Guest post by Dene Rowe, group chief marketing officer at Davies, which owns defendant law firm Keoghs
No professional sector is immune from automation – even one as specialised and nuanced as law.
While there is still no replacement for human expertise in complex cases, we are seeing automated processes improve efficiency, take over mundane tasks and enable lawyers to spend more time focusing on the briefs that really need their attention.
However, the adoption of automated systems to settle routine injury claims raises a number of important ethical questions.
The case for automation
Many lawyers are rolling out intelligent systems that automate straightforward tasks or assist human decision-making across the entire value chain. Implementing an automated claims processing workflow – including claims intake, assessment and, finally, claims settlement – eliminates friction and costs by combining machine learning and human expertise to streamline and speed up claims-related operations.
As more digital tools come to the fore, lawyers and insurers can apply accelerated claims-handling and automated decision-making to an increasing proportion of their overall cases, thereby boosting claims professionals’ productivity while freeing up capacity.
However, in some cases, automation raises the questions as to how individual circumstances can be taken into account for claim types where they are material to the settlement amount. This becomes even more pertinent where automation processes have been established solely based on previously settled historical cases of similar types.
The question arises, however, as to whether using historical data is a reliable base to make a settlement decision and whether this technology can provide lawyers with a consistent method of providing objective, fair and precise compensation structures for claimants that can be flexible when evaluating individual injury claims.
When looking at motor claims in particular, as a result of the implementation of the Official Injury Claims (OIC) portal, the historic methods of valuing minor motor injuries that also fall outside of the whiplash tariff definition, probably some 40% of the total volume, have become obsolete.
One claim can often represent several smaller claims rolled into one, with multiple parties, suppliers and claim types – such as vehicle damage, car rental and injury – to be managed.
The caveat to achieving full automation in claims is that certain aspects of the process or scenarios will require complex judgement, investigation or the human touch, such as managing a claim that requires a more tailored settlement decision.
In the OIC portal example, a vast number of claims will not have a previous case law that can put the compensation amount into perspective, therefore automated systems do not have the past data to rely on to provide the correct settlement amount.
Yet integrated, automated claims processing for the high-volume motor claims environment is now a reality, capable of fast deployment and significant scalability.
Claims handlers will need to remain in the driver’s seat to take control and handle critical elements and it is vital that automated mechanisms are able to identify when the situation requires human intervention and can manage the interaction between handler and machine effectively.
By incorporating efficient, automated process management with skilled claims handlers, insurers can build an automation process that delivers a fair and just settlement for a claimant.
The main task for claim leaders will be two-fold:
- How to master the effective integration of multiple technologies and analytical tools at their disposal to deliver seamless automated claim processing and decision support for claim handlers in a way that improves the outcome for claimants; and
- How to safeguard against incorrect algorithms basing future settlements on unrepresentative past data to ensure a fair and just outcome for all.
Perhaps borrowing a phrase from the investment industry should be the prime consideration when it comes to effective automation: past performance is no guarantee of future results.