across a risk portfolio, without conducting time-consuming audits in every location.
Data and analytics tools can pinpoint:
- Where exposures are coming from, helping target risk management strategies to address the most vulnerable areas
- Underlying causes of loss, enabling clients to implement effective prevention strategies
- Patterns that might otherwise go unnoticed, helping to stay ahead of emerging risks
As claims data becomes more actionable, risk managers can make more informed decisions about insurance coverage and risk management — critical in an increasingly complex risk environment. For example, these tools can help quantify risk and get insurance limit recommendations.
Yet, challenges remain. Many large organizations have accumulated dozens — or even hundreds — of different systems through acquisitions or decentralized operations, making it difficult to achieve a single, unified view of claims data.
The process of data collection and data sharing, combined with AI mechanisms, heightens the exposure to cyber threats. A high level of cyber security, robust controls and a well-defined incident response plan are essential to mitigate this risk.
“Insurance markets tend to view AI mechanisms as components of the broader computer system and therefore include them within the scope of cyber insurance policies. As reliance on and exchange of online data increases, so too does cyber risk exposure — making it essential to use appropriate tools to safeguard data and mitigate risk,” says Pablo Constenla, Aon’s Head of Cyber and Financial Lines Coverage and Claims for Europe, the Middle East and Africa.
Partnering with brokers and insurers can help bridge these gaps and deliver insights across systems via comprehensive claims analytics dashboards.
How to use data and advanced analytics tools effectively:
- Benchmark claims performance against peers to assess exposure levels.
- Identify recurring loss drivers and implement targeted risk controls.
- Invest in training teams to interpret data and analytics tools proactively.