Detect Financial Crime & Fraud and Act Against Them Before They Occur

Industry Insights Technology

FinTech breakthroughs, while they facilitate online financial transactions, are indicating an upsurge in the adoption of next-generation technologies, including Artificial Intelligence, Data Science, and Machine Learning, to fight financial crime and frauds. This is laying the groundwork for innovations in the financial risk management landscape, creating immense sales potential for financial crime and fraud management solutions in today’s finance industry.

Financial institutions, including banks, have always been reeling under the pressure of regulations and security concerns. However, in the Information Age, sophisticated fraudsters have found new ways of attacking banking systems with technologically-advanced tools. Financial institutions, today, are under tremendous pressure to accelerate digital transformation and combat financial crimes and frauds, and meet customer demand for immediacy and personalized experience.

Rise in losses due to fraud payments and unauthorized access to public financial accounts has led the governments of many nations to establish strict rules and regulations to prevent financial fraud and financial crime.

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As the introduction to digital banking services has created opportunities for fraudsters to digitally attack the finance industry, the demand for more efficient solutions for managing financial frauds and crimes has surged significantly in the past few years.

As the customer is at the forefront of banks’ business policies, increasing concerns of customers about secure banking, especially with mobile or Internet banking, are triggering banks to adopt robust fraud detection and prevention solutions.

Market players are more inclined towards implementing Robotics Process Automation (RPA) techniques to replace time-consuming and expensive processes in the traditional fraud detection and prevention fundamentals of the finance industry. With the increasing prevalence of machine learning, Artificial Neural Networks (ANN), and Natural Language Processing (NPL), RPA is expected to reach its renaissance in the financial crime and fraud management solutions.

The emergence of advanced technologies is not only reshaping the finance industry but is also making it vulnerable to severe financial threats such as identity theft, cyber stalling, card skimming, and phishing. In addition, the younger generation of investors is showing proclivity for digital or cashless transactions, and this is pressing financial institutions even more to arm themselves with efficient financial crime and fraud management solutions.

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