Identifying who was at fault in a motor accident (referred to as a liability decision) is a difficult task and an historical area of weakness in the motor insurance industry. There are a number of problems with the liability process which increase claims costs throughout the industry.
First Notification of Loss (FNOL) is the process where a customer first notifies their insurer. These calls are generally handled by contact centres where employee turnover is high. Contact centre roles are often low paid, employee engagement poor and handler error is common as a result.
A poor liability judgement at FNOL can cause claim delays and result in significantly higher costs being incurred by the insurer later in the claim process. Poor liability judgements can also impact an insurer’s reputation and customer satisfaction levels.
An incorrect liability decision may be costly, but even a slow liability judgement at the outset can affect the insurers ability to retain control of the claim.
Whilst liability has been a significant area of friction in the industry for some time, Rainbird is the first technology recognised as capable of truly automating this process, providing a model of liability that is capable of delivering comprehensive complex judgements.
Rainbird was assessed by AIS as an ideal tool because of its ability to host and run a nuanced decisioning process. They recognised that Rainbird could make decisions based on real-world handler experience and live claim data. They also appreciated the benefits of Rainbird’s ability to provide a rationale for each decision which serves as a full audit trail.
AIS put their team of liability experts through the Rainbird Developer Programme so that they could use the Rainbird platform to encode their own knowledge.
Rainbird’s open architecture made it easy to integrate the new model of knowledge into a web tool, although AIS also intend to license the API directly, for easy integration into existing systems.
Rainbird takes each claim’s data and compares it with it’s knowledge map using a process called cognitive reasoning. When it needs more data, it can ask efficient questions using a simple chat interface. The result is an accurate judgement, using a probabilistic method similar to that used by human experts.
Rainbird handles any uncertainty and missing data and simply takes that into account when providing feedback.
Each outcome includes a rationale and a full audit trail backed by evidence, satisfying the client’s obligations to Treating Customers Fairly (TCF) and their other regulatory obligations.
By implementing the solution within a liability process, Insurers and others in the motor claims industry can expect to see a material improvement in both the accuracy and consistency of front end liability decision making whilst also obtaining a detailed record of how and why each decision was reached.
Based on current industry claim costs, even a reduction of 2% will yield savings of more than £40 per claim.