Using data in real time

Insurance company underwriting today is relatively old-fashioned in an age of machine learning and AI. Many insurance companies still use a “lookback” approach to underwriting and pricing. They look at financial results from the previous year to price policies for the next year. In many cases, regulations prevent insurance companies from adjusting premium rates according to market realities; so even when an insurance company adopts the latest underwriting technologies, they can’t do much with it.

Takadao’s mission is to provide the global underinsured with access to fair and transparent insurance alternatives. From an insurance perspective, a global fund is highly diversified and will benefit from lower overall risk. However, the downside to a global fund is that it hasn’t been done before and hence there isn’t enough historical data to underwrite and predict the risk to a high confidence level.

To address this, Takadao’s underwriting technology amalgamates data from multiple sources in its underwriting algorithm and uses machine learning to adjust and balance contributions, reserves and payouts in real-time. As the tDAOs grow, each tDAO will have more and more data that is fed into Takadao’s underwriting algorithms which strengthens long-term risk management and fund solvency.