What if automation could help efficiently and accurately estimate risk reserves?
CLIENT
Prime Meridian Direct
Industry
Insurance
LOCATION
South Africa
YEAR FOUNDED
2009
Insurers are under increasing pressure to effectively and proactively protect their policyholders and mitigate risk amid the rising threats posed by climate change and cyberattacks.
Outstanding Claims Reserve (OCR) processes, which act as a buffer to cover the cost of claims incurred but not yet paid, are key to an insurer’s financial health. An inadequate OCR can risk an insurer’s financial health and lead to regulatory problems, but manual processes often impede a company’s ability to improve its resilience through an effective OCR.
Prime Meridian Direct (PMD) sought to enhance its financial stability by automating its Outstanding Claims Reserve (OCR) process. With automation, PMD hoped to deploy a tailored OCR model that would revolutionize how they monitored and managed their reserves, would help streamline their operations, and would empower executives to make more informed decisions about reserve allocation and risk management. This combination of benefits would in turn strengthen the company’s financial position.
PMD’s systems did not afford the company a dynamic and accurate view of the reserves required to meet future claim payments. This resulted in uncertainty about financial stability and potential risks associated with under- or over-provisioning. In addition, the insurers’ manual processes were time-consuming and prone to errors, hindering effective decision-making and impacting its risk management.
PMD engaged Sand Technologies as a technology partner due to the company’s advanced data analytics and software engineering experience. Together, the companies developed a custom OCR model to incorporate specific claim process and line-level claim information to ensure accurate reserve setting.
In addition, traditional actuarial methods such as the Basic Chain Ladder (BCL) and Bornheutter Ferguson (BF) were implemented and automated to enable efficient real-time reserve estimation – a dramatic improvement over the previous three-month delay to receive estimates from their underwriter’s actuarial team. Sand Technologies also worked with PMD to build stochastic risk-reserving models to enable accurate confidence estimation of risk reserves by development period.
During a six-month implementation period, Sand Technologies and PMD leveraged eight data sources and ingested 5-10 million rows of data. Given the vast amount of data utilized, the companies adopted robust data guidelines to ensure the seamless collection and management of this data.
The solution was implemented using serverless Azure functions, allowing for efficient, cost-effective and scalable execution.
The successful implementation of the OCR automation solution helped PMD significantly enhance its financial stability and risk management practices. With its new platform, PMD is well-positioned to explore innovative AI and data-driven solutions in the future that will enhance its customer service and drive further operational efficiencies.
