How Automation Can Support First Notice of Loss (FNOL) Reports

Close up of hands holding a smartphone and taking a photo at the scene of a car accident to submit as first notice of loss for a car insurance claimThe First Notice of Loss (FNOL) – the first step in claims processing – is one of the most crucial customer touchpoints for an insurer. Yet, for most carriers, FNOL continues to be a lengthy, manual, call centre-based service requiring extensive data gathering. This process translates to high operational costs and cycle time and a less than satisfactory customer experience.

Providing a fast, streamlined and transparent claims intake process is no longer aspirational; it is table stakes for customers who expect nothing less from their interactions with all their service providers, including banking, retail, and entertainment.

Luckily for insurers, the intelligent automation landscape has advanced significantly over the last few years, enabling insurers to innovate rapidly and cost-effectively.

Traditionally, the key barriers to change for insurers included long-established processes that rely on legacy systems and a workforce under strain. A transformation roadmap for claims starts with re-imagining the end-to-end customer experience at each stage of the claim. Intelligent automation and artificial intelligence (AI) offer a proven pathway to produce a better claims service while leveraging core legacy systems. Intelligent automation brings systems, both legacy and new, into the process to create a seamless experience.

Automating FNOL in auto insurance

With automated FNOL, following a road accident, for example, a driver can immediately start a claim through an app by 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 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 in the system, and the next task can be triggered, such as photographic evidence analyzed by AI. AI can 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 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.

A person holds a tablet displaying an insurance claims form

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 consider it a total loss. Digital workers can access data around legacy vehicle costs, making it easier to assess “damaged-to-fixed” costs against online vehicle valuations. In the event of a total loss, the digital workers can offer the claimant a fast decision, enabling a quick settlement and payment into the claimant’s bank account.

Motor claims, particularly 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 can also contain costs associated with the claim, including storage of the vehicle, third-party inspections and quotes to fix the vehicle, and third-party claimant costs such as vehicle rentals during the lifecycle of the claim.

There will always be cases where digital workers are unable to make a decision and fully automate a claim. For instance, where the cost of repair is very close to the cost of total loss, or where the value of the vehicle is above a set value or threshold. In these instances, the claim is passed to a human adjuster for investigation or adjudication to ensure a correct decision is reached. The human and digital workers can collaborate on the claim with the digital workforce picking up the time-consuming data processing tasks so that the human adjustors can focus on their analysis and decision.

Automating FNOL in travel insurance

Travel insurance is another area where we see intelligent automation successfully deployed. An example of this is an insurer that uses 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, containing multiple currencies. For adjustors, gathering all the information and putting it into a coherent and consistent format can be extremely time-consuming work.

However, travel insurers can now use digital workers and embedded functionality such as optical character recognition (OCR) and a translation engine to extract meaning, context and understanding from all the documentation provided. Digital workers can understand the value of invoices (including thresholds set for high-value claims), spot-check all 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 to execute the payment.

Benefits of intelligent automation in insurance

Deploying the broad range of capabilities embedded within an intelligent automation platform, including OCR, natural language understanding and translation capability, saves time for claims handlers. Intelligent automation enables claims handlers to focus on high-value cases, leading to more accurate and cost-effective decisions and a faster, more seamless customer experience.

Delivery of automated FNOL will soon become far more common across lines of business as firms accelerate their shift towards an augmented workforce. Over the next few years, we will see insurers increasingly use intelligent automation in decision-making. Using AI capabilities to evaluate data in real-time and make data-driven decisions is incredibly powerful within insurance processes and a potential game-changer for insurance providers.

Notable benefits of intelligent automation include:

  • Improved operational efficiency and faster claims settlement – 60%+ reduction in customer cycle time
  • Increased transparency – 90% reduction in settlement disputes
  • Reduction in claim expenses – 50%+ reduction in rental and storage expenses
  • Improved employee experience – 80%+ reduction in time spent on the phone collecting basic claim info from customer

By: Hiba Abdou, Head of Technology and Intelligent Automation

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