Optimizing Insurance Claims Processing with Generative AI Technology
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As a global insurance brand, MetLife knew it was time to make a change to its claims processing systems. With fraud more prevalent than ever, it needed a workflow that would help detect fraudulent cases accurately and quickly. Insurance claims processing is a task that rests heavily on the shoulders of being efficient, accurate, and decisive – something that may be challenging when no two claims are built alike.
In this industry, everyday challenges are considered to come with the territory. Data management, fraud, and error-prone work are all too familiar to those in the insurance claims processing industry.?
There has to be a better way, and generative AI might be the key.?
A report by Deloitte uncovered that 38% of insurance CEOs are already taking the first steps on the journey of generative AI initiatives. What’s more, 34% of companies surveyed indicated that they’re blending AI into their existing day-to-day workflows.?
The fact is that generative AI has the potential to revolutionize the insurance claims industry. It improves decision-making accuracy and equip employees with more actionable data. Let’s take a deeper look at generative ai services, and why it might just be the next best thing for your daily processes.
Understanding Generative AI
Solving issues with underwriting, claims processing, and fraud detection using generative AI sounds great. But what is generative AI in the first place?
Generative artificial intelligence (AI) is a term used to describe a specific use case of AI. This use case is built around algorithms that create brand-new content. Programs like ChatGPT and Dall-E are examples of generative AI.?
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From personal to professional, there are hundreds of uses for generative AI.?
One example is in the world of healthcare. The researchers at Mayo Clinic developed a robust, deep-learning algorithm that forecasts the likelihood of surgical complications. Through generative AI, patients receive customized treatment recommendations based on the presented risk.?
Similarly, Best Buy has harnessed generative AI to troubleshoot product issues, manage subscriptions, reschedule order deliveries, and much more. Customer service associates at brick-and-mortar locations and online can touch base with gen-AI tools to gain a leg up on serving shoppers.?
Generative AI isn’t just customer facing, however – Goldman Sachs has spearheaded more than one generative AI project within its internal business operations. However, ‘internal’ is exactly what they are. AI is now handling business intelligence tasks and streamlining workflows for employees at this Fortune 100 company.
Microsoft, meanwhile, adopted large language models and integrated them into its Bing search engine and directly into Windows 11 through its Copilot application. The latter allows users to adjust their settings, perform web searches, and generally speed up the operating process.
The Role of Generative AI in Insurance Claims Processing
In 2022, the global market size of generative AI in the insurance sector was estimated to be $462.11 million. By 2032, that estimate rockets to $8,099.97 million. With such a large market size, what role does it play??
Document Analysis and Data Extraction
Some challenges associated with data extraction within the insurance industry include its sheer volume, not to mention the variety presented in that data. While diverse data is crucial for insurance claims processing, it can increase the time needed to sort and understand that information while being difficult to scale.?
Generative AI implementation services can provide a platform that eases the burdens of the extraction process. Through machine learning, entity recognition, data classification, and general extraction are made much easier for the user. When fed information about policy details, accident reports, and medical records, a well-trained AI can sort through to find the critical data, saving you immense time.?
It’s not just time-saving, however. While claims processors are great at what they do, there is always a human margin for error. A study by West Monroe noted that 66% of respondents found data quality and accuracy to be one of their biggest challenges. When you automate your insurance claims technology through a generative AI service, you’ll notice a rise in efficiency and accuracy.?
Fraud Detection
Anyone who has worked in insurance claims processing for a while has likely seen it all when it comes to fraud. Opportunistic individuals and organized networks alike will do what it takes to try to ‘beat the system.’?
You know what to look for, you know the red flags, but that doesn’t stop these cases from rolling in every day. Forbes even estimates that a whopping 20% of insurance claims are fraudulent. It states that insurance fraud is the second most costly white-collar crime in the US, following right behind tax evasion.?
Rest easy: generative AI services can help with that, too.?
When a generative AI platform is trained on previous claims and cases, it earns the ability to identify patterns and anomalies in claims data. Using predictive analysis, data collection, and human review for final action, generative AI can reduce fraudulent claims. Reducing fraudulent claims will, in turn, have a positive ripple effect: costs are reduced, customers are happy, and proper persecution can be achieved faster.
Claims Assessment and Estimation:
Claims assessment and estimation is the bread and butter of insurance claims processing. Evaluating, inspecting, and assessing the situation and breaking it down into parts to discover the validity and outcome of a claim is a pivotal part of this entire industry.?
With generative AI services, though, that process can be streamlined, sped up, and even more accurate. A gen-AI platform can scan documents, look over images understand what is being presented there, and sift through mountainous amounts of relevant data. Automating the processes of damage assessment and loss estimation is one of the best ways that generative AI leads to more efficient claim processing and pinpoint accuracy.?
Customer Interaction?
According to a report by McKinsey, modern customers are anticipating tailored, personalized advice that is one of a kind to their specific situation. We’ve talked before about the role AI can play in customer service via chatbots and virtual assistants. It’s already used at banks, retail, and the healthcare sector. Insurance is just one of many industries that can benefit from the 24-hour, personalized boon of AI-powered chatbots.?
Their biggest role in insurance claims processing is receiving initial claim inquiries. When a user lands on the site, a chatbot using generative AI to craft responses will take in the first point-of-contact details about the claim.?
The ultimate result is improved satisfaction and drastically reduced response times, which means you can get to your client’s claim with information already in hand provided by the AI.?
Benefits of Generative AI in Claims Processing
Increased Efficiency and Productivity
A human being sorting through hundreds of data points, processing and making sense of them all, might take hours — or even days. Generative AI services, however, manage that bulk of information in a matter of minutes, if not instantly.
For example, a car insurance company might process a claim using automated data entry and priority organization through generative AI. The AI can collect data from accident reports and repair estimates in record time. It can also look over all the current claims and sort them by severity and urgency.?
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Improved Accuracy and Reduced Errors
Human error, from typos to honest mistakes, is, well, human. AI, however, is not human and, therefore, has a much lower margin of error. Language processing and powerful machine learning algorithms work together to automate the tedious processes of working with claims. From there, they churn out accurate, understandable, actionable results.?
Enhanced customer experience
It’s no wonder that generative AI services tend to enhance customer experiences through reduced errors and quicker processing times. Through AI, non-value-added human interventions are reduced, and support is made even more quick and efficient. This leads to upped retention rates , which is ideal for the business as well.?
Cost Reduction and Profitability?
Not only will faster processing times and enhanced customer experiences increase profits and trim costs, but generative AI investments can also lead to additional revenue in other areas within an insurance company.?
With gen-AI, you might be able to identify growth opportunities. You may also see chances to create personalized insurance products, or even expand your company’s market reach when you analyze customer behavior and processes. An insurance company with innovative product development and broadened demographics will always remain at the top.?
Faster Claim Settlement Times
Undoubtedly, generative AI services can quickly summarize property damage reports and legal documents in half the time that the human eye. When you’re using an AI to get the paperwork out of the way, you’re left to add the human element to decision-making, allowing you plenty of time to make an informed decision.?
Data-driven Insights For Process Improvement
With the insights provided by generative AI services, you’ll be allowed to take a step back and look at your processes as a whole. The data and analytics provided by AI integration may prove invaluable to decision-making and product improvement.
Challenges and Considerations of Generative AI Implementation Services?
While generative AI implementation services offer many benefits, there are a few risks to consider.?
Data privacy and security concerns
Generative AI’s language models and machine learning algorithms are usually built on real-world examples and tend to learn even more as they are used and developed. As with any human-made product for use in a digital space, there is the risk of data breaches and privacy errors.?
Privacy is one of the biggest concerns that organizations have about generative AI.?
There is also the additional concern of malicious prompt engineering. While it’s rare, using specific prompts may give malicious actors access sensitive data.?
Most organizations that use generative AI understand that they must let their customers know how their data will be used. 98% of organizations contacted by Cisco stated that a platform’s privacy certifications are crucial to their purchasing decisions.?
Model Bias and Fairness?
Model bias refers to the presence of unfair or even prejudiced-generated content. For example, in insurance, a machine learning model that has been trained on information that contains?
Model bias may unwittingly make assessments that enforce prejudices or social inequalities. For example, an insurance claim might give two clients in the same situation a different outcome based on each person’s socioeconomic background.?
Human-In-The-Loop Approach
The goal with generative AI services is that there’s always a ‘human-in-the-loop'. This technology is meant to work alongside people, not against or in place of us. However, this can come with a drawback. Excessive human oversight might unintentionally worsen occasional errors in judgment created by an AI rather than combat them.?
Integration With Existing systems
Many insurance companies have been in the game for a long time. This means most work with legacy systems and frameworks that are already interwoven into the company's fabric. While a generative AI platform is highly beneficial, you might encounter occasional issues, such as performance bottlenecks and increased workflow complexity.?
Regulatory Compliance
All of the above, especially model bias’ potential to create unfair outcomes, can bring the potential risk of regulatory compliance to insurance companies using generative AI. Even without model bias, a poorly trained AI might return results that it thinks are good but are, in fact, outside of company or legal policy.?
Case Studies and Best Practices
In a recent report, Sprout.ai indicates that 59% of insurance organizations have already adopted generative AI services. Here are a few ways that they’ve made them work.?
Successful Implementations of Generative AI in Insurance
MetLife?
As discussed earlier, MetLife needed to upgrade its fraud detection accuracy. The impact was immediately apparent when MetLife decided to implement generative AI into its call centers . It was there to coach agents and improve customer interactions, which led to positive changes across the board, not just how fraud was caught. With the use of generative AI services, MetLife saw:?
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Helvetica?
Helvetica, a Swiss insurance company, tested their new digital assistant, Clara. The ChatGPT-powered bot launched in early 2023, providing customers access to the answers they’re looking for on Helvetica’s website. However, by this time, Helvetica had already used AI for several years in its claims processing and fraud identification departments.?
Anthem?
When Anthem needed a synthetic data platform , they took it to the top by partnering with Google Cloud. From there, the brand generated 1.5–2 petabytes of information covering medical histories and healthcare claims to refine its algorithms to a tee.?
Best Practices for Adopting Generative AI in Insurance?
There are a few best practices to remember when contacting generative AI implementation services and laying the groundwork for this digital transformation.?
Generative AI Services are the Future of Insurance Claims Processing
From faster claims processing to happier customers, there are tons of different ways that AI is beneficial to the insurance industry. Using it for data collection saves time, and it’s excellent at fraud detection once it’s trained well.?
Generative AI isn’t exactly new, but it’s still relatively fresh on the scene in a workable way. Decision-makers in insurance companies should act now with the knowledge that this technology will only improve. Staying on the pulse will keep your company ahead of the competition.?
Insurers who want to hop aboard the train of this innovative, game-changing tech can contact Ziffity to learn more about our generative AI implementation services, where we’ll help find the best product to suit your insurance claims needs.?
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