In today’s data-driven business environment, the finance team plays a critical role in transforming raw data into actionable insights that inform strategic decision-making. However, the prevalence of disconnected data sources, often referred to as data silos, creates significant bottlenecks that hinder your team’s ability to operate efficiently and generate reliable financial information.

While our discussions have previously highlighted the unique analytics challenges and opportunities within industries such as automotive, healthcare, and kids' gaming, today, we turn our focus to the finance sector. In this article, we’ll zoom in on analytics challenges in the finance world, and we’ll answer why Countly is exceptionally suited for product analytics in the financial sector.

In 2023 and beyond, leveraging digital banking transformation will continue to be a prominent. How? Well, technology, like its influence on other emerging markets, is gradually transforming the field of financial services in every manner. However, the sector has a long road ahead, as banks are still experimenting digitally. Meanwhile, consumer behavior and demands have also evolved to a great extent.

What is kpi in business? A CFO Key Performance Indicator (KPI) or metric is a quantifiable high level measure of financial performance. These KPIs can be considered a specific subset of financial KPIs, used to help a CFO make informed decisions that steer their company in the right direction. These performance metrics can also be used to measure a company’s financial performance relative to competitors in the same industry.

Last year, we held our first Accelerate event, to explore industry trends, data and technology innovations, and data strategy case studies in financial services. This year, we are expanding to five industry events, featuring leaders in financial services; retail and consumer goods; manufacturing; media, advertising and entertainment; and healthcare and life sciences. Accelerate Financial Services and Accelerate Retail are one-day virtual events brought to you by Microsoft.

It’s no surprise that ever since ChatGPT’s broader predictive capabilities were made available to the public in November 2022, the sprawl of stakeholder capitalization on large language models (LLMs) has permeated nearly every sector of modern industry, accompanied or exacerbated by collective fascination. Financial services is no exception. But what might this transformation look like, from practical applications to potential risks?

Financial services companies are leveraging data and machine learning to mitigate risks like fraud and cyber threats and to provide a modern customer experience. By following these measures, they are able to comply with regulations, optimize their trading and answer their customers’ needs. In today’s competitive digital world, these changes are essential for ensuring their relevance and efficiency.

For the banking and financial services industry, artificial intelligence (AI) isn't just a new tech trend. It's a powerful tool that will have a wide range of impacts, from risk management to operational efficiency and customer experience. According to Deloitte, the world’s top 14 investment banks could potentially boost their front-office productivity by 27% to 35% by leveraging generative AI.

The world has really come a long way due to widespread digital transformation adoption! And, it’s no secret that it has changed the FinTech sector drastically. In light of this evolution, it has become imperative for lenders to adapt and refine their operations with a well-defined Loan Management System.

For business and IT leaders, digital transformation in the financial services industry continues to pose a challenge but is necessary to keep pace with changing regulatory requirements, consumer demand, and budget constraints. It's also important to prevent operational areas from growing their expenses unintentionally. In the typical boom and bust cycle, banks can feel pressure to roll out new financial products, services, and business lines.