Like Cindy, you also spent most of your career in traditional underwriting roles. How much does that knowledge and experience help in your current role on the Velogica team?
I couldn’t do what I do without it. Yes, I’ve moved from a traditional production environment to a technology-driven environment, and we’re using different tools to underwrite, but the goal is the same: evaluate individual mortality risk and protect the insurance company from taking on too great a risk.
It takes skills and knowledge from multiple fields of learning to automate the underwriting process, and knowledge of traditional underwriting and underwriting rules is essential to getting it right. We have professionals on the Velogica team that come from various disciplines. They bring skills that are fundamental to building and maintaining an underwriting algorithm – in actuarial, data, and behaviorial sciences, artificial intelligence and machine learning. But everyone on the team needs to learn underwriting concepts – and they do – just in a different way than I did.
What data sources are used in the Velogica engine today?
Velogica uses information in the application, prescription data, MVR, MIB, criminal history, clinical lab data, and we are in process of implementing credit-based mortality scores. A combination of sources may be used, based on client preferences.
How do some of the newer and emerging data sources compare to the more tried and tested e-data sources?
Rx was a big leap forward because it brought medical information into the automated process. The newer electronic data that we are integrating into the Velogica algorithm – like clinical lab data (CLD) – has enormous potential. CLD can be a highly effective replacement for fluids from both risk assessment and cost perspectives, giving the underwriter the ability to stratify otherwise declinable cases on a simple product.
Clinical lab data is just the most recent example of how SCOR is constantly working to keep the flexibility and power of Velogica up to date and with the latest data available to underwriting automation.
What products can be underwritten using Velogica?
Velogica is being used across the product spectrum from final expense, simple and fully underwritten products. It has the potential to also underwrite group, disability, long term care and critical illness. The algorithm obtains underwriting evidence, correlates both disclosed and discovered evidence and renders a decision, most of the time in less than a minute.
It’s highly versatile and can be used in many ways including straight through decisioning, triage and input to a carrier’s workflow either to take a case down a certain underwriting path or as input to a predictive model. A carrier can have a multi-line distribution and/or traditional life-focused agent-driven business with various products and underwriting rules represented in Velogica.
How many applications have been underwritten by Velogica?
Since inception, about 3.8 million
How can automated underwriting be expanded to higher face amounts with rates closer to fully underwritten?
We’re focusing on two approaches. One is to add new data sources that can provide protective value with no degradation in the speed of the decision. The other is to get smarter about when “slow evidence” is really needed. We need to identify where time and money are being spent on traditional requirements that add no – or minimal – protective value when compared to instant data sources.