Within the insurance sector, there has been a massive acceleration toward digital channels and automation, particularly in claims management. With the overnight shift to remote working, claims surges resulting from the havoc wrought by the pandemic, and customers moving to mostly digital communications channels, insurance providers have been hard-pressed to keep up.
In response, the market has seen an increase in the take-up of new AI and claims management software platforms to facilitate processes and new working challenges. However, adding this technology into long-established processes which also rely on legacy systems and a workforce under strain creates challenges. Using an intelligent automation platform is a great way to support connectivity between both old and new technology while helping to improve processes from the inside out. This enables the people on a claims team to focus on helping customers rather than on time-consuming data tasks or manually moving a claim along to settlement.
A transformation plan for claims should look holistically at the whole journey, from the pain points that any new technology is solving to an examination of the efficiency of processes at each stage of a claim.
Intelligent automation is a great example of how AI and a digital workforce combine and work together to produce a better claims service. As well as combining these capabilities, the digital workforce also brings other systems, both legacy and new, into the process to create a seamless experience.
What Is FNOL? And How Is It Used in Motor Insurance Claims Management?
First notice of loss (FNOL) is a great example of how we can see this in action. Motor insurance providers are leading the charge in rolling out electronic first notice of loss (eFNOL) capabilities, meaning that customers can start a claim through an application via an app on a mobile phone, handheld or desktop device in real-time. Following a road accident, for example, a driver can immediately start a claim through an app, taking photographs of the accident, the damage, and the position of any other vehicles involved to support the claim and uploading them. They could even submit recorded testimony from witnesses. This frictionless process gets the claim off to a great start and helps to process it more quickly.
The completion of the form on the device is the starting point for triggering the automated claims process. Data provided by the customer is automatically logged into the system and the next task can be triggered, such as AI capabilities within the enterprise automation platform analyzing the photographic evidence. AI can be used to check that the vehicle is as described before the accident and detect any modifications to the vehicle that might invalidate the policy. It could also help providers ensure the photographic evidence aligns with the events as described in the details of the claim, evaluating any impact damage to vehicles or other positional discrepancies.
The digital worker can also pick up and process other documentation provided by the customer in the claim form or via other channels such as email or online portals. Documents can automatically be sent for fraud analysis if required.
Once the visual evidence has been processed and analyzed with AI, the digital worker can access information associated with vehicles of that type, age, mileage, and value, along with information about the potential to fix the damage to the vehicle, based on legacy data and details of the insurance policy in question.
In these instances, digital workers can use standardized data to quickly decide whether it is cost-beneficial to the insurer to repair the vehicle following the accident or if it is a total loss. In the event of a total loss, the digital workers can give a fast decision to the claimant, enabling a quick settlement and payment into the claimant’s bank account.
Motor claims, and in particular those resulting from an accident, typically involve multiple steps, significant delays, and uncertainty and anxiety for claimants. By using intelligent automation, the insurer can provide a fast and seamless experience for customers and deliver a swift resolution in what can be trying circumstances following an accident.
The benefits to the insurance provider extend beyond delivering a first-class customer experience. The insurer is also able to contain some costs associated with the claim, including storage of the vehicle, third-party inspections and quotes to potentially fix the vehicle, as well as third-party claimant costs such as vehicle rentals during the lifecycle of the claim.
There will of course always be cases where digital workers are not able to make a decision and fully automate a claim. For instance, where the cost of repair is very close to the cost of a total loss, or where the value of the vehicle is above a set value or threshold. In such instances, the claim is passed on to a human adjuster for investigation or adjudication, to ensure a correct decision is reached. In these situations, human and digital workers collaborate on the claim but with the digital workforce picking up the time-consuming data processing tasks, the human adjustors can focus on their analysis and decision.
Automated FNOL: Using Automation for Complex Insurance Claims
Beyond auto insurance, travel insurance is another area where we see intelligent automation being deployed successfully. An example of this is an insurer who is using the enhanced capabilities embedded within the intelligent automation platform to handle claims when an individual becomes sick or injured while in a foreign country. Typically, these types of claims involve large amounts of paperwork (from doctors, hospitals, hotels, and travel operators) in multiple languages and containing multiple currencies. For adjustors, gathering all of the information and putting it into a coherent and consistent format can be extremely time-consuming work.
What Technologies Are Being Used by Insurers to Automate FNOL?
One travel insurer is now using digital workers and embedded functionality such as optical character recognition (OCR) and a translation engine to extract meaning, context, and understanding from all of the documentation that is provided. Digital workers can understand the value of invoices (and thresholds can be set for high-value claims), spot-check all of the data, values, and currency conversions, and automatically and instantly payout on the claim. If there are any data points or values that the digital workers do not understand or if there appears to be a discrepancy in the information provided, the claim is passed on to a human adjuster for evaluation and then given back to the digital worker for the execution of the payment.
The deployment of the broad range of capabilities embedded within an intelligent automation platform, including OCR, natural language understanding, and translation capability, is giving time back to claims handlers, freeing them up to focus on high-value cases, leading to more accurate and cost-effective decisions, and delivering a faster, more seamless experience for customers.
Delivery of eFNOL using automation is likely to become far more common across lines of business shortly, as firms accelerate their shift towards an augmented workforce. The increase in the use of AI and digital workers to access data around legacy vehicle costs, assessing ‘’damaged-to-fixed’ costs against online vehicle valuations.
However, over the next few years, we will see insurers increasingly using intelligent automation in decisions as well. Using AI capabilities not only to evaluate data in real-time but also to make data-driven decisions is incredibly powerful within insurance processes and a potential game changer for insurance providers.