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How AI helps claims handlers provide a better customer experience

Ericson Chan, Zurich Insurance’s Chief Information and Digital Officer, recently announced that Zurich is starting to experiment with OpenAI’s natural language processing tool ChatGPT in claims and underwriting.

AI can create “a huge amount of efficiency” in jobs such as extracting information from long documents and writing code for statistical models, he told the Financial Times. Zurich UK already uses our AI technology to settle claims in real time.

The arrival of ChatGPT has prompted many in the insurance industry, and further afield, to wonder – and worry – whether AI will replace humans.

Here at Sprout, we have always been convinced that AI is not here to take humans’ jobs, but help them offload repetitive tasks. Our AI-powered claims processing software takes jobs like reading documents and inputting data off claims handlers’ plates, so they can focus on high level work and an empathetic, differentiated customer service.

“The idea that AI will replace people altogether, has  been a broad misunderstanding of AI in the Insurance Industry up to now. The hype around ChatGPT has raised awareness of the potential of AI. During claims processing, AI can efficiently and accurately sift through and review data so claims handlers have time to provide a better customer experience instead of processing data.”

Sprout’s CEO Roi Amir

Chan agreed. “For underwriting, for claims, it is not going to replace [people] but it is going to make it a lot more efficient,” he said.

This blog will explore the ways our AI helps claims handlers work more efficiently and focus on customers and resolving complex claims.

Read more: How insurers can select the right claims for automation

Automate repetitive tasks

When claims processing is automated, claim handlers can devote more time and attention to customers since they are freed from the time-consuming tasks of collecting and reviewing claims information, overseeing payments, and updating customer information. As a result, they are able to respond to customers’ inquiries more promptly and empathetically, with the ability to assure them that their claims will resolved efficiently.

Lower the risk of bias or error

AI-powered claims processing minimises the risk of human error or bias, ensuring a fair and just outcome for insurers and customers alike. This approach enables insurers to process large volumes of claims data at scale and high speeds, providing customers with the assurance that their claims are being handled accurately, and handlers with the assurance that outcomes are fair.

Process claims faster

People nowadays expect streamlined and straightforward services, whether they are shopping, banking – or making an insurance claim. That expectation may not be met without automated claims processing. Our AI helps insurers process claims in real time, resulting in satisfied customers and a higher Total Net Promoter Score (TNPS).

Read more: Insurance customers anticipate a far faster claims process than the one they experience. How can insurers catch up?

How Sprout.ai helps claims handlers work more effectively

Our patented technology can process claims forms and extract the meaning of a claim far faster than a human. This is particularly useful in a world where the volume of data is increasing exponentially. 

Optical character recognition (OCR) capabilities can read handwritten language at a level that surpasses human competence, in languages from Greek to Japanese. It can help eliminate loss making or incorrect decisions by automating the process and referring to thousands of data points. 

We partner with insurers, integrating data-led technology with their claim management systems and processes for a tailored, individualised approach. Our open API enables automation and digital transformation through insurers’ existing systems to ensure our AI meets insurers’ distinct needs. 

“The pilot was great fun and I learned some things along the way. The Sprout.ai team was second to none. They were fully invested and listened to our feedback to ensure it’s a success for all. I will certainly be singing their praises.”

Zurich claims handler after working with Sprout.ai

How automated policy checking AI works

  • Firstly, historical data, such as claim types, policies, and settlement decisions are analysed.
  • A library of hypotheses for coverage inclusions and exclusions based on that historical data is then built. For example, “forced entry to the car” would be included, but “car’s doors were unlocked” would be excluded depending on the policy wording.
  • At Sprout.ai, our AI then processes the claim description and context, retrieves the policy information, and identifies the relevant policy sections. Natural language processing (NLP) and Optical Character Recognition (OCR) can contextualise policy language to turn that language into actionable decision making.
  • Policy checking then compares the claim description to policy coverage and provides a recommendation on coverage and settlement amount.
  • The conclusions are returned to the claims platform and claims handler.

Sprout.ai was developed using more than 20,000 historical claims. Every new claim added to the platform brings new knowledge and experience. As with a human claims handler, this will help the AI to keep getting better at what it does. The process reduces errors, increases fairness and frees handlers from repetitive tasks so they can focus on customer service and complicated claims.

AI and automation are already transforming the insurance industry, boosting efficiency and freeing staff from spending time on low-value, repetitive work. To learn more about partnering with Sprout.ai, book a call with one of the team.

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How insurers can select the right claims for automation

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.

Be selective 

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.

Read more: How to build a business case for AI-powered claims transformation

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.

Read more: Why processing claims in under 24 hours is a game changer for insurance companies

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.

Read more: What is tNPS, and how can insurers boost it?

Greater accuracy

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. 

Speak to one of the team about how we can help you automate claims processing

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How to build a business case for AI-powered claims transformation

Claims are one of the most important customer touchpoints for insurers. Swift, fair resolutions lead to happy, loyal customers and higher tNPS. Delays, mistakes, and a lack of communication drive customers away.

The claims process includes:

The capture and validation of a claim

The checking of claim details against a policy

Determining settlement and resolution

Manual processes and outdated systems prevent each of these steps from being as efficient as possible. 

However, AI such as the automated claims processing technology we have built here at Sprout can powerfully transform and optimise claims.

Innovating these processes and systems ensures operational efficiencies are achieved for claims and the business as a whole.

When customers know claims processing will be swift, accurate and fair, they trust the insurance industry. Furthermore, claims handlers have time to focus on serving their customers with empathy, speed, and transparency.

Read more: Joanne Richardson, former Health Director at AXA, on how insurers can overcome legacy systems, unstructured data, delays and inflation

Insurance leaders are eager to find ways to become more efficient, with 95% of insurance executives saying they will accelerate their digital transformation efforts.

However, upgrading the claims process requires an upfront investment of time and resources. It is one thing to say they will upgrade, and another to actually do it.

Letting things remain as they are might be efficient in the short term, but in the long term will lead to higher costs, slower processing, and a loss of ground to competitors.

The blog will help you build a compelling business case for AI-powered claims transformation today.

What are the benefits of claims transformation?

Zurich has upgraded their claims processing with the help of Sprout.ai.

The results:

98% accuracy from over 2000 claims assessed

£75K+ leakage and additional recoveries identified

+100 TNPS from handlers, with increased consistency, confidence and clarity

Upgrading the claims process can lead to

A better customer experience

The ability to process claims faster and with greater accuracy translates into higher customer satisfaction. Here at Sprout.ai, we are proud to be able to help insurers boost tNPS and client retention rates.

When the collection and processing of claims information, policy term reviews, payment oversight, and customer information updates is automated, claims handlers are free to focus on providing excellent customer service.

Reduced costs of settling claims

With automated claims processing, handlers spend less time on each claim. Despite this, insurers can be sure that the claim data has been processed with high levels of accuracy, and without bias. These savings give insurers a competitive edge. They can be passed on to customers, used to beat inflation, or boost profits. 

Increased efficiency and capacity of claims handlers

When claims handlers need to collect and process claims information, review policy terms, oversee payments, and update customer information, they have little time to speak to customers. When insurers automate claims processes using our technology, handlers can respond quicker to customer queries, and resolve their claims faster.

Maximised value of claims data and systems

Technology enables insurers to extract data that can be leveraged to enrich and enhance decision-making processes, resulting in greater efficiency.

Reduced leakage

Personal auto insurance leakage alone comes to $29 billion each year, according to Verisk. That is driven by fraud and human error, both of which can be reduced with automation.

Average human accuracy levels in claims processing are around 80%. Our technology has an accuracy rate of over 98%. This helps reduce operational costs, minimise waste, and lowers the risk of human error-related losses. As a result, fewer claims need to be reopened. Disputes are reduced.

Does claims transformation disrupt workflows and cause lots of upheaval?

Not with the right partners, such as Sprout.

Claims transformation is about altering the current processes and systems in place in order to ensure operational efficiencies are achieved. 

Typically, the outcome of adding claims automation into the end to end claims process augments, rather than disrupts.

Read more: How Sprout.ai partnered with Zurich UK, integrating cutting edge, data-led technology with their existing systems and processes to enable end-to-end property claims automation

More data, the automation of manual activities, and the contextualisation of claims information into actionable recommendations all speed up workflows, enabling claims handlers to do more with their time.

What’s the ROI of claims transformation?

ROI is driven by reducing costs and reducing leakage. This is different from insurer to insurer, but lower costs can be driven by:

Fewer complaints

Less reprocessing of settled claims

Lower outsourcing costs

More accurate payment of claims through reduced fraud and errors

The question to ask is: What gains in efficiency, such as hours saved per claim, will this upgrade bring?

In the past, insurers wanting to upgrade the claims process faced obstacles. Regulation made it difficult for them to experiment, while limited competition gave them little encouragement to do so. 

That is no longer the case today. Real time, automated claims processing is possible. The insurers that offer it will be the ones that thrive in 2023 and beyond, whether they are legacy companies or digital challengers.

Ready to upgrade to AI-powered claims processing?
Speak to one of the team about how we can help

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What is tNPS, and how can insurers boost it?

Transactional Net Promoter Score, or tNPS, is a way for insurers (and other businesses) to measure customer satisfaction. After a customer interacts with the insurer, they are asked to provide feedback. The results are a way to better understand how to improve customer experience and, in turn, enhance retention.

Why tNPS matters

An insurer’s tNPS indicates how likely their customers are to recommend it to others, based on their experience of the taking out a policy, filing a claim, asking a question, renewing their policy, and more.

Loyalty and retention are key priorities for insurance companies, which operate in a traditionally high-churn market of tight margins. Measuring and understanding customer experience help insurers understand which customer touch points are working, and which need improvement.

How is tNPS calculated?

Customers are asked the question: “How likely are you to recommend the insurer to a friend or colleague?” 

They can answer based on a scale of zero to 10. The score reflects their overall satisfaction with their experience and their feelings towards the insurer.

To calculate the overall score, subtract the percentage of detractors from the percentage of promoters.

What is a good tNPS score? 

In the insurance industry, a score of 20 or higher is considered good.

Which customer touchpoints have the greatest impact on tNPS?

After a customer purchases an insurance policy, the next ‘touchpoint’ is typically filing a claim. This moment, up until the claim in resolved, has a significant impact on the overall customer experience. 

Our recent research into customer expectations of the claims process shows a major disparity between customer expectations and the reality of how long insurance claims currently take to process. One in five (21%) insurance customers expect claims to be resolved within hours. However, 43% of customers responding to the survey waited over two weeks for a claim to be resolved, across multiple insurance lines.

Read the full report.

How can tNPS be improved?

A low tNPS tends to be caused by one or two sticking points that are driving customers away. The most common causes of a low score are expensive premiums, lack of claim acceptance, poor communication and slow claims processing.

By honing in on the issue causing complaints, it is possible to quickly boost tNPS.

How automation boosts tNPS

Automation can help resolve many of the issues that lower tNPS.

Reduce costs

Automation can reduce the cost of a claims journey by as much as 30%, according to McKinsey. With automated claims processing, handlers spend less time on each claim. Despite this, insurers can be sure that the claim data has been processed with high levels of accuracy, and without bias, which reduces the number of complaints and challenges. These savings can be invested in lowering premiums.

Fairer and more accurate claims processing

When claims processing is automated, claims teams can process large volumes of data at scale, at speed, and with fewer errors or biases than a human. Insurers and customers can be assured that the fairest possible outcome has been achieved.

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.

Faster claims processing

Customers today are used to speed and simplicity from their service providers, whether they are hiring a car to contacting their bank. They expect the same from their insurers, but are unlikely to receive it – unless the insurer is using automated claims processing. 

Faster, more accurate claims lead to higher customer satisfaction. Our technology is proven to directly improve insurers’ tNPS and client retention. 

A number of leading 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.

Sprout.ai partnered with Zurich UK, integrating cutting edge, data-led technology with their existing systems and processes to enable end-to-end property claims automation. The partnership has boosted TNPS by +100, with increased consistency, confidence and clarity.

Read more.

Better communication and customer service

Our technology enables claims handlers to focus on customer service, rather than the lengthy processes of collecting and processing claims information, reviewing policy terms, overseeing payments, and updating customer information.

How Sprout.ai works

Natural language processing (NLP) and patented optical character recognition (OCR) technology can rapidly extract all relevant information from any type of document, from PDFs, to images to freeform notes – even if it is in handwritten Japanese.

Relevant data is contextualised immediately, then validated against the policy contracts and schedules to check if the claim is covered under the customer’s specific policy. 

Limits, excesses, inclusions and exclusions are automatically calculated.

Our technology also helps check for fraud, reduce waste or abuse, and identify outliers. 

Speak to one of the team about how we can help you boost tNPS by automating claims processing

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How AI-powered claims processing helps insurers beat inflation

Earlier this month, the CEO of a leading global insurer said that the impact of inflation on the company’s underwriting margins is now on the decline. However, inflation remains a threat. The soaring cost of motor claims led to the insurer missing analyst expectations in its full-year results.

It is not the only insurer to be affected by inflated motor costs. In January, the CEO of a UK-based motor insurer resigned after repeated profit warnings that were triggered by the escalating cost of claims. Another insurer attributed an underwriting loss to inflation and weather-related accidents, which lead to more motor insurance claims. A US-based insurer reported a net loss of $310 million in the fourth quarter last year as a result of  increased claims costs, even though it had increased motor insurance prices. 

Read more: Joanne Richardson, former Health Director at AXA, on how insurers can overcome legacy systems, unstructured data, delays and inflation

Motor insurance is just one area where inflation is rampant. Insurers operating in many categories, from home to health to motor and more, are facing higher costs. Russia’s invasion of Ukraine and Covid-related lockdowns in China have led to supply chain issues and increased inflationary pressures. Extreme weather, rising wages, higher legal and medical costs have further pushed up insurers’ costs.

It comes as no surprise that inflation is an “immediate focus for insurers, with 79% of global respondents anticipating it to be a concern in the next year,” according to a recent Goldman Sachs Insurance Asset Management survey.

Efficiency is key

In this climate, insurers need to operate at maximum efficiency.  Intelligent claims automation technology like ours is a clear way to do this. Automation can reduce the cost of a claims journey by as much as 30%, according to McKinsey.

We enable insurers to reduce the average time it takes to settle a claim from 30 days to less than 24 hours, while boosting accuracy. In many cases, we enable instant settlement. As a result, claims handlers can process more claims and have more time to focus on serving their customers with empathy, speed, and transparency.

Read more: Why processing claims in under 24 hours is a game changer for insurance companies

Not all insurance lines are the same. However, by adapting certain features and data sources, we have developed a solution that’s configurable and inflation-beating for every insurance line, from health and life insurance to motor and property. Our technology is designed to extract all necessary information from all types of claim documents, from handwritten doctor’s notes to call transcripts and prescriptions. To ensure accuracy, external data points such as treatment codes, provider network policies, or medication information are used to validate the claim, which is then cross-checked against policy documents. Our deep learning AI algorithms then predict the best next step for the claim and provide clear justifications. Limits, excesses, inclusions, and exclusions are automatically calculated.

Sprout.ai leads to

Reduced costs

With automated claims processing, handlers spend less time on each claim. Despite this, insurers can be sure that the claim data has been processed with high levels of accuracy, and without bias. These savings give insurers a competitive edge. They can be passed on to customers, used to beat inflation, or boost profits. 

Higher accuracy

Average human accuracy levels in claims processing hover at around 80%. Our technology has an accuracy rate of over 98%. This helps reduce operational costs, minimise waste, and lowers the risk of human error-related losses. As a result, fewer claims need to be reopened. Disputes are reduced.

Increased customer satisfaction and retention

Our ability to process claims faster and with greater accuracy translates into higher customer satisfaction. We take pride in our role in improving insurers’ Transactional Net Promoter Scores and client retention rates. We handle the collection and processing of claims information, policy term reviews, payment oversight, and customer information updates. Claims handlers are free to focus on providing excellent customer service.

Data-driven decision-making

Our patented technology enables insurers to extract data that can be leveraged to enrich and enhance decision-making processes, resulting in greater efficiency.

Read more: 6 ways insurers benefit from automating claims processing

Case Study: How Zurich UK boosts efficiency with Sprout.ai

We partnered with Zurich UK, integrating our cutting edge, data-led technology into their existing systems and processes to enable end-to-end property claims automation. Download the full report.

Results

Zurich UK can settle 45% of customer claims in real time, whether they are made by phone or online, with the help of Sprout.ai and other key initiatives.

The number of claims settled within five days of initial submission by rose by 10%, thanks to Sprout.ai and other key interventions,

For some claims, policy documents can be reviewed in seconds. Historically, it could take claims handlers up to 30 minutes per claim.

Claims handlers are no longer constrained by the many documents associated with each claim, leaving them with more time to spend with customers, at times when human touch and empathy can make a real difference. 

Value from claims data and systems is maximised. Sprout.ai delivers data insights that facilitate agility, improve retention rate and control costs.

Accuracy is improved. 

Sprout.ai ’s products have been built to ensure that the rationale behind the AI’s decision-making process is clear and simple to understand. The decision-making process is more transparent, and handlers can explain decisions more easily.

To learn more about how Sprout.ai can help you beat inflation, book a call.

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Why processing claims in under 24 hours is a game changer for insurance companies

More UK consumers are shopping around for insurance this year than in previous years, the CEO of price comparison website Moneysupermarket Peter Duffy said last week. Switching has decreased since UK regulators banned “loyalty penalties”, higher fees for existing customers, but higher living costs have led to the return of customers looking around for cheaper policies.

“We see premium inflation continuing in 2023 and we see consumers continuing to want to make sure they get the best value product,” he said. 

A customer’s impression of their insurer is determined by a number of factors, but claims turnaround time is to be among the most important. A rapid resolution creates a positive impression, builds loyalty and increases the chance of customer retention. A slow resolution and a lack of communication will encourage the customer to look for another policy.

Accenture warns that unsatisfactory claims experiences could put as much as $170 billion in renewal premiums at risk worldwide in the next five years, while McKinsey predicts that claims processing will hold the highest significance in the insurance industry by the year 2030.

Claims processing can be faster

Until recently, insurers did not have access to technology that allowed them to process claims quickly. Legacy software is unable to process unstructured data, so claims handlers had no choice but to spend hours sifting through forms, handwritten documents, PDFs, and images to extract the relevant information. Then they would have to check for coverage and initiate payment. 

This was acceptable to customers in the past, but today consumers are used to instant purchases, same day deliveries and always-available customer service. A wait of 30 days or longer for a resolution is incongruous with the world they live in. However, the vast amounts of data now available have made manual claims processing more laborious than ever, making resolutions even slower and leaving claim handlers with insufficient time to focus on customer service.

The results for insurers are low Transactional Net Promoter Scores and high customer churn, often to digital challenger brands.

However, technology like ours is enabling insurers to process claims in under a day, and often in real time. We’re empowering intelligent claims decisions by using AI and machine learning to interpret data and remove nuance. The administrative tasks that would take a handler hours or even days can be done in minutes, leaving the handler free to make decisions and support customers.

Read more: Zurich can now resolve property claims within 24 hours using Sprout.ai

How it works

Our natural language processing (NLP) and patented optical character recognition (OCR) technology is optimised for claims. It can rapidly extract all relevant information from any type of document, from PDFs, to images to freeform notes – even if it is in handwritten Japanese.

Natural language processing algorithms immediately contextualise relevant data, then validate it against the policy contracts and schedules to check if the claim is covered under the customer’s specific policy. Limits, excesses, inclusions and exclusions are automatically calculated. Our technology helps validate claims, check for fraud, reduce waste or abuse, and identify outliers. 

The benefits of processing 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.

Greater accuracy

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 can be used to enhance 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. 

Speak to one of the team about how we can help you process claims in real time

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6 ways insurers benefit from automating claims processing

Claims are a vital moment for insurers. They are likely to be the first time a customer comes into contact with the insurer since they bought their policy. They are the moment the customers discovers whether that purchase was worth. 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.

However, processing claims has traditionally been a slow, manual task. As legacy software struggles to process unstructured data, 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. It is unsurprising claims handlers have little time to focus on customer service.

Not only is this process costly and inefficient for the insurers, but customers are left waiting weeks for responses, decisions and payments. This delay couldn’t come at a worse time for them. Often, they will have just gone through a stressful experience that led to them making the claim. Adding the stress of waiting leads to dissatisfied, frustrated customers, who are driven to look for an alternative insurer.

Insurers have traditionally faced obstacles in upgrading the claims process.  Regulation has made it difficult for them to experiment, while limited competition has given them little encouragement to do so. Today, that is no longer the case. Real time, automated claims processing is possible. The insurers that offer it will be the most appealing option to customers, whether they are legacy companies or digital challengers.

Read more: The insurance industry in 2023 and beyond

At Sprout.ai, we have enabled 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.

We’ll explore the benefits of automating claims processing in greater detail below.

Faster resolutions

When customers make a claim, they want to know whether the claim has been successful, and then receive their payment as quickly as possible. Waiting weeks or even months is an incredibly frustrating or difficult experience. 

When processing is automated with Sprout.ai, claims can be settled in hours, or even in real time. Our AI can process data far faster than a human can, so handlers no longer have to waste time on clerical tasks. One leading insurer is now settling 45% of customer claims by phone and online in real time using our software. 

Read more: Zurich can now resolve property claims within 24 hours using Sprout.ai

Claim handlers can focus on customers

When claims handlers need to collect and process claims information, review policy terms, oversee payments, and update customer information, they have little time to speak to customers. When insurers automate claims processes using our technology, handlers can respond quicker to customer queries, and resolve their claims faster.

More accurate, better informed decisions

When claims processing is automated, claims teams can process large volumes of data at scale, at speed, and with fewer errors or biases than a human. Insurers and customers can be assured that the fairest possible outcome has been achieved.

Happier customers and higher tNPS

Customers are used to efficiency and simplicity from many service providers, from shopping to banking. They expect the same from their insurers, but are unlikely to receive it unless the insurer is using automated claims processing. 

Read more: Customers’ expectations vs reality

Faster claims processing leads to happier customers and higher TNPS. Not only do customers receive resolutions faster, but  they are more easily able to speak to claims handlers, and the outcomes are more accurate.

Less leakage

Higher customer satisfaction, driven by the better customer service and faster processing times will lead to increased customer retention to other major insurers and digital incumbents.

Lower costs

Automation can reduce the cost of a claims journey by as much as 30%, according to Mckinsey. With automated claims processing, handlers spend less time on each claim. Despite this, insurers can be sure that the claim data has been processed with high levels of accuracy, and without bias.

These savings give insurers a competitive edge. They can be passed on to customers, used to beat inflation, or boost profits. 

Speak to one of the team about how we can help you automate claims processing

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Joanne Richardson, former Health Director at AXA, on how insurers can overcome legacy systems, unstructured data, delays and inflation

Joanne Richardson spent over 20 years working in health insurance across multiple countries for AXA, including Mexico, France and the UK. She spent five years as a Health Director in the Group head office in Paris, where she developed group strategic initiatives such as Care Coordination. She then worked in Group Risk Management, leading in-depth reviews of the major AXA health entities, helping to ensure long term profitable growth through International best practice.

She spoke to us about the key challenges facing insurers today, and how Sprout.ai helps solve them.

Sprout.ai: What relationship do health insurers want to have with customers today?

Joanne Richardson: Health insurers today have a clear desire to be more customer-centric. They aim to help people be healthy and stay healthy.

They want seamless quick claims processing, and then they want to be able to concentrate on adding additional value services to customers. That means giving them access to the latest medical innovations, providing them with support to manage chronic illnesses, such as apps for diabetes management, understanding their needs and having the time to provide dedicated support for complex cases. 

This enables customers to live healthy lives and to return to health as quickly as possible.

Sprout.ai: And what relationship do health insurers have with medical providers?

JR: Many insurance health insurers have a wide network of medical providers. These providers want the right money to be promptly paid for the work that they’ve done. 

Insurers want to be able issue timely, accurate payments. They want to establish a high quality medical network at an optimal price point that is more a partnership than a transaction. 

Shareholders need to be considered here too. Health insurance is a small margin product, so profitable growth has to be done through efficiency, innovation, and a good reputation in the market. 

Sprout.ai: What challenges are health insurers facing today?

  1. Legacy Systems

JR: As mentioned, providers want to be paid accurately and quickly. Insurers want claims to happen seamlessly and without problems. However, because of the way that many health insurance products are designed to fit state provision, they are managed on old bespoke systems. These are slow to change. They’re incredibly expensive to replace, and have an awful lot of manual intervention. 

Health claims are as prone to fraud, waste, abuse as all insurance claims. It’s estimated that 5-6% of all global claims payments are paid inaccurately. 

Furthermore, it’s a slow process. It’s often not automated, and particularly complex claims take a long time to get through. 

How does Sprout.ai help solve the problem of legacy systems?

JR: One of the things that attracted us to Sprout.ai in the first place was the fact that its claims system sits on top of your old bespoke systems, so you don’t need to replace them. As anybody who’s ever tried to replace the claim system in health will know, this is expensive, takes a long time, and often does not result in success. 

  1. Unstructured data

JR: We then go forward to look at data that’s linked to claims. Old claims systems were written to capture the minimum amount of data required in order to pay claims, because data capture takes time and multiple attempts. 

Lots of data is provided during the health claims process, but an awful lot of it is not structured. When it is on claims forms for medical information, it’s often not captured. This means that there isn’t enough structured data within the systems to be able to understand customers’ needs, to analyse fraud, waste and abuse, and assess quality of care.

How does Sprout.ai help solve the problem of unstructured data?

JR: One of the things we liked about Sprout.ai was its ability to capture much more data, capture much richer data, and then format it so it is structured. This then allows analysis into needs, leakage, and care quality to happen. And as Sprout.ai sits outside of the legacy systems, you don’t need to adjust all your data structures.

  1. Delays and inflation 

JR: First, we’ve still got the backlog of treatments waiting to happen because of COVID within state systems, and also to an extent within private systems. This is an opportunity for health insurers. People are turning to private insurance as they realise how long they may have to wait to get treatment within the state. However, those treatments are also delayed in the private system. Delaying treatment often means that the final interventions are more complex, and consequently more expensive. 

Second, there’s the challenge of inflation.  We can see what’s happening with general inflation with the war in Ukraine, as well as the supply chain problems we have post COVID. We understand from historical analysis that medical inflation tends to be higher than general inflation. It isn’t clear yet exactly what the impact is going to be, but health insurers can’t wait a year to find out what the inflation results in. They have to price for it now. 

That means that, unless they can find ways of reducing costs in the short term, they are going to end up putting their prices up to a point where for some people health insurance will become unaffordable. And let’s face it, the people who stop paying health insurance are not the ones having treatment. They’re the ones who aren’t. That means that the subsidy that comes from those people to the people who are claiming is reduced. Therefore, prices go up again. It’s a vicious circle. 

So, it is important that insurers can react to both the opportunities of new health insurance customers, and also price health insurance in a way that they can retain their existing customer base. 

Sprout.ai: How does Sprout.ai help solve the problems of delays and inflation?

Our AI powered technology delivers fast and accurate claims decisions, enabling you to better serve your customers.

It extracts all of the data in the claims documents from providers, customers, doctors. Then, the data is structured and put into the insurer’s system. Natural language processing (NLP) interprets the documents and unstructured data, then triages the claim, and checks for fraud, anomalies, and coverage. Then, using machine learning, our technology checks the claim against historical claims and recommends the next best step. The claim can either be settled right away, or, if it’s more complex, passed on to a claim handler.

Some answers have been lightly edited for clarity.

Watch the full Webinar here.

To learn more about how Sprout.ai can boost efficiency and enhance customer experience, book a call today.

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The insurance industry in 2023 and beyond

The global insurance market faces many challenges this year, from ever higher customer expectations, to soaring inflation, climate change, cyber security risks and pandemics. Few insurance lines will be unaffected by these issues. Insurers operating in every jurisdiction and across every line will need to think about how to deal with them.

Here is how Sprout.ai envisions the year ahead playing out, as well as some thoughts on what might happen further ahead.

Inflation will drive up insurance premiums

Inflation is significantly impacting the insurance industry as the rising cost of goods, repairs, and services drives up claims payouts for insurers. As a result, premiums may also increase as insurers look to offset their losses. Traditional insurers may have an advantage in this market as they have a more established brand and deeper coffers, which customers may find more reassuring during uncertain times.

However, traditional insurers also have higher operational costs compared to technology-first insurance providers. To remain competitive, traditional insurers will need to optimise their operations and invest in technology that allows them to provide better service at a lower cost. The insurers that can do this quickly and efficiently will come out on top.

The insurance industry will also need to meet cost-of-living pressures

Despite the higher costs caused by inflation, insurers will need to adapt by offering flexible and competitively priced products to their customers as cost-of-living pressures continue to bite. To stay competitive, insurers should invest in product innovation and offer flexibility and choice. In 2023, customers will look for lower cost policies that are tailored to their specific needs.

To help prevent or mitigate potential losses or risks, many insurance companies will provide additional services to their customers. These will reduce exposure, reduce overall claims volumes, and improve profitability for the company. For example, offering health insurance customers periodic health checks or gym memberships can improve customers’ health and well-being, which reduces the likelihood of making a claim, while generating additional revenues if the right partnerships are created. This can be seen as a win-win situation for both the insurer and the customer.

Insurtech startups will face funding challenges

The decline in tech funding in 2022 has affected the insurtech sector, with companies experiencing a drop in later-stage growth funding and reductions in valuations. Investors are becoming more cautious and focusing on growth metrics, which poses a risk for insurtech startups that rely on funding to fuel their growth. However, this presents opportunities for well-financed companies with deep pockets.

 Traditional insurers may be able to regain market share or drive consolidation in the market as they partner with new and traditional insurance companies. The future of the industry is uncertain and the funding situation may change, but for now, venture capital and private equity funds still have money to invest and insurtech is still considered a “hot” area.

Artificial intelligence and the Internet of Things will continue to disrupt

Artificial intelligence (AI) is overhauling the insurance industry by automating complex tasks that were once difficult to perform with traditional software , as well as the simpler, repetitive ones. With the use of deep learning and other AI techniques, many decision-making processes in insurance can be automated or assisted by software. For example, identifying the circumstances that led to a customer’s insurance claim and cross-referencing it with the terms of the current policy is a complex task that can now be automated. More and more insurers are leveraging this type of technology.

In 2023 and beyond, insurers will begin to use the Internet of Things (IoT) and wearable devices to track customers’ behaviour to identify and mitigate the risk of claiming on insurance. This technology can be helpful in tracking patterns and behaviours, or monitoring health and activity levels for health insurance customers. IoT and wearables can provide insurers with valuable data that can help them better understand the risks their customers face, and allow them to offer more tailored insurance products.

Customer-centric approaches to claims will become the norm

Today, the majority of insurers structure their operations by insurance lines. For customers, this is highly inefficient. One customer holds multiple policies for different insurance lines. It becomes even more inefficient and problematic if the customer needs to claim on more than one type of insurance. 

Here’s what that problem looks like:

Customer ‘A’ owns a house where a fire breaks out. The fire destroys the entire contents of the home and causes the customer severe respiratory issues. Customer ‘A’ will need to claim on up to three insurance policies: buildings, contents and health insurance. This are likely to be held with different companies.

Customer are often emotionally, financially, or physically vulnerable when filing an insurance claim. Improving efficiencies in the claims process will help reduce that stress and enhance the overall customer experience. 

Flexible workforces and embedded technology will enable resilience to global crises

The Covid-19 pandemic had a far-reaching impact on health insurers. Claims volumes increased by 40-60% and have not fallen since. This dramatic increase has been driven not just by Covid infections, but by the knock-on impact of the pandemic on other long-term health conditions. Insurance companies have had to retrain claims handlers from other areas such as motor insurance to manage health claims. This has been a long and expensive process as it can take up to 9 months to train claims handlers.

This highlighted the challenge of dealing with a crisis and a spike in claims using legacy processes and technology. In the years ahead, global warming will present enormous challenges for insurers in the form of wildfires, rising sea levels, and floods. Insurers will prepare for these events by automating much of the claims process and increasing the flexibility and elasticity of their workforce.

To learn more about how Sprout.ai can boost efficiency and enhance customer experience, book a call today.

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Customers’ expectations vs reality

Insurance customers anticipate a far faster claims process than the one they experience. How can insurers catch up?

More than 1 in 5 (21%) insurance customers expect claims to be resolved within hours. A total of 100% of 18 to 24 year olds expect a resolution on an insurance claim within one week, according to our recent research into customer expectations of the claims process.

Download the report: Responding to rising customer expectations in insurance

We surveyed 1,000 consumers about their attitudes towards insurance claims. Of that number, 99% were either solely responsible for choosing and purchasing insurance products, or made the decisions with a member of their household. 

They told us:

  • 43% of customers across multiple insurance lines waited over two weeks for a claim to be resolved
  • 62% of claimants with a “good” or “very good” customer experience said that they stayed with their existing insurance provider
  • 31% of claimants with a “good” or “very good” customer experience said that they would use the same provider at some point in the future
  • 19% of those with a “bad” or “very bad” experience said they are still a customer of their existing insurance provider
  • 89% with a “bad” or “very bad” experience said they would not purchase a policy from the same insurer in the future

Customer service matters most during claims

In today’s highly competitive insurance markets, margins are tight. It is easy for customers to switch between different providers. Delivering excellent customer experience is, therefore, vital for customer retention.

After a customer purchases an insurance policy, the next ‘touchpoint’ is typically when a claim is filed. The customer is likely to be vulnerable or distressed. The insurer needs to deliver and prove that the customer’s purchase was a wise investment.

The time it takes for a claim to be processed and the ease of speaking to a claims handler have a significant impact on the overall customer experience. This can boost customer experience, and in turn, the insurer’s Transactional Net Promoter Scores (TNPS).

How Sprout.ai helps insurers meet their customers’ expectations

Customers want: Quick resolutions

Sprout.ai empowers insurers to settle many claims in real time, and speed up the time it takes to process more complex claims.

Customers want: To be able to speak to a handler

Sprout.ai performs many of the repetitive data entry and checking tasks that take up claim handlers’ time, freeing them up to speak to customers.

Customers want: Confidence that their claim has been processed fairly

Sprout.ai is free from bias and 97% accurate. 

How it works

Data extraction

Documents submitted for a claim can include PDFs, handwritten reports, images and freeform notes, as well as structured text and digital content. Manually processing these documents is time consuming and open to inaccuracy, fraud and wastage. 

Our NLP and patented OCR technology can extract all relevant information from any type of document submitted as part of the claims process. As a result, it can be used to automate and provide insights. 

Data enrichment 

We refine and improve the data we have captured by up to 300% by attaching external data points such as fraud checks, replacement prices, claims history and much more. This helps us validate the claim, checking for fraud, reduce waste and abuse and identify outliers. 

Policy checking

Our technology enables fast, accurate and superior policy checking and claim validation. It takes all relevant information and validates it against the policy documents to check whether the claim is covered under the customer’s specific policy. 

Our patented NLP solution can automatically check for coverage a moment a claim is made due to its deep understanding of claims and insurance related language, including synonyms for the same word (e.g. waste, garbage, rubbish). 

As a result, claims can be processed in real time, or far faster than before, freeing up handlers to focus on customer service.

To learn more about how Sprout.ai can help you process claims in real time, book a call with one of our claims experts