The use of data science to enable customer solutions, risk and regulation generates potential for massive value creation. So naturally we are seeing many AI initiatives in the financial sector. For instance, improving customer experience or better risk management to increase both revenues and profitability.
But many financials are struggling with the question: how can we unleash the full benefits while we face data quality and governance issues and lack a common language? Through our combination of sector knowledge and data-science expertise we are well positioned to advise you on how to capture the value of AI.
Let’s discuss the possibilities.
The data strategy is aligned with the business strategy to capture the most value. The challenge is to consider all impact areas including change (organisational impact, regulation, processes), technology/IT and data/model. Our deep sector knowledge allows us to identify key impact areas and anticipate potential pitfalls. Together with experts on data engineering and data science we design the strategic roadmap.
In end-to-end solution design the challenge is to align all the different elements in the process. We can deliver customised solutions for elements like governance, building data pipelines, model development and model design. Our expertise in data science, data engineering and data visualisation ensures that the solutions we deliver create value for the process.
We believe in knowledge sharing via workshops. We first share the current state of new technologies and how they can be applied. In break-out sessions we determine suitable business cases for these new technologies. Using the design-thinking model, we then start to develop the first minimal viable product.