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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.