Increasing the Efficiency of Claims Operations in the Digital Era – Deep dive New levers to save claims handling costs

On average, we estimate that UK P&C insurers spend up to 80% of total premiums on claims handling and indemnity. Being sandwiched between changing customer demands, regulatory requirements, and a low interest rate environment, the pressure for insurers to reduce claims handling costs is self-evident.

However, from our experience, manual processes are still predominant in claims organisations – a fact that comes at a high cost. For example, the challenge to cover peaks and marginal hours at stable service levels force up staff counts, while often work flow systems are struggling to optimally triage claims, thus allocating skilled personnel on simple or repetitive tasks. Claims handler fail to deal with the increasing availability of data sources, and logic patterns remain in the dark.

Figure 1: Cost drivers in claims handling - examples

With customers increasingly preferring to use digital communication channels on the one hand, and with technology opening up the possibility to automate back-end processes on the other, economic opportunities arise along the entire claims value chain. These opportunities and the extent of their economic potential very much depend on the insurers’ client base, its capability to change, and the degree to which it already leverages technology in the claims cycle. However, our accumulated experience shows that around 60% of P&C claims qualify today for straight-through processing (STP) by means of leveraging advanced automation tools – a potential that is yet rarely exploited.

While we have introduced the levers of that opportunity in our overview article, we will now take a closer look at cost saving potentials in claims handling along the value chain.

Figure 2: Opportunities for increased efficiency along the claims value chain - examples

 

FIRST NOTICE OF LOSS (FNOL) Offer digital channels, process ‘simple’ claims straight-through, and route to personal channels for complex issues

The FNOL inhibits a large cost saving potential through leveraging digital customer interaction channels. What’s more, digitising the claims information at the FNOL is important to be able to enhance the processes both further down the claims and the overall insurance value chain. In order to properly enhance efficiency, however, digital channels have to be carefully integrated with traditional ones. Chat bots, for example, can be used as a first touch point that could then route to the call centre if complex issues such as the involvement of a 3rd party are detected. Likewise, call centre staff can push links to online recording tools to the claimant’s mobile in case of a simple claim. Overall, with the omnipresence of smartphones today whilst digital reporting tools are becoming increasingly smarter, certain P&C insurers can strive to route up to 80% of claims through digital recording.

Digital claims recording: The advantage for efficiency is clear-cut. The digital intake of claims information ensures that the information can be streamlined to unify the data for further processing. Today, many software (as a service) suppliers are offering platforms that enable claimants to self-submit a case. By ‘outsourcing’ the recording of a claim to the client, we estimate that the service centre can be relieved of around 10 minutes per claim on average.
Examples of suppliers include: RightIndem; Pega; Snapsheet; VIZION; ControlExpert; 360Globalnet; Verisk Analytics

AI-driven chat bots: Chat bots can be increasingly deployed to answer questions about existing claims as well as to accept a notice of loss. Thus they represent another lever to relieve workloads of call centres and to digitally record claims data for facilitated utilisation further down the insurance value chain. Chat bot solutions are manifold, and a prominent example is Lemonade’s AI Jim. Software-as-a-service providers differ mainly in the performance of the AI they are based on, key criteria for the selection would be whether they already have claims specific data training and if they are able to recognize client’s moods.
Examples of suppliers include: IP Soft; avaamo; api.ai

Automated fraud detection: Fraud detection in the FNOL can take on various forms, which is why technology suppliers offer an array of solutions with distinct functionalities. Applications to cross-reference different data bases in order to filter out claimants that are especially prone to fraudulent behaviour are proving to be especially helpful in enhancing manual assessments. Other useful applications are voice analysis and automated detection of photo alteration. The automation of fraud detection is key to securing high straight-through processing rates without losing control of indemnity spend.
Examples of suppliers include: Dence digital evidence for cross-referencing data; Verisk Analytics for picture alteration; nemesysco for voice analysis

Digital assistance solutions: Positioning a connected device at the point-of-need/location of loss can drive efficiency in many ways: telematics devices can provide information about the geolocation, to be then matched with the nearest repair shop, petrol station etc. If necessary, they can send out an automated SOS signal so that the relevant emergency services can come to the customer’s aid. For simple claims in motor insurance, the digital assistance, analysing key metric such as voltage in the vehicle, might even be able to provide step-by-step instruction to the driver as to an appropriate course of action. Unlike engineers, digital assistance solutions have the advantage of real-time insights, rendering processing times to 0, as well as reducing the need for on-site repair visits for simple cases. In a nutshell, smart IoT devices will again relieve the service centre as well as fulfilment suppliers.
Examples of suppliers include: ControlExpert; Vizion; Pace; OCTO; Openbay; and interesting best practices are Allianz – MyTripBuddy; Ford- Mi.Ford; Volvo – Volvo On Call app

 

LOSS ASSESSMENT Filter out claims for straight-through processing, and enhance manual processes with smart assessment tools

The application of AI in claims assessment may challenge today’s insurers. However, we believe that it will be a key competitive factor and turn the understanding of ‘efficiency’ in claims upside-down. The more accurate AI’s and their respective models become, the more cases can be processed in a straight-through manner, until eventually claims processes are fully automated. Today, the amount of claims that an AI flags up accurately for STP depends on the level of training, and the STP-rate is dependent on a certain risk appetite on the part of the insurer. From our assessment, AI can already quite accurately filter out simple bulk claims and thus, after around 6 months of training alongside manual assessments, enable straight through processing of ~50% of P&C claims (including standard claims like wind-screen damages).

Automated triage and initial indemnity decision-making: Based on established variables set by the insurer, AI can determine the right course of action in real-time. If the claim is clear-cut and/or of minor enough nature, the indemnity decision can be made E2E within seconds.
Examples of suppliers include: Verisk Analytics; Tractable; cognotekt; Cognitive Scale

Automated claims estimation: AI-solutions can analyse claims information in all formats, including pictures and videos, to generate an initial estimation of claims costs. Those estimations can serve as a basis for claims handlers and in turn speed up the estimation process. We believe that AI will be able to outperform human adjusters in the near future, so that the deployment of AI in claims assessment becomes a key factor for future cost savings.
Examples of suppliers include: Verisk Analytics; Tractable

Save costs through remote video inspection: Remote video assessment will probably not be a game changer like AI, but it is already been tried and tested in the industry (e.g. Lemonade). More specifically, medium-value claims (not too low to qualify for direct settlement nor too high to require manual inspection) can be assessed through a live video call via the client’s mobile device, saving time and effort for both parties.
Examples of suppliers include: Odigo; MotionsCloud

 

FULFILMENT/REPAIR – Relieve the burden on service centre with chat bots and increase control through portal solutions

On top of leveraging chat bots to handle service requests (described in the previous paragraph), digital supplier management allows for further efficiency gains in the fulfilment stage of a claim. More specifically, digital communication between claims handler, clients, and suppliers through portal solutions improves the efficiency in the transfer and validation of data and claims documents. At times, a streamlined relationship to fulfilment suppliers can be utilised to increase control and guaranteed delivery times. Furthermore, contracts and banking information can be integrated into supplier scheduling tools to increase the speed of delivery. Through the friction reductions and speeding up of processing times, our assessment shows a potential decrease of Full Time Equivalents (FTEs) by around ~5%.
Examples of suppliers include: ControlExpert; Guidewire; Quantoz; Eucon

 

SETTLEMENT/CLOSURE – Relieve service centre and technical staff through automation of repetitive tasks

In the settlement stage of a claim, automation potentials and efficiency levers are highly dependent on the specific workflows of the insurer. However, repetitive and easy manual tasks connected to the closure of a claim, e.g. the updating of accounting systems and reporting, allow for further efficiency gains through automation.

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In a nutshell, the identified levers will allow for increased cost savings as well as considerable reductions of cycle times. We believe the fastest insurer to implement these levers will benefit from a competitive advantage that will be hard to catch up to. It should thus be on every insurer’s agenda to carefully assess their current claims processes and to strategically define use cases.

Bertrand Lavayssière

Partner Office London

Milena Rottensteiner

Senior Consultant Office Frankfurt

Marcus Li

Analyst Office London

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