DECSYS

Key expertise from UoN

Explainable Artificial Intelligence, Uncertainty Quantification in Machine Learning Systems, Qualitative-Quantitative Uncertainty Integration to Machine Learning Systems, Compositional Data Analysis

Challenge area within FinTech we are trying to tackle

The primary challenge we are addressing is the issue of uncertainty in decision-making procedures within the FinTech industry. Many FinTech companies may face difficulties when they need to make critical decisions based on data that inherently includes a level of uncertainty. This could involve credit risk assessment, user feedback integration, or investment strategy formulation where the underlying data can be ambiguous or incomplete. Our focus is on enabling these companies to manage and interpret uncertain data effectively so they can make more informed decisions.

Solution and vision for the end product and concept

Our vision is to develop a software solution designed specifically for the FinTech sector. This software will be capable of collecting both data and the associated uncertainty related to that data. The unique aspect of our solution lies in its ability to process these dual layers of information—actual data points and their uncertainty margins—to deliver tailored, precise outcomes. 

The end product will enable FinTech companies to integrate this enhanced decision-making tool into their existing systems. By doing so, they can improve the accuracy of their decisions, reduce risks associated with uncertainty, and optimise their strategies based on more reliable insights. Ultimately, our software aims to transform how FinTech companies handle uncertainty, turning potential vulnerabilities into strengths in their decision-making frameworks.

This approach not only helps in tactical day-to-day decision-making but also supports strategic planning and long-term business resilience in a sector that is continuously evolving and facing new challenges.