The emergence of Open Banking represents a significant shift in financial data management, influencing financial institutions' market dynamics and marketing strategies. This increased competition creates opportunities and challenges, as institutions manage data inflow to improve products and services while mitigating data outflow that could aid competitors. This study introduces a framework to predict customers' propensity to share data via Open Banking and interprets this behavior through Explanatory Model Analysis (EMA). Using data from a large Brazilian financial institution with approximately 3.2 million customers, a hybrid data balancing strategy incorporating ADASYN and NEARMISS techniques was employed to address the infrequency of data sharing and enhance the training of XGBoost models. These models accurately predicted customer data sharing, achieving 91.39% accuracy for inflow and 91.53% for outflow. The EMA phase combined the Shapley Additive Explanations (SHAP) method with the Classification and Regression Tree (CART) technique, revealing the most influential features on customer decisions. Key features included the number of transactions and purchases in mobile channels, interactions within these channels, and credit-related features, particularly credit card usage across the national banking system. These results highlight the critical role of mobile engagement and credit in driving customer data-sharing behaviors, providing financial institutions with strategic insights to enhance competitiveness and innovation in the Open Banking environment.

This research article analyses and demonstrates the hidden implications for fairness of seemingly neutral data coupled with powerful technology, such as machine learning (ML), using Open Banking as an example. Open Banking has ignited a revolution in financial services, opening new opportunities for customer acquisition, management, retention, and risk assessment. However, the granularity of transaction data holds potential for harm where unnoticed proxies for sensitive and prohibited characteristics may lead to indirect discrimination. Against this backdrop, we investigate the dimensions of financial vulnerability (FV), a global concern resulting from COVID-19 and rising inflation. Specifically, we look to understand the behavioral elements leading up to FV and its impact on at-risk, disadvantaged groups through the lens of fair interpretation. Using a unique dataset from a UK FinTech lender, we demonstrate the power of fine-grained transaction data while simultaneously cautioning its safe usage. Three ML classifiers are compared in predicting the likelihood of FV, and groups exhibiting different magnitudes and forms of FV are identified via clustering to highlight the effects of feature combination. Our results indicate that engineered features of financial behavior can be predictive of omitted personal information, particularly sensitive or protected characteristics, shedding light on the hidden dangers of Open Banking data. We discuss the implications and conclude fairness via unawareness is ineffective in this new technological environment.

The status quo in retail banking is tottering. This has forced banks and credit unions to modify their business models, re-prioritize investments, change products and services offered and ramp up innovation efforts. There has also been a rethinking of distribution options, with digital channels significantly increasing in importance. These shifts are reflected in the sixth iteration of a study of the future of retail banking conducted by The Economist Intelligence Unit, on behalf of Temenos. Until recently, the changes in consumer behavior were believed to be the primary impetus for changes in retail banking strategies.

Innovations within FinTech are causing major changes to the dynamic between clients and wealth management providers. With technology as a driving force behind industry changes, understanding how client perspectives are shifting is crucial. For the wealth management sector, there are three key innovations that institutions need to be paying close attention to. These are artificial intelligence, open banking, and agile distribution. Understanding these will be the foundation for meeting new customer demands in the coming years.

The rise of technology and digital services has led to increasing customer demands for simplicity and speed. Banks and financial services institutions are continuously searching for new ways to retain and attract customers while aiming to respond to heightened consumer demand for personalized services. For this reason, customer-centric offerings continue to dominate the financial technology (FinTech) landscape. Personalization takes advantage of real-time data and cutting-edge technologies to deliver product or service information to customers. In an extremely competitive financial services sector, there is more pressure than ever for FinTech companies to provide customers with a better experience.

As part of the partnership, Fabrick's unique offering will become part of the Microsoft Commercial Marketplace, Microsoft's financial ecosystem that already includes more than 17,000 globally certified apps and services. This collaboration will enable Fabrick to strengthen its presence in the corporate market, both domestically and internationally, allowing for multiple companies across Europe to benefit from the new Open Banking and Open Payment solutions. The agreement will see Fabrick collaborate with Microsoft Italia to further enhance its approach to financial sector innovation, based on the ability to openly integrate third-party services for the rapid development of digital, personalised and affordable products and services. These services will centre around the needs of advanced end users and capitalise on the flexibility, scalability and security of the Microsoft Azure cloud platform, as well as the most advanced features of Artificial Intelligence and Integrated Data Analysis. The Personal Finance Management solution is already available and enables end customers to view and manage their money whether it is in a different bank or bank accounts all from a single app, providing a complete and real-time view of their resources, in line with PSD2 regulations.

The UK government's 2019 Fintech State of the Nation report identified a raft of areas in which artificial intelligence (AI) could have an impact on the financial services sector, ranging from delivering customer support through to underwriting loans and providing real-time fraud and risk management. These developments are underpinned by "machine learning", which allows computer programs to teach themselves by examining data. AI is a topic already being explored by many financial service providers, with 56 per cent believing it will reshape the sector, according to a survey from a "Big Four" accountancy firm. The poll found many companies plan to use AI to deliver automated advice to clients – having a "bot" deliver information online could cut costs which could be passed on to customers through lower fees. Banks using AI could examine data about young people's spending habits and enable them to qualify for personal loans or mortgages even if they have a short credit history, while start-up Financial services is highly-regulated and the use of AI can cut the cost of compliance dramatically.

Thanks to open banking, fintech early adopters likely already have accounts that round up transactions to boost savings or connect to third-party tools for loan applications, budget management and more. But the new wave of fintech startups are proving there's much more that can be done using open banking, the two-year-old mandate from UK regulators that required banks to easily allow their customers to share their data with third parties such as apps. "Open banking offers people the chance to get personalised, tailored support to help them manage their money by allowing regulated companies to securely analyse their bank data," says Lubaina Manji, senior programme manager at Nesta Challenges, one of the organisations behind the Open Up 2020 Challenge, alongside the Open Banking Implementation Entity (OBIE). "It's enabled the creation of new services and tools to help people with every aspect of money management – from budgeting to investing, and much, much more, all in a safe and secure way." And some of the innovations from finalists in the Open Up 2020 Challenge have surprised with their ingenuity and customer focus, she says, citing Sustainably's round-up tool for automated charity donations, and Kalgera's neuroscience-informed AI to help spot fraud targeting people with dementia – two projects that highlight the purpose-driven idea behind open banking and the aim to get financial support to show who need it the most.

'Tis the season to be knowledgeable! With almost 40 years in the industry, the collective payments expertise of the Ingenico team is unparalleled. In 2019, Authorised Push Payment Fraud (APP Fraud) rose by 40%, costing the UK £616 million. Thanks to PSD2 and Open Banking, we will continue to see more new players in fintech. This is brilliant, but it means fraudsters will inevitably innovate their techniques, too.

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