Enhancing the performance of Claims Organisations in the Digital Era – Overview New levers to enhance client relationships and economic performance

Changed customer behaviour resulting from experiences in other industries as well as advances in technology are unfolding new levers to enhance the performance of claims organisations. The traditional trade-off between efficiency, effectiveness, and customer satisfaction can be mitigated through technology, and a claims business transformation today promises straightforward benefits.

Our accumulated client experiences have shown, for example, that the combination of chat bots and AI-driven claims triage can allow for cost reductions of around 24% through a steep increase in straight-through processing (STP), whilst at the same time enabling real-time customer service and better accessibility. Beyond improving claims metrics, industry leaders have demonstrated how to turn claims data into risk ratings for individualised pricing, thus enhancing overall business performance.

From the abundance of opportunities available, insurers today can select technologies and transformation levers according to their overall strategic direction and the respective claims target dimensions in focus. In order to enable a structured view of those opportunities, we have aggregated 10 core levers and their business potential below.

Figure 1: New levers in claims transformation

Customer satisfaction in the digital era – Going beyond expectations

Against the learned experiences and promptness of digital services in other industries, customers may feel that many insurers have simply not been living up to their expectations. Insurers that do, however, deliver on customer expectations through a simple and seamless claims experience, transparency, and 24/7 accessibility, can build trust and loyalty, establishing a key competitive advantage in the industry. Our estimations show that the following 5 levers for enhanced customer experience in the claims process can increase the Net Promoter Score (NPS) after a claims experience by as much as 25%:

  1. Transparent claims journeys and status updates: Transparency is a key driver in today’s claims experience, and just as customers would expect to be able to check the location of a parcel, they can be given the option to live-track the status of their claim. Digital interfaces (e.g. mobile optimised websites and portals) allow for a complete overview of the claims journey with real-time information on the claims status (e.g. adjuster assigned, inspection dates).
  2. Digital claims recording: The recording of a claim through a web/mobile solution allows for an easy and real-time FNOL experience. The customer can be guided through every step and be given the possibility to submit claims information in various formats, including text, audio, photo, and video.
  3. AI-driven chat bots: Voice assistants have not exactly built up a reputation of great customer experience. However, AI-driven chat bots are becoming increasingly smarter and are able to understand the client’s mood so they can adapt responses accordingly. Against that background, chat bots can serve as an access channel for those customers that value quick information from immediate responses, independent of time and locality.
  4. Digital assistance: Mobile solutions (e.g. mobile websites) can enhance the service experience tremendously when a damage occurs. Step-by-step assistance on what to do, provision of emergency numbers, or navigation to the recommended repair shop – just to name a few examples – offer opportunities for insurers to prove their value for money at the ‘moment of truth.’
  5. Live video inspection: Remote inspection through a video call via the client’s mobile device could save the client both time and stress.

Based on persona-driven analysis of the claims journey and the identification of respective levers, we understand that even minor improvements can have a major impact, most notably the provision of transparent claims journeys and status updates. Even if the claims status is not updated in real-time right away, an overview of the necessary processing steps together with an estimated delivery time would already significantly increase customers’ acceptance of waiting times and overall satisfaction with the claims process. Find a deep dive article on opportunities for increased customer satisfaction here.

Efficiency – Decrease claims handling costs

The identified levers for claims transformation open up various possibilities to save costs through the automation of customer interaction and the reduction of repetitive manual processes. Our estimations show that the following 8 levers for efficiency enhancement in the claims process can allow for 50% STP rates and thus an enormous cost saving potential:

  1. Digital claims recording and AI-driven chat bots: When looking at the cost of claims handling, the digitalisation of customer interactions allows for a reduction of manual tasks and workload in call centres. While the digital channel might not cover complex issues, they could always be leveraged to increase STP of ‘standard claims and questions’ and ipso facto present a form of efficient triage in itself.
  2. Digital assistance: The digitalisation of assistance services can be leveraged to inquire data automatically. For example, apps allow for quick localisation, telematics and smart home devices for the analysis of the damage, and thus enable a much more targeted service, reducing cycle times.
  3. Live video inspection: The leverage of mobile devices for damage assessment can save costs and manual processes of validation suppliers, especially for medium-value claims (too high for direct settlement, too low for manual inspection).
  4. AI-driven triage and initial indemnity decision-making: The deployment of AI to classify claims and then take rule-based actions accordingly, is one of the biggest levers of technology for efficiency in claims handling. For example, by scanning claims data for specific variables, AI can filter out claims that can be serviced in a straightforward manner from potential cases of fraud, litigation or subrogation, etc. After classifying a claim by its potential severity, artificial intelligence can determine which level of validation is needed, decide on claims routing and assign a case to a claims handler accordingly.
  5. AI-driven claims estimation and prediction and automated fraud detection: Through the ability to process enormous amounts of data and to detect correlations, artificial intelligence systems are increasingly suited to predict the severity of a claim, as well as its potential for fraud. By matching pre-defined variables of a claim to historical claims and cost data, AI-systems can also derive first estimates on indemnity – as of now, however, they mainly function as support systems for the manual estimation process.
  6. Digital supplier management and invoice validation: Portals that connect suppliers and insurers can reduce frictions and speed up communication through a streamlined transfer of data and claims documents. They can also be leveraged to integrate supplier scheduling tools and are thus advantageous for steering and automated routing to suppliers. What’s more, the digitalisation of repair invoices in the process allows for automated validation of professional fees through comparison with historical and external data.

Whilst all of these levers allow for significant increases in efficiency, our experience shows that the cost saving potential increases exponentially if the levers are combined to allow for STP of entire claims categories. For example, by successfully deploying automated fraud detection tools together with invoice validation solutions, insurers can offer STP for automotive claims regarding certain spare parts beyond standard claims such as wind screen damages. Find a deep dive article on opportunities for increased claims efficiency here.

Effectiveness – Control of indemnity spend

In order to control the indemnity spend, or in other words, to be able to improve the calculation of the exact amount to be paid out for a claim under a certain policy, insurers have to make use of one of their greatest assets: historical claims data. Using historical data as a benchmark, predictive analytics and artificial intelligence solutions can increase the accuracy of claims assessment and fraud detection. Our estimations show that the following 4 levers for effectiveness enhancement in the claims process can reduce claims leakage by around 20-30%:

  1. AI-driven claims estimation and prediction: The deployment of technology in claims estimation can reduce one of the main reasons for claims leakage: human error and poor decision-making. AI systems can spot patterns that were previously undetected by traditional means of calculations, and therefore allow for an increase in the accuracy of rules engines.
  2. Automated fraud detection: The ability to detect fraud is a main driver of indemnity spend, and opportunities to leverage technology in the process are manifold. Depending on the format of provided claims information, insurers can enhance manual processes with solutions like voice analysis, automated detection of photo alteration, link analysis (analysis of relational structures between persons and objects), and advanced predictive modelling, to name a few.
  3. Digital supplier management and invoice validation: The digitalisation of interactions with validation and fulfilment suppliers helps to reduce claims leakage through better oversight and quality control. Automated validation of professional fees through comparison with historical and external data is yet another opportunity to reduce leakage.
  4. Enhanced data insights for reserve setting: Reserve setting has always been data driven. However, with the increased number of (external) data sources alongside real-time data, actuarial calculations will produce a much more accurate figure to set for reserves.

Our experience has shown that the deployment of AI solutions in claims estimation can be quite a precarious process, with a lot of resources spent towards ensuring the required historical claims data is available for further processing in the first place, not to mention the need to define and refine respective models. In order for an AI to surpass the accuracy of manual claims assessments, insurers need to train not only the respective AI systems, but also the people dealing with them. However, an insurer that is tackling the challenge is already setting the prerequisites for leveraging its wealth of data thorough the entire insurance value chain. Find a deep dive article on opportunities for bettering claims effectiveness here.

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While the new levers for claims transformation illustrate clear potentials to both ameliorate the qualitative and quantitative performance of the claims organisation, they are highly dependent on sound data preparation on the one hand and the flexibility to integrate new systems into existing claims operations on the other. With many insurers facing, more often than not, obscure and complex IT and data landscapes, our experience shows that specific use cases in claims can trigger a process to continuously make data more readily available to business functions. The straight forward opportunities in claims can thus serve as a catalyst to enhance the organisation’s overall ability to transform – a necessity in our digital era.

To discuss further, please contact london@zeb.co.uk.

Bertrand Lavayssière

Partner Office London

Milena Rottensteiner

Senior Consultant Office Frankfurt

Marcus Li

Analyst Office London

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