How is machine learning transforming financial services?
Standing still is the same as falling behind in today’s fast-changing financial services industry. At the heart of the transformation are new analytics techniques that help companies understand consumers more deeply than ever before: artificial intelligence and, in particular, machine learning. Seventy-nine percent of financial institutions globally believe artificial intelligence will transform not only the way they interact with their clients, but also how they collect, process and use their information.¹
What is machine learning and how can financial institutions use it?
In simple terms, machine learning is the ability of a machine to learn from data, without being explicitly programmed to do so. The algorithms derived from machine learning help find efficiencies in banks' internal processes, especially in areas such as portfolio segmentation, process improvements, and line of credit optimization. For example, machine learning can help banks:
- Identify patterns of suspicious activity and proactively spot it
- Identify high-risk transactions before they are authorized, and prevent fraud attempts
- Identify sudden changes in consumer purchasing behavior
- Minimize human error by automating highly repetitive activities
- Design more convenient offers and service channels for consumers
- Generate revenue with prediction models
However, identifying viable machine learning projects is a challenge for most organizations. To help banks take advantage of the opportunities that machine learning presents, Visa Consulting & Analytics (VCA) has developed new solutions to improve their portfolio profitability and performance.