Loss adjustment automation in the age of customer centricity

Are developments in technology intensifying customer expectations in loss adjustment processes? 

The last fifteen years have seen a huge leap in technology for mankind – from CDs and the internet in internet cafés, we have moved on to artificial intelligence and cloud technologies. Along with these changes there also came a cultural leap, as we have quickly become accustomed to the convenience that new technologies provide. Not just in the field of entertainment; we want to renew insurance policies with the same ease as we renew our Netflix subscription.

The average person doesn’t want to run away from technology. They give in to it and thus, even unknowingly, begin to build their customer experience.  They slowly build up an experience related to a particular company, gaining experience at all points of contact and throughout the relationship: from the moment they realise there is a product/brand/service at all to the moment they abandon the offer. 

Therefore, in order to keep abreast of the times and put the customer at the centre, the insurance industry should also integrate all its projects around a positive customer experience. And since the customer journey from loss notification to the issued decision may be very different (unfortunately often negative), it is this process that is worth focusing on first. 

Customer experience impact on the insurance industry

According to research, one in three Generation Z representatives consider customer experience to be the most important factor when deciding whether to use the services of a particular company. And although this is currently the youngest generation, it is worth remembering that it is already becoming an insurance sector customer, and is about to develop into a target group. 

The data show that 19% of the customers abandon a company completely after a bad experience, and up to 40% of digital customers choose a vendor based on motives beyond price. Here we are already entering the area of customer service, and thus also the area of loss adjustment, where the customer, after all, is not purchasing a new product, but wants to use the service they have paid for. 

Along the way of shaping the quality of the experience, the customer has become accustomed to a degree of care with which they are comfortable and secure. They like to feel that there is a human being on the other side (in this case the adjuster) who, when the customer is experiencing harm, will understand and lead them by the hand.

Customer expectations in the loss adjustment process vs. benefits of automation

Taking all this into account, we can draw the first and quite obvious conclusion – customers’ habits correlate with their expectations.  Today’s customers of insurance companies:   

• Expect a quick response from the company.  They want the company to operate effectively and solve their problems efficiently;  
• Want to be kept informed of the progress of the loss adjustment process and understand what steps are being taken (this is not obvious to every customer);  
• Expect a competent and responsible service.  They want to avoid a situation in which the compensation is too low compared to the actual losses, so they expect a fair and reliable appraisal; 
• Believe that insurance companies should support them in formal matters in order to make the loss adjustment process as easy as possible (there are people with varying levels of intuitiveness of technological solutions among customers);  
• As a key expectation want quick payment at the end of the loss adjustment process;  
• Also expect to be able to easily contact the insurance company if there are any questions on their part or if they wish to obtain information on the status of the loss; 

• When differences of opinion arise regarding the loss appraisal, customers expect the insurance company to endeavour to resolve the disputed issues.   

It is difficult to satisfy all of the above customer expectations without implementing at least basic automation in the company. Further on, we will show how the challenge is being handled by large insurance companies and we will present our own proposals to improve the daily work of adjusters and insurance companies.

How does the market respond to the challenge related to losses? Overview of solutions

The classes of solutions used in the area of loss adjustment are numerous and can be divided into three main blocks:  

1. Solutions using artificial intelligence, including generative AI or LLM (large language model), which at the same time extend the capabilities of other solutions already on the market;  
2. Solutions to support the back-office (such as risk assessment and reporting);  
3. Solutions to support, among other things, self loss adjustment, enabling faster receipt of decisions and ongoing tracking of the claim process. 

What is the market currently using?

Current popular technology trends supporting the work of insurance companies include: 

• Application of AI in fraud detection – solutions trained on historical data (based on analysis of reports) to help detect instances of potential extortion;   
• Automated consultants (voicebots, chatbots) – used for a long time, but now being developed extensively. The main advantage is their high availability and immediate response to customer enquiries. Unfortunately, a few years ago, automated consultants had much less intelligence at their disposal, which makes many people negatively inclined towards them. Today everything depends on how they are implemented in the process. They work well, for example, when notifying the customer of a change in the status of the loss, but not as the main “employees” of the customer support department; 
• Self loss adjustment – mobile applications and customer websites that put some of the work of the adjuster in the hands of the customer (e.g. taking photographic documentation of the loss directly in the application). Thus, they give the customer the feeling that the case is better taken care of by keeping them updated on the status of the loss;  
• Interpretation of document content – combining OCR with artificial intelligence. Solutions that read notifications or even medical records themselves and, on this basis, are able to make their own decisions on claims and even benefit amounts; 
• Automated loss level assessment – visual AI-based solutions that assess the level of loss (e.g. vehicles that have been damaged or property that has been flooded) based on the uploaded images and provide a preliminary loss appraisal. 

There are also minor solutions on the market that facilitate the loss adjustment process, for example, in the form of applications that support the valuation of household goods or remote services for people who are hearing impaired. 

What is the customer’s concern in the loss adjustment process?  

To answer the question of how to improve the loss adjustment process, it is first necessary to recall and capture the main reasons for customer dissatisfaction in the process: 

How to effectively automate the personal bodily injury adjustment process? 

For example, let us have look at the personal bodily injury adjustment process and how we could automate it while remaining customer centric:

As you can see from the graphic, we can already use chatbots and online customer service, as well as natural language processing (NLP) at the loss report stage. Chatbots can assist with customer service and provide information on reported losses through various communication channels (website or application). And technologies responsible for natural language processing will help analyse and understand the content of loss reports, e-mails or documents. They will enable the automation of claims verification and processing.  

Equally, at the claim stage, we can give the customer the opportunity to report the loss via a mobile application, including uploading photos and documents, but also the ability to track the progress of the adjustment process online. The same application could be used by the customer at the claim reporting stage, for example, but here we pose an open question: would insurance companies want to make this particular bit of the process easier for customers? ? We leave the response to your individual consideration. 

Looking further at the granularity of the process, artificial intelligence and machine learning can be introduced in statutory letters and when the adjuster should already have made a final decision on the ninetieth day to grant or refuse a benefit. However, considering the whole process, technology could also enable the analysis or assessment of a loss report, be able to detect a suspicious claim, predict the behaviour of anonymous customers and provide automatic e-mail communication with the customer. And let us not forget that machine learning, as well as data analysis, can be used with huge data sets to create risk models and predict losses. 

It is also worth noting the potential of the Power BI tool, a business intelligence solution that allows users to connect, analyse and share data from different sources to get a more complete picture of the business situation. This is particularly useful, for example, in the context of national regulations requiring additional financial and statistical reports from insurance companies. In this aspect, Power BI enables the creation of relevant reports, while in terms of the overall process, the solution would also enable, for example, the creation of interactive dashboards. 

Integration with external systems is also extremely important, e.g. when the adjuster needs to obtain a medical opinion from a medical examiner or obtain an expert report, confirm the circumstances of the incident or pass on instructions to an external law firm if the company receives a lawsuit in a particular case. 

Workflow engine vs. the personal bodily injury adjustment process   

Ultimately, the application of all these solutions will of course effectively optimise the loss handling process, but it is worth looking at the whole thing holistically at this point. Given such a perspective, it seems reasonable to implement a workflow process engine. Basing the entire loss adjustment process on this type of engine enables much greater automation, increases the flexibility of the system to implement changes to the existing processes and provides better support for new processes.   

In addition, the workflow engine can provide, among other things, task monitoring, detection and rapid response to irregularities, as well as the ability to apply dynamic business rules to control workflow. As part of the process engine, we are able to automate, for example, the dispatch of refusals to customers at the stage when the adjuster needs to take a decision and, due to the lack of completed documentation, cannot grant compensation. The dispatch of 20- or 60-day letters can also be attached to the workflow.   

In terms of the capabilities of the workflow engine, we can also improve:  

• setting up provisions;  
• payment of annuities and reading accounts for payment;  
• annual verification of annuitants; 
• fraud detection; 
• anonymisation of documentation; 
• connection to reference databases, e.g. UFG;  
• recourse.   

Loss adjustment automation. How to streamline the process by putting the customer at the centre? 

In conclusion, let us have a look at what really needs to happen in the process to clear the bottlenecks and optimise the entire loss adjustment process in terms of maximising customer satisfaction: 

• Holistic automation of process tasks, translating into shorter loss adjustment time (use of OCR, image recognition, AI, ML, customer Self Service), as well as optimising insurance company costs;  
• Implementation of a Workflow engine and the orchestration of most tasks of the loss adjustment process, thus eliminating at least process bottlenecks and the need to switch between multiple systems. The workflow engine can also use artificial intelligence and machine learning to detect fraud; 
• Integration with external systems (handling, for example, medical opinions, expert reports/confirmation of the circumstances of an incident or community interviews, as well as with external law firm systems);   
• Automation of tasks that unnecessarily consume time (payment of compensation/benefits, annuities, anonymisation of documents, sharing of information among insurance companies). This will make the process smoother, which the customer will certainly experience.   

Sources:

• _{Mimo kryzysu firmy w Polsce nie rezygnują z inwestycji w IT – Puls Biznesu – pb.pl}
• _{„Epoka nowych doświadczeń. Raport Customer Experience 2023”, PZU, Digital University, październik 2023}
• _{Opracowanie własne na podstawie źródło https://www.ey.com/pl_pl/digital-first/doswiadczenie-klienta-customer-experience-czyli-zarzadzanie-doswiadczeniem-klienta}