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The rise of automated decision-making systems has been extraordinary in the last few years, both in terms of scale and scope of operation. This is especially true in the field of fintech, where robo financial advisors have gained prominence with their claim to "democratise" finance, with their low operating costs, multi-tasking abilities and potential for mass adoption. This series of three research papers is focused on demystifying algorithmic explainability in the field of fintech, by diving deep into both theoretical and practical aspects of the phenomenon, and contextualising the discussion to India. The first paper explores the trade-off that emerges between performance and explainability for robo financial advisors, through a detailed review of available literature that allowed comparisons between relevant processes adopted around the world, and interviews with various stakeholders within India to understand the evolving domestic situation. The paper finds that it is not quite a question of if ADS will play a significant role in India's financial services sector but more a question of when that will happen. The second paper operationalises algorithmic explainability in the particular context of risk profiling done by robo financial advisory applications. Here, an approach towards developing a 'RegTech' tool is outlined, which can explain the robo advisor's decision-making, using machine learning models to recognise and reconstruct different levels of explanations. Finally, the third paper evaluates the effectiveness of user-centric explanations in conveying the decision-making logic of complex algorithmic systems in fintech. The paper demonstrates the usefulness of such explanations from the perspectives of both novice and seasoned investors, and goes on to differentiate between white- and black-box explanations. In sum, this three-paper series, using a range of tools and approaches, examines in detail the under-appreciated regulatory and operational challenges that emerge during the use of algorithms in the field of fintech, and explores ways to resolve them. While the first paper looks at the present and future of AI in Indian fintech, the second paper develops a tool to explain a robo advisor's decisionmaking, and the third finds factors that determine users' comprehension and confidence in such systems. The results of these three approaches in the three papers become vital when seen in the context of the rapid rise of artificial intelligence across products, services and industries globally. If humans are to work alongside machines in this changing world, explainability becomes an important aspect to consider for companies, regulators and users alike, in order for humans to trust the algorithmic systems in place and improve outcomes — in this case, financial outcomes — for all.

We examine government decisions to support troubled banks. Our contribution is the examination of how federalism can affect decisions to classify banks as systemically important. Whether a bank is viewed by politicians as 'systemically important' varies based on how its failure would affect supporters of the government. How a federation is designed has a strong influence on which banks are given public assistance. Where the top level of government is solely responsible for banks, there will be fewer systemically important institutions and so more banks will be allowed to fail. Where lower levels are responsible, governments will allow fewer failures. We use this approach to understand government support for failing banks in Germany. Our findings are relevant for the European Banking Union. Adapted from the source document.

We examine government decisions to support troubled banks. Our contribution is the examination of how federalism can affect decisions to classify banks as systemically important. Whether a bank is viewed by politicians as 'systemically important' varies based on how its failure would affect supporters of the government. How a federation is designed has a strong influence on which banks are given public assistance. Where the top level of government is solely responsible for banks, there will be fewer systemically important institutions and so more banks will be allowed to fail. Where lower levels are responsible, governments will allow fewer failures. We use this approach to understand government support for failing banks in Germany. Our findings are relevant for the European Banking Union.