Claim management, how technology turns it around

Claims management is the thorn in the flesh of insurance companies and policyholders, despite being an at least partly digital process. What better can the most advanced technologies, AI, big data, blockchain do? Startups will tell us

Published on 17 Jul 2019

Claim management is undoubtedly one of the insurance cornerstones and also one of its most critical issues, both for the complexity of its management, and for its delicacy being the most important touchpoint with the customer. Claim management is, for a Company, always the time for truth in its relationship with the customer: if the whole compensation process is effective, fast, transparent and satisfactory with regard to the latter, nothing more applies to the customer’s loyalty. The challenge is now even more demanding, as customer requirements have evolved and grown; what was once a ‘hope’ for the customer, is now a fair claim that, if not met, leads the party concerned to change Company as easily as changing a TV channel. 

How can digital transformation enhance claim management? 

Improving efficiency – Insurance claims settlement is only one of the hallmarks of the claims management process. The time needed to manage a claim involves several procedures starting with the claim reporting, and right here the customer experience is crucial. The next steps will assess whether the claim is justified (i.e. whether it is covered by the policy), true, and how much the insurance company will pay. The insurance companies are expected to be responsive and compliant, to be by customers’ side and not just a “concern in the dark”. Reducing the time needed to settle insurance claims is a way to reduce the number of customer complaints and improve service, increasing the level of satisfaction and giving the Company a competitive advantage. Digital transformation is a field where great results can be achieved: the use of software to manage the entire claim process, starting with the user, and with a high automation level, speeds up the process and minimizes costs. 

Reducing frauds – A further key aspect is the role that technology can play in fraud detection. Fraudulent claims are a well-known cost to companies, which the insurance industry then shifts to its customers, so the cost of fraud is borne by reputable clients. From software tools analyzing big data, to blockchain infrastructures, there are several solutions that the digital technology can offer to reduce the number of frauds to insurance companies, with benefits for both companies and customers. 

Reducing operating and staff costs – As mentioned above, digitalizing the entire claim management process leads to improving process efficiency to customer satisfaction. It also reduces the Company’s operating costs: process automation and collaborative digital tools (allowing all human resources involved in managing a claim to easily collaborate, share files, analyze data, take decisions), speed up the process and eventually reduce its cost. 

Which technologies have the greatest impact in this respect? 

Cloud, Artificial Intelligence and Machine Learning, Big Data Analytics, Blockchain, IoT, Chatbot are the technologies currently disrupting many industries, including insurance one. In particular, all these technologies (excluding Blockchain ) are already widely used and in being applied have proven their high potential, thus representing a field where new applications will be increasingly developed; Blockchain, being the most important technological platform since the same Internet, is also a growing trend, although more complex, where so far more trials have been carried out. 

The claim management startups 

Claim management is not for everyone. 

 “We have analyzed over 2,500 insurtech startups in Europe and only 15% of fully qualified insurance companies are engaged in claims settlement and fraud prevention. The remaining 85% focus on new distribution channels, new insurance products or risk assessment. No wonder, as claims and fraud are the links in a value chain requiring a mix of advanced technology and expertise not always running together”, said Florian Graillot, founder of astorya.vc, a venture capital company focused on European insurtech startups. 

Let’s see some starstups succeeding in this sector. 

The chatbots, (which are nothing more than an application of artificial intelligence) in claim management will be increasingly important. According to Gartner, by 2020, 85% of customer interactions will be managed by chatbots. Chatbot claims management empowers customers to automate the initial reporting process and make it available and easy to use 24/7. Any examples? 

Lemonade, a NY-based company that is one of the most funded companies, reported to have solved a claim in three seconds, via chatbot. Among the most funded insurtech startups there is also Trov, on-demand policies to protect personal assets, also featured by the use of a chatbot for claim management. 

Cove, a New Zealand startup has developed a chatbot technology for the entire process from purchase to claim. The founders strongly believe that artificial intelligence can make insurance more human. 

Spixii, an Italian-French startup, already in 2016 had conquered Open-F@b Call4Ideas 2016 with its chatbot. 

A less mentioned but ever more important technology for claim management is image recognition. 

For many years now, when digital technology became available, taking photographs has become much simpler and less expensive than it used to be. There is a huge potential in claim management as well, offering customers the possibility to gain more control in a long and unclear process. The Italian startup Insoore has partially seized this opportunity by offering insurance companies an innovative system to acquire images of vehicles by leveraging crowdsourcing, or through a platform linking the companies with thousands of detectors to create photographic records of insured vehicles, both Underwrite and Crash. If the photos taken comply with the acceptance criteria, the insurance company accepts the recording and Insoore transfers the payment to the user’s account. However, the image compliance is defined by human operators. 

The British startup Tractable, specialized in artificial intelligence in accidents and disaster recovery, went further by automating this process: using a database of over 130 million images of destroyed cars, it trained its systems to recognize the type of damage that a vehicle has suffered and to predict the likely repair expense, which can then be communicated to the insurance company. 

Recent breakthroughs in cloud computing, data storage, processing power and self-learning have made this technology available. 

Artificial intelligence, machine learning and data science are technologies designed to ensure a clear improvement in claims management, mainly if implemented throughout the process, and if can help claim managers. This is what the French startup Zelros has been doing: its end-to-end platform covers the entire back office activity of a company, helping staff to better manage sales on the one hand and claims on the other. In particular, the Zelros algorithms help to extract and make sense of information, reducing time and improving decisions. Astorya VC, the startup’s investors, wrote on their blog: “Insurance employees (claims managers, sales agents, risk underwriters) take their daily decisions on the basis of policyholder data. However, insurance companies usually work on a number of computer systems and databases (CRM, policy administration, risks, etc.) with access being limited to the required employees only. Most employees do not have access to such datasets or have to manually access many systems to collect unrelated information. It’s a nightmare. Zelros‘ founders, long-standing insurance employees, had a perfect understanding of the problem. Thanks to the technology (NLP, AutoML, SHAP, SHAP, etc.) Zelros allows insurance managers to access customer data scattered across many silos through a simple messenger (or a plug-in for any corporate messenger). By querying the company datasets, insurers receive customer information or sales suggestions based on the AI. Thanks to the artificial intelligence algorithms, in some cases, the answers are even received before the question is asked. The algorithm classifies claims according to complexity level, calculating fraud or eligibility scores and anticipating the type of resolution”. 

Another British startup, Rightindem, offers companies a solution designed looking at the customer experience, their slogan is ‘we help you delivering the claims service your customers are looking for’. It is basically a tool (also in the form of a chatbot) that the Company makes available to the customer who is self-sufficient in the management of the claim. The system allows customers to easily describe, in natural language, how the accident occurred and to add supporting photos and videos, helping them to file and handle the claim more quickly and transparently. 

Claim management requires a high effort in terms of time and human resources, many entities need to be coordinated (e.g. the policyholder, the insurance company, the mechanic) and there is often a lack of easy access to information. 

Claims Control, a Lithuanian startup, and Openclaims, a Dutch startup, offer collaboration platforms that bring together all the entities involved in claims management. This allows quick and easy access to information, sharing photos and keeping all communications in a single place. 

Insurance fraud is a very thorny and expensive problem for companies that new technologies and start-ups can help to solve. 

The French company Shift Technologies has developed a software-as-a-service (SaaS) that leverages big data and artificial intelligence, designed to detect potential insurance fraud and automate the claim. The company-owned software uses mathematical models and algorithms to detect fraudulent practices and supports claim managers in a much more accurate and faster decision-making process. Shift can always improve its algorithms and be ever more precise in detecting insurance fraud by working with many insurance companies and accordingly obtaining data from several databases. 

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