NLPs and automated image analysis: How AI is being used to prevent insurance fraud

Image source: Ion Chiosea – 123RF.com

In 2022, insurance providers in South Africa detected approximately 8,931 cases of insurance fraud and dishonesty and prevented R1.1bn losses which would have affected the insurance industry as a whole. Despite this, one cannot ignore the fact that also in 2022 the insurance industry suffered losses amounting to R77m. So, how can AI be used to prevent any further losses?

Sophisticated scams

Fraudsters have identified sophisticated methods which are supported and made easier by digital tools in order to commit fraud. For instance, impersonation has become a big part of committing insurance fraud mainly because AI-powered deepfake technology is used to manipulate and bypass verification systems during the application process to create 'new' people with fake identities enabling them to apply for insurance and claim from insurance companies. AI and machine learning algorithms also enable fraudsters and criminal syndicates to exaggerate the extent of damages suffered by the insured through the manipulation and forgery of images, documents and audio recordings.

Further, the presentation of false death certificates for purposes of claiming from funeral policy insurance providers or failure to disclose crucial health information during application processes remains one of the largest acts of deceit that accompanies insurance fraud which, according to the Association for Savings and Investments South Africa, funeral policy fraud contributed approximately R17m to the total amount of losses suffered in 2022.

To fight against fraud, South African insurance providers are making use of AI and machine learning algorithms as key tools in fraud detection and prevention. This is done by using AI tools which utilise machine learning algorithms to analyse large volumes of data in order to identify patterns and red flags for potential fraudulent claims, which also assists insurance claim processors to identify those cases that may need to be investigated. This is a much more efficient way of processing claims as, unlike the traditional manual methods, AI can detect patterns much faster than paging through applications and claim forms.

Role of NLPs

Even with the use of AI systems, insurance fraud cases keep rising. However, insurance providers can utilise natural language processing (NLPs), a form of AI which can be used to analyse data including insurance claims and phone calls between policy holders and insurance processors. By using NLPs, insurance providers will be able to identify inconsistencies, conflict or language that varies from normal insurance claim patterns, which may indicate potential fraud.

Furthermore, insurance providers can utilise predictive analytics functions of AI to detect fraudulent claims before it happens by using and analysing historical data that already exists on systems of insurance providers and thereby pre-empting potential fraud. This will assist with detecting fraudulent claims before they occur.

Automated image analysis

Given that AI can be used to manipulate and exaggerate the extent of damages, AI can also be used to detect any inconsistencies in images submitted as part of insurance claims. Although not often used in South Africa, automated image analysis, as an AI machine learning tool, can offer a solution to insurance providers, especially in car accident-related and home insurance claims.

Using automated image analysis can prove to be much more effective in processing claims as this machine learning tool can analyse images in terms of the lighting, shadows and object placement in images to determine whether or not the image has been forged or manipulated or whether the image exhibits patterns of potential fraud.

Further, although it is possible (albeit a difficult task for the naked eye) for insurance processors to identify inconsistencies in images, automated image analysis can be used to detect these inconsistencies at a faster rate than that of a human being.

No single catch-all

Insurance fraud remains a persistent challenge for insurers and there is no one-size-fits-all solution to address it. With AI reshaping the world, there are many possibilities of detecting and containing fraud through the use of AI.

By employing automated fraud detection, predictive analytics and pattern recognition methods, the financial impact of fraud on businesses and policyholders will reduce significantly.

However, with AI predicted to grow exponentially as technology continues to develop, insurance providers will need to develop innovative and effective fraud prevention measures. For now, the preventative measures used by insurance providers are effective in reducing fraud in South Africa.