Fraudulent claims are increasing yearly, driving up premiums for honest customers and placing operational and financial strain on insurance companies. Businesses must address this growing problem. However, detecting and preventing fraud is challenging without the latest tools.
Fraudsters are becoming increasingly sophisticated, leveraging technologies that outsmart traditional systems. One solution is to invest in innovative technologies, such as artificial intelligence (AI). Many companies have already integrated AI to combat scams, helping insurers prevent them in various ways.
An overview of business insurance fraud
Insurance fraud is a growing challenge for businesses and insurers. Recent data reveals the scale of the problem, with one out of every 30 claims being fraudulent. In 2023 alone, there were 115.3 reported cases of insurance scams worldwide. The effects of such activities are far-reaching in monetary losses and operational inefficiencies.
For example, processing a claim suspected of fabrication takes three times as long, leading to delays and increased administrative costs. Moreover, 68 percent of industry professionals anticipate fraud rising over the next five years, making prevention more important than ever.
The main factor driving insurance fraud is the sophistication of the methods used.
Advancements in technology have given rise to more complex schemes, such as deepfakes and synthetic identities, social engineering tactics, and image-enhancing software. Each technique makes it more challenging to detect scams, which is why insurers and businesses must adopt advanced tools to counteract these schemes.
How AI helps with business insurance fraud
Like many other industries, insurance is utilizing AI more frequently, especially as insurance forgery becomes increasingly complicated. Artificial intelligence has become a powerful tool in this fight, offering innovative solutions to detect and respond to fraudulent activities more effectively.
Because it is protecting businesses on a greater scale, 42 percent of insurers have already invested in generative AI tools, while 57 percent plan to do so in the near future. The following are ways insurers are using AI tools to implement safety and efficiency.
1. Facilitates real-time fraud detection
AI can detect fraud in real-time by analyzing vast amounts of data for patterns that would be impossible for humans to find quickly. It then leverages advanced algorithms to monitor every claim that comes through.
When submitted, the technology can flag suspicious activities, such as inconsistencies in documentation, unusual claim amounts, or repetitive claims from the same individual or entity. This instant analysis allows insurers to act swiftly, reducing the time spent investing and preventing payouts.
2. Identifies anomalies with machine learning
Machine learning is excellent at detecting anomalies in insurance claims by analyzing datasets and understanding patterns over time. Traditional methods rely on static rules, but machine learning algorithms improve over time with new data. This allows the technology to detect irregularities and signal indications of fraud.
For example, these systems can compare a claim’s details against historical data to spot inconsistencies, such as claims that deviate from typical patterns. By continuously refining their models, machine learning tools become more effective, enabling insurers to focus on high-risk claims while streamlining legitimate ones.
3. Authenticates documents with computer vision
Computer vision is crucial in verifying insurance claim documents. By analyzing photos, videos, and scanned documents, its algorithms can detect signs of tampering or manipulation. For instance, it can find inconsistencies in lighting or pixel patterns that suggest an edited image.
Additionally, computer vision tools can cross-reference submitted documents with databases to verify their legitimacy, such as checking license plates or property ownership records. This advancement accelerates verification, improving efficiency and trust in the claims process.
4. Monitors behavioral patterns with predictive analytics
AI-powered predictive analytics can also detect irregularities in user activity. It will analyze user behavior, such as login frequency, geographic locations, or changes in claim submission patterns. These insights allow insurers to continue investigating potential fraud before it escalates.
5. Enhances customer verification with natural language processing
Natural language processing (NLP) is a branch of AI that focuses on understanding and analyzing human language. In the insurance industry, companies can use it to strengthen customer verification processes by identifying inconsistencies or red flags in written or verbal communication.
NLP algorithms can achieve this by analyzing language used in claim descriptions, emails, and phone transcripts to detect signs of deception, such as contradictory statements. Additionally, NLP can cross-check customer information with other records to verify accuracy. By automating these checks, NLP reduces manual effort and ensures quick processing of legitimate claims.
6. Predicts emerging fraud trends
AI’s ability to analyze historical data and real-time patterns allows systems to notice shifts in fraud schemes before they become widespread. For instance, machine learning models can detect an uptick in claims with similar fraudulent characteristics.
Additionally, AI can assess external factors like economic conditions or regional events to anticipate fraud spikes in vulnerable areas. This capability enables insurers to stay ahead of evolving tactics to address new schemes before they cause damage.
Using AI for fraud prevention
As insurance fraud increases, so does the need for AI to prevent it. This innovation has become invaluable for numerous reasons. It streamlines claims processing and saves businesses significant time and money while keeping insurers one step ahead of new tactics.
As deception continues to evolve, staying proactive in the latest AI prevention strategies will be essential. Companies can benefit from AI solutions, as investing in them will ensure long-term resilience and success in the sector.
Zac Amos is the Features Editor at ReHack, where he covers business tech, HR, and cybersecurity. He is also a regular contributor at AllBusiness, TalentCulture, and VentureBeat. For more of his work, follow him on Twitter or LinkedIn.
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Based in New York, Stephen Freeman is a Senior Editor at Trending Insurance News. Previously he has worked for Forbes and The Huffington Post. Steven is a graduate of Risk Management at the University of New York.