TAGDit Data as a Service tool is ideal for use in fintech. It is built-in AI and data analytics that apply novel 6-dimensional (6D) mathematics to achieve new levels of predictivity and has been awarded one US patent and another pending. TAGDit 6D data transformations may complex 4D (x,y,z,t) problems into a 6D space (x,y,z, t1,t2,t3) where new conservation laws result in simplified mathematics. Solutions from calculations performed in 6D space are mapped back to 4D space for interpretation. This results in an improved Black Scholes algorithm that lowers risk, increases predictive power for pricing exotic, beyond Bermudan style options, plus analytic results for the first time, and Feynman diagram methods to calculate series expansions of very discontinuous jump stochastic, risky multiple correlated volatility stock markets with variable arbitrage. Having three-time dimensions projected down to our one leads to all methods of previous advanced predictive power, but goes beyond that as gauge field theory dualities are also known, leading to critical phenomena and new econophysics.

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Converts intangibles to tangibles.

Quadratic voting is a good way to quantify trust. TAGDit can be used to quantify the direction, weight, and duration of the trust. The goal of quantifying trust is to turn it into a measurable variable and a real asset that can impact the bottom line in accounting practices. For this to happen, the intangible value needs to be firmly placed in the world of measurement and ubiquitously accepted. The Social Capital Quality Vector that emerges from 6D data transformations quantifies trust and its flow in social networks. Applying specific weight, and 6D mathematic algorithms to each transferred vote can reveal group trust patterns. This specific metric emerges from deep research into biology, sociology, and physics and can provide an enhanced foundation for fundamental accounting practices.