The banking and financial services industry has been leveraging the latest technologies to improve customer experiences and streamline their workflows. A combination of technologies such as artificial intelligence (AI), natural language processing (NLP), and robotic process automation (RPA) is helping the industry move forward in this direction. In this article, we will explore how these technologies are enhancing debt collection
As we move towards a more digitally enabled world, it’s not just the way we communicate or gather information that’s changing; the way we pay for goods and services is also evolving. Digital payments have become the new norm, replacing traditional methods such as cash or card payments. They offer a faster, more convenient, and secure way to manage transactions.
Matching businesses with the right partners is becoming increasingly difficult in today’s crowded market. Technology can help, but it can also be overwhelming. Finnovating, a Madrid-based startup, has developed its own Generative Pre-Trained Transformer called MatchGPT, to make B2B matchmaking simpler and more effective. Background on Finnovating and Its B2B Matching Platform Finnovating began as a B2B matching platform that
Advancements in technology have brought about the use of artificial intelligence (AI) in various industries, including banking. One of its most notable applications is the use of AI-powered chatbots to engage with customers. While chatbots can provide convenience and efficiency, they also come with challenges. In recent years, the Consumer Financial Protection Bureau (CFPB) has been monitoring the increasing use
The Consumer Financial Protection Bureau (CFPB) has been monitoring banks’ increasing use of AI-powered chatbots amid a surge of complaints from frustrated customers. While chatbots can offer a fast and efficient way for financial institutions to interact with customers, they can also lead to customer frustration, reduced trust, and even violations of the law. In this article, we will explore
Artificial Intelligence (AI) has become a game-changer for the financial services industry. With the advent of big data, fintech companies can now leverage AI to analyze vast amounts of financial data and provide insights, recommendations, and forecasts to customers. Moreover, AI tools are also improving risk management practices and facilitating financial inclusivity by providing credit opportunities to previously underserved individuals.
Fusion Risk Management, a leading provider of software solutions for business continuity, risk management, IT disaster recovery, and crisis management, has announced an expanded functionality of its third-party risk management (TPRM) offering. The enhanced solution delivers continuous monitoring of third parties beyond its traditional scope, as well as an evaluation of potential operational and business impacts that those third parties
Xaindex, a crypto liquidity platform focused on researching and applying neural networks and artificial intelligence algorithms in high-frequency trading and investments, has launched a new synthetic intelligence (SI) to provide advanced liquidity management for cryptocurrencies. Xaindex’s advanced model of the algorithmic stablecoin, or Synthetic Utility Token (SUT), is based on these developments in the field of neural networks. The innovative
Swan, a fintech startup based in France, has achieved a significant milestone by open-sourcing its no-code banking interfaces. This move has reduced the time to market of new pilots by as much as 75%. Swan is dedicated to opening up opportunities for any type of business to embed financial features into their offering, without extensive development efforts. Overview of Swan’s
Financial institutions are required by law to comply with Anti-Money Laundering (AML) regulations in order to prevent illicit financial activities, such as fraud, terrorist financing, and money laundering. However, achieving AML compliance is a challenging task that requires significant human and financial resources. Financial institutions face several challenges, including the difficulty of identifying suspicious transactions, the high cost of compliance,
As financial services companies aim to increase lending volumes and reduce loan processing times, the need for automation tools has never been more pressing. Automation can help companies scale quickly, reduce costs, and improve accuracy. However, automating document processing has been challenging due to the wide range of document types and formats, as well as the complexity of the information
The financial technology (FinTech) industry has undergone a revolutionary change in the past decade, aided by technological advancements that have paved the way for new products and services. Artificial Intelligence (AI) has undoubtedly played a crucial role in determining the direction of the industry. As we move towards 2023, the role of AI in FinTech is expected to grow significantly,
