While artificial intelligence (AI) promises faster and smarter decision making, the Actuaries Institute and the Australian Human Rights Commission (AHRC) worry about potential discrimination and highlight the need to prevent this. To address the issue, they created a Guidance Resource designed to help insurers and actuaries to comply with the federal anti-discrimination legislation when AI is used in pricing or underwriting insurance products. The guidance was developed after a 2021 report by the AHRC that looked at the human rights impacts of new and emerging technologies, including AI-informed decision making. The Actuaries Institute strongly supported the report's recommendations to develop a set guidelines for use by the government and non-government organisations on complying with federal antidiscrimination laws when AI has been used in decision making. It approached the AHRC with a collaboration offer and together they developed these guidelines.

CoreLogic has announced an extended relationship with Google Cloud to support the launch of its new CoreLogic Discovery Platform. Built on Google Cloud's infrastructure, Discovery Platform provides a comprehensive property analytics environment and cloud-based data exchange for businesses across multiple sectors. CoreLogic launched Discovery Platform in June earlier this year, stating that the new product would enable businesses--including property and real estate technology (PropTech/ReTech), mortgage lenders, marketers, and insurance firms--to discover, integrate, analyse, and model property insights to make critical business decisions faster. The multi-year relationship between CoreLogic and Google Cloud enables the development of a scalable platform built with several Google Cloud services including Dataproc, BigQuery, Anthos and Cloud Run to manage the data science workloads for predictive and prescriptive analytics. BigQuery is the petabyte-scale backend for the platform, enabling comprehensive property data views built from a wide array of CoreLogic and third-party data sets.

GCube has launched a new data-powered insurance offering to support the growth of the renewable energy industry, with support from Clire, a company dedicated to maximizing project returns from renewable energy assets. The offering will leverage AI-led analytics and data sets to offer enhanced terms and reduced premiums for wind and solar operating companies. By having Clir onboard a wind portfolio's data set onto its platform, GCube will aim to uncover an asset's meteorological and operational loading, overall component health and reliability, and the impact of current operations and maintenance. These insights will give GCube clarity on its underwriting pricing, and offer more competitive terms where operating projects model with lower risk factors. "Insuring renewable energy has been a tumultuous process over the last decade," said Fraser McLachlan, Chief Executive Officer, GCube Insurance Inc. "Claims from equipment failure, natural catastrophe loss and contractor error have forced some underwriters to exit the market. To continue to offer insurance at sustainable rates for clients, we need to have deeper insights into the risk of failure and operational management of renewable energy equipment."

Cloud computing will become a common technology in the insurance industry over the next decade, according to a survey by Sollers Consulting. Robotic Process Automation (RPA) is seen as more important in the market than Artificial Intelligence and Machine Learning, while Telematics and the Internet of Things are weighted comparatively low. The survey showed that over eight of the top ten insurers in the markets will rely on cloud and robotic process automation (RPA) by 2031. Artificial intelligence and machine learning will also be important, but they score slightly lower than RPA. While open APIs are almost as important, the Internet of Things (IoT), telematics and blockchain are not seen as top issues in the insurance industry.

By utilising machine learning and numerical text processing techniques, Swiss Re has been able to generate a "predictive view" of motor frequency developments in several markets. In a recent conversation with Nikita Kuksin, Hhead of modelling within Casualty R&D, Miriam Hook, vice president Global clients and Surbhi Gupta, assistant vice president, casualty R&D at Swiss Re, it was explained to us how these alternative approaches were able to provide added granularity to existing data. "We intended to develop an alternative to traditional actuarial calculation methods that would give us an "external perspective" on claims frequency within our motor portfolio and allow us to predict motor frequency developments in several motor markets," said Kuksin, who leads the modelling team within the casualty research and development department at the Swiss Re Institute. Gupta, who prior to her current role served at Swiss Re for three years' as a data scientist, explained how these methods were brought into fruition by first checking the status quo of frequency developments against external data, before then explaining motor frequency using external data to generate factors that could be projected into the future. "These are complex objectives, requiring solid data sets and robust analytics," Gupta explained.

Reinsurer Munich Re sees data analytics and artificial intelligence as key tools to open up new possibilities for managing and covering risk, and for supporting insurers across the entire value chain. "At Munich Re, our goal is to pioneer digital solutions for the insurance industry," said Doris Höpke, Member of the Board of Management "So we have been investing heavily in data analytics and artificial intelligence, in order to support our clients with innovative methods and new products," she explained in a statement ahead of the industry meeting in Baden-Baden. Munich Re says it is focused on combining primary insurers' portfolio data with external public sources, such as site geography, building construction, weather, or socio-economic status. By applying machine-learning principles, the company then looks to discover hidden loss drivers and respond with loss-prevention measures or by adjusting pricing. "This means faster claims estimates and handling, and better pricing as a result of improved accuracy in risk assessment," Hopke continued.

With mass tort style litigations reaching new highs in 2019, insurance and reinsurance companies should increasingly be thinking about how to capitalise on this emerging opportunity, according to Robert Reville, CEO of insurtech risk modelling and analytics firm Praedicat. Speaking at the Reinsurance Rendezvous event in Monte Carlo, Reville explained that a number of factors had come together to drive the increase in mass litigation activity this year. For example, hedge funds and other sources of capital are now helping to finance litigation in the US, making it possible for the plaintiff's to continue to drive very expensive forms of litigation. What's more, Praedicat believes there is a sense that the jury pool in the US is increasingly suspicious of corporations, and are more willing to accept that they could have been involved in nefarious actions. Finally – and of most relevance to the re/insurance industry – is the decades of accumulated science that is being brought to bear to describe what corporations are selling and doing that could potentially cause bodily or property damage, or environmental damage.

Munich Re has announced a new partnership with re/insurance industry consortium the Geospatial Intelligence Center (GIC) to provide its members with access to automated damage classification analytics following major catastrophe events. The GIC provides its members with access to imagery and data that enhance underwriting assessments, expedite claims, and improve fraud detection following hurricanes and other disaster events. By collaborating with Munich Re, the consortium will now be able to provide its members with a damage assessment heat map layer to complement its imagery and improve situational awareness post-disaster. Munich Re's analytics solutions can process the GIC's aerial imagery with machine learning models to detect building shapes and damage to individual properties, as well as to impacted geographic areas at large. In the lead up to a catastrophe event, the reinsurer's model can also predict estimated losses using data on property characteristics, weather forecasts, and weather stations.

The UK government has announced that it plans to invest in 40 artificial intelligence (AI) and data analytics projects to boost productivity and improve customer service in the UK insurance, accountancy, and legal services industries. The government has pledged £13 million to support these collaborative industry and research projects and develop the next generation of professional services. One of these projects, developed by Intelligent Voice Ltd, Strenuus Ltd. and the University of East London, will combine AI and voice recognition technology to detect and interpret emotion and linguistics to assess the credibility of insurance claims. Another project is an analysis tool that looks at images collected by drone to assess flood-damaged areas, using a 3D image recognition system to evaluate flood extent and depth alongside impacts on buildings and infrastructure to help with insurance claim assessments. Other examples include an online bot that uses AI to provide answers to online legal questions and software that analyses accounting data and suggests ways to cut expenditure.

QBE Insurance Group has announced that its venture capital arm, QBE Ventures, has closed an investment into machine learning tech firm Hyperscience, and has entered into an agreement to roll out its solutions across QBE globally. Hyperscience uses artificial intelligence (AI) to develop solutions for automating office work across verticals like re/insurance, financial services, health, and governments. It aims to reduce companies' dependencies on costly, slow, and error-prone manual data entry operations by automating the transformation of human-readable content into machine-readable data, and with greater speed and accuracy than legacy data capture technologies. This allows clients to facilitate straight-through-processing, achieve faster customer response times, and unlock data that has otherwise been trapped in static or unsearchable documents. David McMillan, Group Chief Operations Officer (COO) at QBE Insurance Group, said: "This is a practical use of artificial intelligence that will, in a short time, add tangible value to our business. "From driving operational efficiency to unlocking a wealth of new data and insights, HyperScience has delivered a platform that will support QBE's objectives of delivering "Brilliant Basics" in underwriting, pricing and claims." Ted Stuckey, Managing Director of QBE Ventures, added: "QBE Ventures backs companies which are working on technically-challenging and industry-changing ideas.