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The insurance value chain has benefited immensely from the role played by reinsurance over the years. Reinsurance has provided primary underwriters the much needed increase in underwriting capacity, stabilization of underwriting results and access to expertise in product development, pricing, underwriting and claims for new emerging risks. The recent disruptions brought about by advances in technology, rapidly changing customer expectations, changing market demographics and stringent regulatory norms have impacted the reinsurance industry as well. The growth and changes in the primary insurance market have a direct impact on reinsurance and there is a sustained pressure on reinsurance to adapt to the current, rapid pace of change as well as to the future risk landscape.
The pressures that the reinsurance market faces are the result of many factors, including:
Although the fundamental principles of Reinsurance cannot change, the disruptions brought about by way of technological improvements have created opportunities to do business more effectively. AI (Artificial Intelligence), RPA (Robotic Process Automation), Advanced Analytics, High level Automation, Machine Learning, Block chain and the IoT (Internet of Things), are a few of the disruptive technologies that have impacted all industries. Reinsurers worldwide are looking to rapidly adopt relevant digital transformation in their businesses to drive growth and profitability. It is through these long-term initiatives that reinsurers expect cost savings and operational efficiency in the near future. Driven by the advantages and opportunities that the new digital technologies provide, reinsurers are realising the potential for innovative products and services, better turn-around-time, improved customer experience and greater operational efficiency.
Current Challenges in the Reinsurance Landscape
The reinsurance industry by nature is a very niche domain with small numbers of professionals and domain experts. However, the processes in the present value chain are predominantly manual and are highly dependent on the personal expertise and knowledge of the reinsurance personnel. The inherent complexity of the processes involved coupled with the fact that only a few processes are documented, makes the process of comprehensive documentation for the sector a really challenging task. This is partly because the processes followed are very person-centric and that is a further challenge to standardisation or automation. The number of reinsurance solutions available in the market are very few. In addition, the inclusion of multiple stakeholders and the long-tailed or prolonged effect of transactions, makes the entire process very time consuming. With the accounting, reconciliation and settlement processes consuming about 45 percent of the time spent in a reinsurance cycle, the time is at hand for reinsurers to effectively use the opportunities available through digitisation to simplify their processes and enhance efficiency.
The innovations in technology like Artificial Intelligence (AI), Internet of Things (IoT), Robotic Process Automation (RPA), Machine Learning and the advanced use of analytics must be leveraged to create a radically new and efficient reinsurance market place. The use of digital technology in reinsurance will help to increase operational efficiency, reduce the cost of operations and improve accuracy. Some of the reinsurance functions where digital technologies can be effective are:
Three key new technologies and how they can revamp the reinsurance industry:
RPA automates high-volume, manual, repeatable tasks by replicating human interaction with computers. Intelligent or cognitive computing – a more advanced version of RPA, utilises machine learning and artificial intelligence to perform human tasks that need problem-solving skills and decisions. RPA can be used mainly in the areas which need manual intervention to consolidate data available in disparate formats:
Reinsurance is a highly document-intensive function – and this is where Smart Data Extraction can play a vital role in the conversion of data which exists in the form of scanned images, pdf documents and excel files. This will bring about the greatest changes in activities that typically take between a few hours to as long as three days by bringing down the processing time a fraction of the time that it used to take earlier. One of the several use cases of application of these tools in the reinsurer space is automated contract setup for facultative certificates and treaties. Similarly, data for premiums and claims data for processing and accounting can be done in a highly effective and economical manner with digital tools. Cognitive algorithms and character recognition engines make sure that the extracted data is precise and accurate.
Both insurers and reinsurers generate massive volumes of data in the normal course of their businesses. This data can be very effectively used through big data analysis and data mining to create advanced statistical models that will help reinsurers to more accurately forecast events. The wealth of computing power and the large data storage capacities that are available to insurers today, provide reinsurers the ability to easily and effectively analyse data, gain deep insight, predict and recommend actions. Analytics and AI have a many applications in the reinsurance space especially when it comes to reinsuring the weather derivatives such as agriculture, windstorms, hurricanes and other CAT lines of business. With technological advancements available like data from satellite imagery, weather forecasts in real time, hazard recognition, and demographic analyses, etc., underwriters are better positioned to more accurately assess risk exposure and forecast loss occurrences with greater accuracy. One of the critical areas in advanced analytics is catastrophe risk modelling as it has the potential to massively impact most of the reinsurance functions like risk selection, risk prevention, portfolio analysis and pricing decisions. Reinsurers are also exploring new avenues such as Customer Analytics and Social Analytics, which have not been of mainstream relevance in the reinsurance industry.
The disruption wrought with the arrival of digital technologies is an opportunity for reinsurers to adapt, stay relevant and yet, ensure profitability. While many aspects driving the need for reinsurance due to colossal catastrophic losses are mostly limited to capital needs, emerging risks and the need to grow and thrive in a market that has grown fiercely competitive, are driving reinsurers to explore new business models supported by emerging digital technologies. In addition to the traditional reinsurance functions, reinsurers are now extending their business domain to cover loss prevention, risk mitigation, product innovation and data driven underwriting to maintain a holistic, healthy and balanced portfolio that is eminently capable of weathering the storm of digital disruption.