Scene sketch semantic segmentation is a crucial task for various applications including sketch-to-image retrieval and scene understanding. Existing sketch segmentation methods treat sketches as bitmap images, leading to the loss of temporal order among strokes due to the shift from vector to image format. Moreover, these methods struggle to segment objects from categories absent in the training data. In this paper, we propose a Class-Agnostic Visio-Temporal Network (CAVT) for scene sketch semantic segmentation. CAVT employs a class-agnostic object detector to detect individual objects in a scene and groups the strokes of instances through its post-processing module. This is the first approach that performs segmentation at both the instance and stroke levels within scene sketches. Furthermore, there is a lack of free-hand scene sketch datasets with both instance and stroke-level class annotations. To fill this gap, we collected the largest Free-hand Instance- and Stroke-level Scene Sketch Dataset (FrISS) that contains 1K scene sketches and covers 403 object classes with dense annotations. Extensive experiments on FrISS and other datasets demonstrate the superior performance of our method over state-of-the-art scene sketch segmentation models. The code and dataset will be made public after acceptance.

Digital channels targeting the mass consumer market are helping insurers swell their client base without the need for traditional intermediaries – but at a cost. One cost is increased risk of fraud, global insurance fraud analytics firm FRISS said during an event in Chile outlining the results of the first fraud survey of its kind covering all Latin America. As technology develops and purchasing habits change, insurers are increasingly leveraging digital channels, allowing consumers to take out policies online, directly from an insurer, in a largely frictionless manner. The trend is forecast to continue in Latin America as insurers seek to keep costs under control, tap what is still an underpenetrated market, and stand out from the crowd. One consequence of this is the sidelining of brokers, whose detailed client knowledge can help prevent fraud, said FRISS, a Dutch firm that provides an AI-powered platform to help P&C insurers combat fraud and which carried out the survey of insurance companies.

FRISS, a provider of AI-powered fraud and risk solutions for the property and casualty market, has announced that it has extended its partnership with Munich Re to support insurers worldwide in the fight against fraud risk. The extension of the agreement comes after FRISS and Munich Re successfully cooperated in Latin America and Iberia to mitigate fraud risk at P&C insurers. FRISS provides a combination of AI, predictive models, network analysis and text mining for more than 600 risk and fraud indicators that are used by insurers for real-time risk assessment in underwriting, fraud detection during claims and investigations at the special investigation unit. "Many of our insurance clients see the need to increase efficiencies, reduce claims costs and improve their competitive edge by an increased use of automation," said Joachim Mathe, head of Munich Re's global consulting. "To take full advantage of these new opportunities, insurers must arm themselves with relevant digital and data-analytics competency, including a modern IT system supporting such competencies. The combination of our strategy expertise and global player know-how with AI-powered fraud and risk solutions provided by FRISS will help our clients make effective big-picture decisions."

FRISS announces its participation at Booth 802 during ITC 2019, the world's largest insurtech event to be held September 23-25 in Las Vegas. Yannick Brethouwer, VP Technology, and Kurt Jackson, VP Sales, will give a demonstration on September 25 at 11:30am in the Expo Hall's Innovation Alley. The demonstration showcases FRISS' unique underwriting solution, allowing insurers to onboard customers in a split second while refusing policies that would likely challenge their profitability. The FRISS demo will showcase several use cases in just 8 minutes, highlighting the speed at which actionable insights are provided to make better decisions. FRISS Risk Assessment at Underwriting allows insurers to screen new policy requests and renewals to assess risk in real time, with most screenings taking only one second to return actionable insights.

Insurance companies consume terabytes of information every day in the form of digital data. Valuable data is being provided by more and more sources, which quickly paints a reliable picture of a risk or a submitted claim and makes it possible to filter out unwanted risks and fraudulent claims. State-of-the-art technology is required to process this influx of information and convert it into applicable knowledge and insights. This calls for intelligent software capable of processing information quickly, learning independently, drawing smart conclusions, and making recommendations – similar to a human, but then smarter and more efficient. We can identify roughly three types of artificial intelligence.