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Banking automation has become a key driver of efficiency and innovation in the financial services industry. As the banking sector strives to meet the demands of customers while managing costs, they’re turning to technology to streamline operations. But what exactly is banking automation, and how does it work? Let’s break it down. Banking automation refers to the use of technology by financial institutions to perform tasks that would traditionally require human intervention.

Financial services organisations are constantly pressured to streamline operations while maintaining stringent security and compliance standards. As back-office processes become more complex, a flexible, scalable, and automated integration platform becomes essential. Linx addresses these challenges by providing an advanced platform that delivers highly customisable solutions tailored to each organisation’s needs.

In the world of banking, challenges abound. Fragmented processes and add-on technologies that don’t integrate well with legacy equipment pose issues for financial institutions already struggling with ever-increasing regulatory compliance requirements and customer expectations. Banks have invested heavily in anti-money laundering (AML) solutions to keep up with heightened risks and remain competitive.

Financial planning and analysis (FP&A) is recognized as an essential tool for driving business success. At a time when agility has taken center stage, though, FP&A is giving way to the new discipline of extended planning and analysis (xP&A). Why? Because in an increasingly digital landscape where agility is paramount, actionable real-time feedback is essential.

Historically, finance teams largely operated in the background, focusing on record-keeping, compliance, and ensuring that financial operations ran smoothly. Their primary responsibilities revolved around managing costs, balancing the books, and maintaining operational efficiency. In recent years, that has changed.

A prominent global bank was thrust into the spotlight for all the wrong reasons. The institution was hit with a staggering fine – multiple billions – for failing to comply with new data protection regulations that ultimately led to a customer data breach. The breach, which exposed sensitive information, not only resulted in financial penalties but also caused significant reputational damage.

In the finance industry, data is the lifeblood that powers everything from daily operations to strategic decision-making. Financial institutions manage vast amounts of data, ranging from transaction records and market feeds to customer information and regulatory reports. Efficiently processing and analyzing this data is crucial for maintaining competitiveness and compliance in a fast-paced, highly regulated environment.

The Markets in Financial Instruments Directive II (MiFID II) came into effect in January 2018, aiming to improve the competitiveness and transparency of European financial markets. As part of this, financial institutions are obligated to report details of trades and transactions (both equity and non-equity) to regulators within certain time limits.

From traditional brick-and-mortar establishments to sophisticated online platforms, the banking and fintech landscape has drastically evolved. Today, customers expect flawless digital experiences. Any flaw in the experience can cost you their trust, loyalty, and business. Digital banking offers the convenience and accessibility that your customers crave. However, with this transformation comes an increased risk of security breaches, operational failures, and user dissatisfaction.

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission-critical, large-scale data analytics and AI use cases—including enterprise data warehouses. Nearly two years ago, Cloudera announced the general availability of Apache Iceberg in the Cloudera platform, which helps users avoid vendor lock-in and implement an open lakehouse. With an open data lakehouse powered by Apache Iceberg, businesses can better tap into the power of analytics and AI.