AI is quietly transforming the financial sector, and you haven't noticed yet.

Financial institutions possess an overwhelming amount of data, but this data is like a gold mine—without the right tools, it's all for nothing. Until AI came along.

Why Is Big Data So Difficult to Use

IBM's definition of “big data” is very simple: large volume, high speed, diverse types. Imagine smart wearable devices collecting your heart rate, step count, search history in real-time 24 hours a day… A single researcher simply cannot process this information quickly. But AI can.

The Three Major Skills of AI in the Financial Sector

According to UBS data, 75% of banks managing assets over $100 billion are using AI. How exactly are they using it?

1. Anti-fraud: Real-time comparison of customer transaction habits vs. abnormal behavior, which saves banks a substantial amount of money each year.

2. Precision Marketing: AI can analyze your consumption data and automatically determine which products are suitable for you. The Royal Bank of Scotland uses AI to tailor home purchase plans for clients, increasing efficiency by N times.

3. Back-end Operations: Employee process automation, error detection, talent assessment… can all be accomplished with AI. ING ( of the Netherlands has built a hybrid cloud environment, allowing employees to access relevant data anywhere to make decisions.

Where are the bigger opportunities?

IBM research found that at the beginning of the pandemic, 84% of companies planned to increase their investment in AI. This means that platform providers like IBM, Amazon Web Services, and Google Cloud will become the big winners.

Financial AI is just getting started, the real revolution has yet to come.