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Last month, the Singapore bank DBS experienced a 10-hour outage of its digital services. Not only was it massively disruptive to customers, but it caused the bank’s stock to lose 1.4% of its value in a single day. And it’s not the first time DBS has had to deal with the fallout of an IT snafu; in November 2021, Singapore’s finance regulatory body imposed significant additional capital requirements on the bank after its digital banking services were disrupted for two days.

Maintaining trust in the business services your customers rely on is everything. With ever-increasing customer expectations and the promise of ‘always-on’ services, poor digital experiences and outages can cause significant harm to your business. The Interlink Software AIOps and Observability platform strengthens IT teams’ capability to deliver more reliable, available digital services and reduce the risk of customer impacting disruption.

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.