The insurance industry is in the midst of a tech-driven shift. With data and analytics capabilities becoming table stakes for P&C insurers, accelerating the claims process through automation and advanced technologies is a key area to drive improvements in and streamline workflows. Particularly during the claims triage process at First Notice of Loss (FNOL)/ Electronic Notice of Loss (ENOL), straight-through processing (STP) has seen major growth over the last few years – while table stakes in underwriting, it is becoming more common in personal lines transactions.
Still, according to Aite-Novarica’s 2023 report, less than half of insurers are using STP in personal lines transactions, with an STP rate of 7% – relatively similar to the firm’s findings back in 2021.
STP adoption can be challenging for organizations within which legacy systems are embedded. There’s also a limitation for STP that can come from a lack of reliable or available data.
But when customer experience and speed are differentiators in an increasingly connected and digitized insurance ecosystem, implementing STP for insurers only makes good business sense. Technology advances are opening up new opportunities for insurers to implement STP with minimal disruption to their existing processes, while speeding up triage and processing at FNOL. Here, we’ll discuss the value of implementing STP at FNOL, and how you can leverage technology to implement STP.
What is straight-through processing (STP) in insurance?
Straight-through processing (STP) in insurance is the ability for insurers to automatically process transactions without manual intervention.
Systems take in data digitally and complete the transaction in a process handled by automation and algorithms (this could be predictive models, for example) rather than people. STP can apply to underwriting and first-notice-of-loss in claims as just two examples.
The benefits of implementing STP at FNOL: Improving Operational Efficiency
The overarching benefit of implementing STP at FNOL is solving the familiar issue of claims handling efficiency. The claims handling process has traditionally been slow and labor-intensive, requiring significant time and resources.
However, with straight-through processing, insurers can process claims quickly and efficiently, often within minutes of receiving the initial notification of loss. This saves insurers time and money and ensures that policyholders receive prompt and effective service.
In addition to improving efficiency and accuracy, STP has helped insurers reduce costs associated with FNOL processing. By automating routine tasks and streamlining workflows, insurers can reduce the need for adjuster involvement, which can be costly and time-consuming. This, in turn, can help insurers reduce their overall claims processing costs, improving their bottom line and enabling them to invest in other business areas.
#1 – Reducing severity
Straight-through processing at FNOL can significantly reduce severity for insurers with its ability to reduce errors and inconsistencies during the FNOL process. With automation, claims data is captured and processed in a more consistent and standardized process, reducing the risk of errors or omissions.
When automating the many manual tasks involved in the claims process, insurers can reduce the need for human involvement from call center agents, adjusters, legal, and SIU, which can be a significant cost saver. In addition, STP can help insurers spot fraudulent or exaggerated claims more efficiently, lowering their overall claims costs.
#2 – Increasing scalability
Implementing STP at FNOL has been a game-changer for insurers looking to scale their FNOL capabilities. With the power of automation, insurers can easily handle higher volumes of claims while reducing manual tasks and freeing up resources to focus on more complex claims. This has allowed insurers to improve customer service, providing faster and more accurate claim resolution even during catastrophic events.
For example, Clearspeed Surge was developed to help insurers quickly and confidently process large claim volumes during catastrophic, weather-based events. During a “surge” event, call volumes can increase more than 50x, with the risk of opportunistic claims fraud growing exponentially for insurance carriers. Clearspeed Surge provides short, simple, and automated voice questionnaires that detect risk with greater than ninety-seven percent accuracy.
#3 – Improving customer experience
It may not be straightforward to measure in hard dollars how improving your customer experience factors into the equation, but focusing on retention is a good place to start. The average retention rate of personal lines insurers is just 84%, while a few top-performing insurers are in the range of 93% – 95%.
So what is the number one reason why policyholders change carriers? We all know the answer to this one: a bad claims experience. Today’s policyholders expect their insurers to provide a seamless, hassle-free experience, from FNOL to final settlement.
By implementing STP at FNOL, policyholders can experience faster and more accurate claim settlements. Insurers can process claims more quickly, meaning policyholders can get the money they need to cover their losses more quickly. And because STP at FNOL reduces the risk of human error, policyholders are more likely to receive the correct amount of compensation.
This improves customer satisfaction and loyalty and helps insurers stay competitive in an industry that is increasingly focused on customer experience.
Watch the On-Demand Webinar: Claims Experience Innovation – What’s Next?
#4 – Reducing fraud exposure
One of the key benefits of STP is its ability to reduce errors and inconsistencies during the FNOL process. In addition to improving the accuracy of claims data, STP at FNOL also helps insurers identify potential fraud or other issues early on in the process.
El Roble Seguros, the largest auto insurer in Guatemala, implemented Clearspeed to help facilitate STP at FNOL to enhance their claims process. Read more about how El Roble Seguros achieved 31x ROI with Clearspeed in its first year.
#5 – Reducing Human Error
STP at FNOL reduces the risk of human error by performing repetitive and time-consuming tasks in the claims process. Incorrect data entry, miscommunication between parties, and failure to follow proper procedures are some common examples.
STP at FNOL also augments the human expertise of claims adjusters by freeing them up to focus on more complex claims.
Leveraging voice analytics for STP at FNOL
Of course, like any new technology, implementing straight-through processing at FNOL is not without its challenges. Insurers will need to carefully consider how they integrate this new approach into their existing claims processing workflows, and they will need to ensure that they have the correct systems and processes in place to support this new way of doing business.
While most insurers have invested in predictive analytics to enable STP at FNOL, voice analytics platforms like Clearspeed are an example of a simple and easy but highly effective way to support STP at FNOL.
Traditionally, many insurers have turned to Predictive Analytics and Natural Language Processing (NLP) to enable STP and FNOL. The challenge insurers face is that NLP applications require a large amount of data from your core systems and that data has to be accessible, available, and accurate.
The more data analyzed, the greater the accuracy of identifying fraud patterns. NLP applications require time, measured in months, to learn from your specific data before generating accurate predictions.
Accessing data, especially with legacy systems, continues to be an expensive and time-consuming proposition. Even If your core systems are on a modern platform with open API access, is your data available and accurate?
Voice analytics converts speech into unbiased and language-independent data. This data is analyzed for the presence or absence of risk-associated vocal characteristics, with incredibly high accuracy (>97% based on a study with the US Department of Defense.) The insurer can use those results to fast-track low-risk claims with greater confidence, and focus its resources where there is an alert.
The results from voice analytics are similar to those from NLP: they are not a determination but rather a risk alert. The voice analytics generated risk alert can be a unique data point in a risk and fraud ecosystem to help enable STP at FNOL.
The benefits of using voice analytics vs. NLP include the following:
- Access to the data in your modern or legacy internal systems is not required
- Filtering out PII (Personal Identification Information) data is not required
- Voice analytics is easily modified by simply introducing new questions
- Voice analytics works within any customer touchpoints such as web, call center, and chat
Clearspeed voice analytics can help take STP at FNOL to the next level by providing a fast, accurate and unbiased risk insight, previously difficult and expensive to acquire from any other source.
Accelerate adoption of STP at FNOL with voice analytics technology
Successful organizations leverage analytics to capture data and transform it into intelligent insights. To date, the insurance industry has been slow to realize the benefits that voice analytics can offer, despite its technological advances over the past few years.
Groundbreaking voice analytics technology from Clearspeed can accelerate the adoption of STP at FNOL, enabling insurers to realize the benefits of:
- Reducing severity
- Increasing scalability
- Improving customer experience
- Reducing fraud exposure
- Reducing human error
in less time and with lower costs.