Built upon best practice machine learning technology, the modelling processes adopted are used extensively in healthcare, insurance and financial services, where data varies and extremes are common.
PREDiCT Predictive analytics to drive improved performance
Here at Weightmans we have long recognised that historic large loss claims data could be the key to delivering insights, shaping strategies and informing early settlement offers. This realisation has led to the creation of PREDiCT — a predictive data and analytics capability developed by our in-house data scientists utilising data from over a 1100 individual claims harvested over a 12 year period. PREDiCT provides actionable insights to drive improved performance around reserving accuracy, reduced lifecycles and overall indemnity spend.
Unlock the potential of PREDiCT for the benefit of your business
High value injury claims present significant practical challenges; not only is the reserving process often carried out with limited insight into the severity of a Claimant’s injury, it is also conducted against a backdrop of rising claims inflation, uncertainty surrounding the Discount Rate and wider economic volatility. All of this can lead to protracted claims lifecycles and indemnity spend leakage.
These all impact on claims performance and bottom-line profitability.
To tackle these challenges head on, we are transforming the conventional way of handling large loss claims.
How can PREDiCT help you?
Improved reserving accuracy
PREDiCT uses a Meta model trained on our significant data set to deliver optimum reserving in the context of a particular claim.
In July 2021 we conducted a full market launch of PREDiCT. Over the last 18 months we have analysed its success, focusing on the performance indicators below:
Average PREDiCT modelling outputs were within 13% of ultimate paid outcomes, compared with 208% on client-approved reserves
This improved accuracy has opened the potential for the release of significant capital lock-up for reinvestment purposes.
Reduced claims lifecycle
Cases on which PREDiCT was used to inform pro-active case handling strategies delivered a 27% reduction in median claims lifecycle.
Lower overall indemnity spend
Using TBI as an example, we have seen reduced lifecycles result in median savings of over £24,000 per case – £1.2m for a book carrying 50 claims with this injury classification
Making the complex simple
PREDiCT mitigates the lack of claim information at initial reserving by modelling for different outcomes, enabling handlers to validate their own thought processes.
Accelerating settlement times
PREDiCT outputs can be used to inform early Part 36 offers without first gathering a body of expert evidence.
We believe the benefits of PREDiCT are clear — BUT we recognise that there will be concerns about its efficacy and compliance.
Lets talk more about PREDiCT
Lets talk more about PREDiCT
If you would like to speak to a member of our PREDiCT team for further information and to arrange a free demo, fill in our enquiry form and we will be in touch.Contact us