With advances in Artificial intelligence (AI), insurance companies can now identify and understand behavior patterns and model risk with unprecedented levels of accuracy and efficiency. But policy underwriting is not the only mission critical business for insurers. Insurance companies are also some of the largest institutional investors in the world, with more than $6.5 trillion in cash and investment assets under management by U.S. companies, alone. Plunging interest rates have compelled these firms to extend their portfolios beyond traditional fixed assets into broader asset classes, including complex derivatives and alternative assets such as limited partnerships, bank loans and others to squeeze out more substantial returns.
Diversified investment strategies require more sophisticated middle and back-office technology to accommodate the increasingly complex processing of trades, cash transactions, compliance, collateral management, corporate actions, investment accounting updates and daily reconciliations. Legacy investment operations and accounting systems currently used by most insurance firms today will be challenged to efficiently handle the processing of these new investment instruments. Manual workarounds, including the use of offline spreadsheets, are time consuming, costly and error prone. Insurers will meet this challenge with next-generation investment operations and accounting systems that have been built from the ground up with embedded, innovative technologies such as Machine Learning (ML), Predictive Analytics, Robotic Process Automation (RPA) and Natural Language Processing (NLP).
Insurance firms embracing disruptive technologies in investment operations and accounting
In fact, a recent SS&C survey of 100 insurance company investment operations professionals revealed that 75% of these firms are either actively deploying or evaluating such innovative technologies. As such, it was no surprise that “Practical Applications of Disruptive Technologies for the Insurance Industry,” presented by SS&C’s Managing Director and Global Head of Singularity Product Marketing, Scott Kurland, was one of the most popular sessions at the recent Midwest IASA Conference, in Council Bluffs. Iowa. The session was attended by more than 50 professionals from leading insurers based in the Midwest region.
In his presentation, Kurland explained that the main challenges facing insurers in seeking to adopt disruptive AI technologies include established legacy architecture of existing investment operations platforms, a lack of internal technical and business domain expertise and transparency to fully exploit these new technologies, and limited in-house access to data sets required to adequately train Machine Learning and NLP models. Kurland pointed out that many of these challenges can be overcome by partnering with a solutions service provider that is heavily invested in these technologies. Skilled partners such as SS&C can host these next-generation platforms in the cloud, accelerating deployment and maximizing scalability while minimizing end-user maintenance and operational risk.
SS&C is also working to demystify AI-driven results by providing visible diagnostics and audit trails on the behavior and decisions of the AI, while training and testing the validity of Machine Learning models against results from thousands of SS&C data and document samples. Kurland explained that the efficiency gains achievable through the deployment of advanced technology platforms, such as SS&C Singularity™, can be dramatic. They range from 20-30% improvements in trade processing and manual data entry where predictive analytics are deployed, to more than 50% where ML, NLP and RPA are used to facilitate counterparty reconciliations and unstructured document processing.