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Anadolu Sigorta was awarded two separate awards with its digital transformation projects at the Smart–i Awards organized for the 10th anniversary of the foundation of Smart Life Magazine and Sigorta Gündem. Anadolu Sigorta, which has won the Golden Smart-i award with the AS Artificial Intelligence and Image Damage Prediction Project and the Silver Smart–i award with the SOBE - Abuse Detection Platform project, has once again registered its achievements in digital transformation.
Anadolu Sigorta continues to crown its success in the field of digital transformation with awards. The company was awarded two separate awards at the Smart–i Awards competition with its ’Image Damage Prediction Project with Artificial Intelligence with ACE‘ and ’SOBE - Abuse Detection Platform'.
Smart-i Awards, organized specifically for the 10th anniversary of the foundation of Smart Life Magazine and Insurance Agenda, is the first award program based on innovation in the insurance sector in Turkey. Almost 100 applications were submitted to the competition, where innovative projects with products and services aimed at the development of insurance and innovative projects stood out. The winners were announced at the award ceremony held at İş Sanat Cultural Center on Thursday, June 23.
“We have a very strong team in the field of artificial intelligence”
Anadolu Sigorta's Deputy General Manager Mehmet Abaci, who explained that they are happy to be rewarded for their successful activities in the field of digitalization, Anadolu Sigorta said: “Today, all companies have understood the importance of data. With the more effective use of data, we also continue to develop data-based, more customer-oriented products. We have a very strong team in the field of artificial intelligence. We provide better service to our customers thanks to the applications we have developed using artificial intelligence effectively. We are increasing our artificial intelligence competencies and the number of employees in this field. At the same time, we have recently significantly expanded our team that develops analytical solutions that translate data into information.”
“We aim to differentiate ourselves by going beyond the classical methods in damage services”
Mehmet Abaci, who said that they have made their customers' lives easier with the AS Artificial Intelligence Damage Prediction project that they have put into service in April 2020 said: “With the pandemic, the concept of social distance entered our lives, consumer behavior has also changed in this direction. This allowed faster transfer of high-tech solutions to service processes. Our goal is to go beyond the classical methods needed for damage detection by differentiating in damage services. In this way, we want to increase our competitiveness and preferability by providing services in a shorter time independent of time and space. We estimate damage from the image with more than 20 artificial intelligence models developed with internal resources. We have accelerated our innovation efforts by integrating the image processing ability of AS with the damage system. We are able to provide end-to-end autonomous service with our internal systems within the reach of our insured and agents for the most common types of damage.”
“We analyzed about 110 thousand damage files and more than 3 million photos through Artificial Intelligence with AS”
Abacı said that AS can identify the damage from the photo, recognize the 24 parts belonging to the vehicle through the photo or video and identify the damaged parts by detecting the damage from the photo, and stated that after this determination, the decision to replace or repair the damaged part can be made. Abaci also stated that heavy damage detection is possible with fair price control and that a damage report can be created accordingly and said: “With the determination of the appropriateness of the damage, we provide a referral to a mini-repair service that does not violate the non-damage. On the Asli.ai website that we have prepared for this application, users can reach a damage assessment estimate in a very short time by sharing photos of the damage in their vehicles. We analyzed about 110 thousand damage files and more than 3 million photos through AS. With the project, the average time for a claim claim, which was 25 days, including paper works and appraiser analysis, was reduced to 5 days.”
“We have improved the misconduct detection rate by 51 percent”
Noting that misconduct is one of the biggest problems for companies in the insurance sector, Abaci said “Stakeholders of damage in organized crime structures make erroneous damage reports. These misleading notices may include material and physical damages. The main purpose of organized criminal organizations is to mislead insurance companies to pay for damage. In order to prevent insurance misconduct, we have developed an insurance misconduct detection process in the SOBE –Misconduct Detection Platform project. For auto insurance, fraud events in damage files, interpersonal interactions with analytical model, rule engines, social network analysis, and anomaly scenarios in damage files can be detected. Thanks to this platform, the necessary methods and capabilities for effective abuse detection are obtained. Thanks to SOBE, we can easily detect organized gangs by examining all file relationships with social network analysis. We are the only insurance company in Turkey that uses the abuse platform with rule engine, calculating scores with machine learning, analytical flow and social network analysis and organized crime detection modules live. By closing the old application, we saved an annual maintenance and development cost of around 100 thousand euros. We have improved the abuse detection capability by 51 percent compared to the old platform and have achieved approximately 11 million TL more savings compared to the old system in the last two quarters. Thanks to the organized misconduct detection module, 5 gangs were identified and reported to the police forces. In this way, approximately 3 million TL was saved.” |
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