MLC Life Insurance is a specialized life insurance business that represents a landmark strategic partnership between National Australia Bank (NAB) and Nippon Life Insurance. With over 1,400 dedicated employees, the Australian-led and managed business has strived to meet the insurance needs of everyday Australians since 1886.
In an industry where many companies have been around for centuries, it’s no surprise that a good number of them are still relying on outdated legacy systems. As MLCL had grown, it had acquired many different businesses, each with their own data assets, tools, tech stacks, and policy administration systems. In such a heavily regulated industry, MLCL needed to go through a rigorous approval process from entities such as the Australian Prudential Regulation Authority (APRA) before it could adopt any new technologies, which was required to ensure that data would be protected and held within Australian data centers.
Moving toward a predictive operating model
MLCL’s cloud modernization strategy is built on the Snowflake Data Cloud. Regulators need accurate, clean data that shows the business is being well managed. Centralizing legacy data assets on Snowflake gives MLCL the rigorous governance needed to meet APRA compliance standards.
According to the company’s Head of Data and Analytics Scott Williamson, “We chose the Snowflake Data Cloud because it allows us to maximize our data assets and take advantage of best-of-breed tools available. In the insurance industry, it’s all about prediction. We want to have deep, rich data to move the business into a predictive operating model rather than a descriptive one. Ultimately, it allows us to better serve our customers.”
Designing an architecture for the future
Recognizing that they had a large payload to migrate to the cloud, Williamson’s team decided to bring on Snowflake Professional Services from the very beginning.
“We wanted to get it right, as close as possible, on the first try. That’s why Snowflake Professional Services was extremely important to us.”
Scott Williamson, Head of Data and Analytics, MLCL
Not only did MLCL have to prove Snowflake met APRA requirements, the company’s own security team, led by its CISO, had their own laundry list of security validations as well. According to the Snowflake’s Professional Services team, “We have a lot of past experience from previous clients, so MLCL’s requested turnaround time was very achievable with us supporting them.” Life insurance data is incredibly sensitive because it’s about people’s lives, and that includes financial and medical information that need to be protected.
Whether it was working with the security team to ensure HIPAA compliance, integrating with Okta, meeting SOC1, SOC2 security standards, or running multiple, rigorous POC tests for APRA approval, MLCL was able to successfully partner with Snowflake Professional Services to co-design an architecture that met and exceeded all of the company’s requirements
This new architecture is designed to easily allow MLCL to onboard future use cases. Whether it’s adopting new technology such as Informatica that plugs directly into Snowflake, or future expansion into a data lake, it will not require a heavy lift from MLCL. Instead, users will be able to quickly adopt and accelerate value from the platform.
A quick sample of performance improvements MLCL saw with Snowflake:
- Former SQL Server EDW process took almost 5 hours to ingest and move data till raw vault. With Snowflake this overall time is reduced to 1 hour.
- From Raw Vault to Business Vault SQL Server took 2 hours. Snowflake is able to process this in 15 minutes.
- Month-end reporting process usually took 2 days to finish and was dependent on daily jobs. Now with Snowflake, the job finishes within half a day.
Needed insight to grow while managing costs
Williamson views success based on speed and consumption; that is, success is measured based on how fast a technology can be implemented and how quickly people adopt and consume it. However, it needs to be carefully balanced with cost.
“As we move into the cloud, it’s incredibly important for us not to get shocked by the cost, as can easily happen with many cloud-based technologies,” he said. “Snowflake’s separation of compute and storage itself already brings much value. But even more valuable to us were the dashboards that [Snowflake] Professional Services built for us to monitor usage and model the credits we may consume as our business grows year-over-year. That way we can manage our usage effectively.”
Now business units and data science teams across MLCL can freely experiment and iterate without worry.
“The biggest challenge for any organization is adoption of a new tool. But in this situation, people are eager and quick to embrace Snowflake because it’s what they’ve been waiting for. It’s helping them overcome previous limitations and has unearthed real opportunity.”
Scott Williamson, Head of Data and Analytics, MLCL
MLCL has many predictive workloads to model its future risk of insurance positions at the end of every month, which helps it to understand the business’ health. With its legacy infrastructure it took up to one full week to run the report, and required many manual steps for data preparation. Now with Snowflake, MLCL expects those end-of-month reports to be ready before the day has even started
“First, taking out the manual effort to run those reports is huge,” said Williamson. “Secondly, having Snowflake as our single source of truth and bringing in more data will help us understand with even greater clarity how our exposure has changed month to month.”
With Snowflake now at the center of MLCL’s new architecture, and Snowflake Professional Services consulting the company on how to unlock additional innovation with Snowflake, Williamson expects rapid adoption across business units, which will bring even more value over time.