Machine Learning (ML) models are being increasingly employed for credit risk evaluation, with their effectiveness largely hinging on the quality of the input data. In this paper we investigate the impact of several data quality issues, including missing values, noisy attributes, outliers, and label errors, on the predictive accuracy of the machine learning model used in credit risk assessment. Utilizing an open-source dataset, we introduce controlled data corruption using the Pucktrick library to assess the robustness of 10 frequently used models like Random Forest, SVM, and Logistic Regression and so on. Our experiments show significant differences in model robustness based on the nature and severity of the data degradation. Moreover, the proposed methodology and accompanying tools offer practical support for practitioners seeking to enhance data pipeline robustness, and provide researchers with a flexible framework for further experimentation in data-centric AI contexts.

By 2022, the AI in FinTech market will be worth $7.25 billion. Artificial Intelligence (AI) is driving a new wave in FinTech. From banks to financial institutions, everyone is using it. AI for FinTech enables companies to process customer data at a faster pace. As a result, it helps to achieve maximum product personalization.

The Institute of International Finance (IIF) is one of the world's largest global associations of financial institutions with about 400 member firms in more than 75 countries. We serve as a forum for exchanging views and developing proposals on global financial issues; we advocate for regulatory, financial, and economic policies that are in the broad interests of our members and foster global financial stability and sustainable economic growth; and we provide our members with an independent source of economic and financial research. The Institute's Digital Finance team helps the financial services industry and the public sector understand technology-driven trends reshaping the industry, such as the implications of BigTech firms, the rise of digital assets (including CBDCs), artificial intelligence (AI) and machine learning (ML), increased automation, and cross-border connectivity. The team is also leading the effort to leverage the use of new technologies to meet regulatory and compliance challenges. Some of the key areas that the team is focusing on currently include cloud adoption and technology partnerships, the regulation of tech firms, the implications of digital currencies, the emergence of decentralized finance (DeFi), international digital economic cooperation, the ethical use of data including topics such as transparency, controls and governance, commercial opportunities surrounding digital identity, and cyber intrusion.

Through the increased availability of data and online connectivity through novel interfaces & APIs, we are faced with more opportunities than ever before. For instance, today, you can use many services to get data on purchases you'd like to make and suggestions on when the optimal time to make the purchase would be (e.g. However, soon, this operation may seem antiquated as artificial intelligence (AI) and assisting algorithms have become more prevalent and can make these decisions in your place. In imagining a future like this, will the balance of power shift toward the data owner and end-purchaser or will tool manufacturers and conduits be able to gain an upper hand? With consumer preferences for regained privacy and control, as well as new regulation such as the General Data Protection Regulation (GDPR), it's plausible to see more data held by the consumer and the consumer exercise more control over where their data is used.

What a year it has been. On many fronts, it has been a fantastic year of firsts and non-stop travel. We launched our first market innovation report to lay out the opportunities for innovating for the older adults, a population that financial services startups and entrepreneurs largely ignore. We hosted our first fintech demo day where we convened entrepreneurs, thought leaders, venture capitalists, and consumers. I am particularly proud of the diversity of our founders, whom I believe represent the melting pot nature of the America that we live in today.

This opens the door for a new generation of millennial talent - who have come to expect technology to pave the way for their career paths in a way yet to be seen. "Most CFOs today began their journey to the top spot in lower level management accounting or analyst roles. Having these roles replaced by machines will have a dramatic impact to career paths and the way we think about the various jobs in finance," commented Klimas. We have already started to see this focus be realized, with three of the top 10 companies slated to hire the most 2016 college graduates according to LinkedIn Research falling into the accounting and consulting space.