First Notice of Loss (FNOL) is the first notification to an insurer after a loss, bodily injury, theft or damage to an insured property. It is the first step in claims processing and plays an important role in the success of insurance companies, impacting both profitability and customer retention.
The challenge is that while new technologies are lowering insurers’ FNOL collection costs, many customers require a human touch when filing FNOLs after a tragic event.
Here, we introduce the FNOL and evaluate its importance and share the optimal FNOL strategy for insurance companies.
What is FNOL?
FNOL is the first step of claims processing. To complete the FNOL, policyholders or third party claimants provide the insurance company with the following information:
- Policy number
- Incident details as date, time and location
- Incident description and type of the loss
- Claim supportive documents such as: Police reports, medical reports, expert reports
- If it is a car accident, the policyholder should also provide information about the other party’s insurance information and driver’s license.
Why is FNOL important?
The FNOL process is critical to understanding the initial claim’s amount or determining whether or not it is fraudulent. Claims processing expenses equivalent for 70% of the premiums collected for property insurance, making it the largest burden for insurance companies.
In addition, the first moments after a tragic event are also crucial for customers. The way insurers proceed with the FNOL process has a direct impact on customer loyalty. EY study shows that for 87% of customers, effective claims processing is a criterion for choosing a provider.
Top 5 technologies that ease the FNOL process
New technologies create new opportunities for both policy holders and insurers to submit/receive a FNOL. Deloitte discovered that during the COVID-19 Pandemic, insurers increased their adoption of digital channels such as mobile apps, with some handling more than 50% of claims in this manner. Chatbots can automate the processing of digital claims and communicate with users on mobile apps and messaging services to enhance customer satisfaction.
- Policy number
- Time and location of the accident
- Recording damages by taking videos or photos.
- Police report, etc.
Chatbots and voice bots are useful in capturing FNOLs through:
- Call centers
- Online chats on
- The insurer’s website
- Mobile apps of insurance companies
- Messaging apps like WhatsApp.
Challenge of chatbots
Insurers need to be sure of the effective functionality of their chatbots since ineffective chatbots can lower customer retention rates because they cannot help policyholders in a convenient way during their difficult times. Therefore chatbot company you collaborate with becomes important
Insurance companies should also keep in mind that not all people are digitally literate: for instance, 16% of adults in the U.S are not capable of handling digital technological tools.
In this regard, insurers need to adopt chatbots responsibly. They can use behavioral analytics or conduct surveys to understand the digital literacy of their customers and could serve certain customers with chatbots. Having a button that directs customers to a live agent if they wish also a capability insurers should keep in their minds.
2. Digital channels
More than 20% of customers already use digital channels to submit their FNOLs. This percentage is expected to increase as we become more accustomed to digital platforms. To help policyholders submit their own FNOLs, insurance companies can develop their own websites or customized mobile apps to simplify the FNOL submission.
No-code platforms can assist insurers to build an app since they don’t require code writing.
3. Optical character recognition (OCR)
OCR is an AI-based technology that recognizes handwritten digits and text. Due to strict regulations, handwritten documents are part of claims processing. In the case of FNOL, police reports are usually handwritten. In addition, claim reports detailing the accident/theft and damage may also be handwritten, as the insurance company requires the policyholder’s wet signature. In such cases, OCR helps insurers automate information capture from handwritten documents and increase the operational efficiency of the company.
4. Computer vision
Computer vision is the technique by which AI models can infer meaning from visual inputs such as images and videos. Computer vision models predict the cost of the claim to the insurance company by evaluating the videos and photos taken and uploaded by the policyholder or claim adjuster. In this way, computer vision helps allocate the insurance company’s financial resources more confidently.
Insurers can also use the IoT to verify information provided by policyholders to FNOL. For example, the location, time and date of a car accident can be verified through a smart vehicle’s memory. By using telematics, insurers can more effectively detect fraudulent claims that cost insurance companies more than $40 billion annually in the U.S.
What is the optimal FNOL strategy for the insurers?
Despite its importance, a clear FNOL strategy is challenging because:
- Customers may demand different levels of digitization in this step. For example, some prefer fully technology-enabled FNOLs, others prefer a human touch with experts completing FNOLs, and still others prefer a mix of both.
- Different insurance products have different FNOL requirements.
In the case of business insurance, for example, 22% of customers prioritize fully digital claims processing when selecting a provider. On the other hand, another 22% demand communication with experts. According to McKinsey, insurance is the sector that customers need human contact the most to solve their problems.
Consequently, insurers face a trade-off between cost-friendly automation and customer retention, for some customer segments. According to Deloitte, pre-millennials may require less digitized FNOL processes. Thus, insurers should determine a dynamic strategy by considering the following factors:
- Generational shift: By 2030, millennials and post-millennials (those born after 1997) will constitute almost half of the adult population. Having been born into a digital world, these people are likely to value physical interaction less. Thus, by time, optimal FNOL strategy requires a greater investment on digital transformation.
- User understanding: As customers’ needs vary, insurers can now profitably address each customer if they understand their requirements. They can introduce different segments with different levels of digital claims processing. In order to determine segments they can use behavioral analytics.
- Clustering damages: It is ineffective to apply the same FNOL strategy to all claims. Larger claim amounts may require more physical interaction, as more panic and stress may cause customers not to use digital platforms. In this regard, the use of telematics can be beneficial for insurers to approximate loss amounts.
This approach involves having multiple FNOL processes. A more risky alternative would be to have a delightful default digital channel for different FNOL types to push digital adoption and maximize automation benefits possibly at the cost of alienating some users. And for complex cases, non-digital FNOL processes may still be necessary.
If you struggle to find optimal claims processing strategy you can read our article on claims processing transformation.
If you want to learn more about claims processing automation you can read our Top 3 Insurance Claims Processing Automation Technologies article.
If you need more information regarding the latest in insurtech and identify top vendors, we can help.
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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