Insurers are always looking for ways to increase efficiency while decreasing costs. One way to achieve this is by automating elements of claims processing. In this post, we’ll help you identify which claims can be automated, and run through the key benefits of automating claims processing.
How to identify the right claims types for automation
Look for high volume, low complexity claims
Machines are really good at handling simple tasks at high volumes, so it’s best to start with claims that are not too complex. This will enable you to see results quickly and get a good return on investment.
Look for desk-based work
Claims that can be worked on from a desk, without the need for onsite visits or assessments, are generally the easiest to automate.
Assess where automation unlocks the most value
Each insurer’s needs and goals are unique. Assessing where automation can unlock the most value for your business is crucial.
Automation doesn’t need to be applied everywhere. There are many tasks within the claims process that can still be handled manually without any downside.
What types of claims can be automated – and which can’t?
Automation can work on any type of claim, from home and health to motor and travel. However, it’s important to note that some claims may not be suitable for automation. For example, claims that require a high degree of human judgement and expertise may be more difficult to automate at the moment.
Additionally, some claims may require physical assessments that cannot be done remotely.
It also depends on the platform.
Some platforms may specialise in automating certain parts of the claims process. Others have specific tools for key assessments or activities that happen within a particular insurance line.
For instance, the claims automation platform we have developed here at Sprout.ai specialises in using generative AI, computer vision, and NLP to contextualise claims documentation.
The world of automation is constantly evolving
And the speed of change is increasing. It is now possible to automate increasingly complex claims, but labelled data is needed to train AI models accurately.
At Sprout.ai we have bridged that gap by implementing generative AI that creates synthetic claims data. This can be used to help AI engines understand complex claim scenarios more quickly.
Why automate claims processing?
Claims are an important moment for insurers. They are likely to be the first time a customer comes into contact with the company since they bought their policy. As such they are often the moment when the customers discover whether their purchase was worthwhile. This experience will determine whether they remain a customer, or move on to another insurer.
According to McKinsey, claims processing will be the most important function in the insurance industry by 2030. Meanwhile, poor claims experiences could put up to $170 billion in renewal premiums at risk globally over the next five years, according to Accenture.
Processing claims has traditionally been a slow, manual task. Legacy software cannot process unstructured data, so claim handlers must spend days sifting through forms, handwritten documents, PDFs and images to extract the relevant information. Once they have done all that, they need to check whether a customer is covered, and then initiate the payment. With the volumes of data available today, manually processing claims is more laborious than ever.
The benefits of automating claims processing
Our claims processing software is helping insurers to reduce the average time it takes to settle a claim from 30 days to less than 24 hours. In many cases, we enable instant settlement. Claims handlers have time to focus on serving their customers with empathy, speed, and transparency.
Process claims in under a day
Major insurers are now using our technology to empower rapid, intelligent claims decisions. We have reduced the average time it takes to settle a claim from 30 days down to less than 24 hours. In many cases, settlement is instant.
Higher customer satisfaction and retention
Faster, more accurate claims means higher customer satisfaction. We pride ourselves on directly improving insurers Transactional Net Promoter Scores and client retention. Claims handlers can focus on customer service, rather than collecting and processing claims information, reviewing policy terms, overseeing payments, and updating customer information.
Average human accuracy levels are around 80%, but we have achieved 98+% accuracy. This reduces operational costs, waste and leakage from human error is reduced. Fewer claims need to be reopened and there are fewer disputes.
Data-driven decision making
Our patented technology allows insurers to extract data that can be used to enrich and improve decision making, allowing for greater efficiencies..
Case study: How AdvanceCare is serving more customers, while maintaining an exceptional claims experience with Sprout.ai
AdvanceCare is using our technology to automatically extract relevant data from healthcare invoices. This follows a successful pilot, in which AdvanceCare cut down the claims settlement turnaround time to near real time.
Claims handlers no longer need to spend their time on low-value, repetitive tasks, allowing them to dedicate more quality time to tasks that are more valuable and rewarding, optimising the customer experience.
During the pilot, the work capacity per team member increased, while the work volume was lowered. AdvanceCare is now able to scale up its business by serving more customers, while maintaining an exceptional claims experience.