Using AI to Energize Claims Processing for Insurance TPAs
By Marc Rothchild, Senior Vice President – Head of Claims, Xceedance
The global insurance industry reached $8.3 trillion in 2025, a scale rivalling the GDP of major economies. This growth is fueled by digital transformation, rising demand for cyber insurance, population health management, and climate risk coverage. As risks diversify and customer expectations rise, third-party administrators (TPAs) face unprecedented workloads, managing more claims across both the life and non-life segments than ever before.
To keep pace, the industry is embracing AI and process automation, reshaping claims operations from manual, error-prone tasks to intelligent workflows. The forecast signals a new era defined by insurtech collaborations, personalization through AI, blockchain-driven efficiency, customer-centric digital experiences, ecosystem partnerships, and regulatory technology.
Role of AI in Claims Processing
Artificial intelligence (AI) has moved from being a promising technology to a critical enabler in insurance claims management. As claim volumes surge and customer expectations rise, AI and automation are already nestled in how insurers and third-party administrators (TPAs) operate.
A recent industry analysis shows that 84% of insurers are now actively deploying AI in claims processing, and the results are transformative: claims processing times have dropped by 59%, and fraud detection accuracy has improved by 78%, saving billions globally. Customer satisfaction has surged by 63%, thanks to faster resolutions and personalized experiences.
These gains go beyond automation. AI enables predictive analytics, real-time fraud detection, and intelligent triage, helping TPAs manage complex workflows with precision. From integrating unstructured data to automating repetitive tasks, AI-driven systems are replacing manual processes that once consumed hours of adjuster time and improving compliance.
Tangible benefits of AI usage in claims processing
The impact of using artificial intelligence in claims processing is slowly gaining ground. Right from integrating and structuring historical data to improving fraud detection and prevention, recording processing time and cost, and enhancing accuracy and consistency in claims assessment are some of the key benefits. There is also the strategic impact of having historical data for better claims management and its use alongside predictive analytics in processing to get a better hold on forecasting. Let’s delve into some details:
● Integration and structuring of data – The TPAs were hard-pressed to integrate data collected from multiple sources such as email, WhatsApp, and text messages. Now, AI is capable of compiling, structuring, sorting, and analyzing all of this for generating insights that serve better decision-making amongst TPAs. Additionally, the AI can handle processes across activities, enabling TPAs to leverage historical data effectively for managing their business.
● Improved fraud detection and prevention – TPAs can leverage AI to reduce the risk in insurance claims by establishing oversight of claims and highlighting anomalies through historical data comparisons. Insurers can also better forecast claims more accurately using AI, thus allowing them to optimize risks that will positively impact their combined ratios.
● Reduced processing times and costs – Since AI can process data faster and more accurately, the overall time taken to process claims gets reduced with greater efficiencies built in. These two factors cut down operational costs while driving better customer retention due to better relationship management.
● Better accuracy and consistency in claims assessment – Since AI can manage mundane work consistently, it leaves the TPAs with time to plan for additional workloads and its adjusters to focus on more value-added claims handling activities. Error reductions compared to manual data entry also ensure that insurers can deliver better customer experiences and deeper and more accurate data to the insureds they service.
Some challenges and considerations
As is the case with any new technology innovation, AI also brings with it some major challenges. Besides ethical considerations, there are questions about data privacy issues, compatibility across legacy systems, and preparing the workforce for a paradigm shift. Let’s explore some of these:
● Ethical considerations – A lot has been spoken about AI biases and how Insurer’s Claims teams and TPAs must be wary of them. AI models are being continuously trained, and insurers must assist in this process by sifting out obvious biases and correcting them. This is where human intervention plays a key role as the systems mature and learn to handle situations termed outliers.
● Data privacy and security – Data privacy and privacy fall under the purview of global laws, making it imperative for insurers to install adequate measures. Any leaks could result in repercussions for the insurer and the insured, besides bringing the regulatory norms into focus.
● Integration and compatibility – Integrating new technologies with legacy systems is a challenge at the best of times. TPAs need to make early investments to upgrade their systems to build compatibility so that AI can function seamlessly.
● Training and upskilling – Finally, the TPA workforce must be skilled in using AI in claims handling. Retraining and capacity-building investments would be crucial for getting optimal productivity from AI investments.
Future trends and outlook
As the insurance industry adopts AI in claims, it is becoming evident that the industry is benefiting through enhanced customer experience, faster claims processing, automation of manual and repetitive tasks, and improved accuracy and consistency of data, resulting in better insights. This is important as Insured and TPA claims organizations look to tackle the evolving claims adjuster staffing market challenges.
The industry is moving toward composite AI and generative AI for advanced use cases like automated damage assessment, dynamic fraud prevention, and hyper-personalized customer engagement.
The next stage of this evolution involves broadening the scope of data collection from connected devices, which further simplifies the claims processing through better risk assessments.
In conclusion
Artificial Intelligence is already making an impact on the claims processing efforts. They have considerably reduced manual operations and given the TPAs more time to play a strategic role in the business. Early adopters have reported improved bottom lines by up to 20% in their operations, taking the first step towards integrating structured and unstructured data and obtaining historical information for better quality analysis and insights. The growing use of Internet of Things (IoT) devices in the health, automobile, and real estate business would add considerably to the data sources and deepen the insurance industry’s involvement with AI. All these innovations would drive a positive impact not just for the insurers but also for its customers.
