The adoption of AI/ML in financial services is increasing as companies seek to drive more robust, data-driven decision processes as part of their digital transformation journey. For global banking, McKinsey estimates that AI technologies could potentially deliver up to $1 trillion of additional value each year. But productionising machine learning at scale is challenging.

In the last few years, fintech enterprises have disrupted the financial services and banking industry by taking everything computing technology offers – from machine learning to blockchain – and turning it up a notch. Traditional financial institutions must now compete with challenger banks offering electronic payment alternatives, peer-to-peer lending, and investment apps.

It is no surprise that cybercriminals are after the money, and banks have plenty lying around. They also have gobs of data, making banks irresistible to hackers who have a field day attacking complex banking IT systems flush with more connections than a movie agent. Here are a few recent facts to know.

Financial Institutions (FIs) need to respond with agility and business velocity to keep pace with changing economic conditions. Yet, emerging competition from fintechs and challenger banks and increasing customer expectations is making this task difficult, especially as regulatory and compliance requirements increase. Embracing the next phase of digital transformation is an imperative for financial institutions to sustain and grow in a competitive environment of rising cost pressures.