IT failures are more common than we think.
Most companies make a run at conceal their failures and pretend there is nothing wrong.
Ultimately, the clients suffer.
For banks and financial institutions, such problems are particularly unsettling.
IT disruptions lock costumers out of their accounts, disabling them from paying for food, rent or petrol.
Still, the number of IT failures is on the rise.
The new functions are written by different teams in different programming languages, which add to the complexity.
As a result, few people fully understand the entire system.
Barclays, which had the highest number of incidents, reported 41 cases in 9 months.
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But financial institutions are reluctant to upgrading their systems.
Not only would this be a costly option, but it also carries a great risk.
For that reason, were witnessing a deadlock.
Is there a safe way to prevent current IT failures without choosing between bad or worse?
No one can anticipate them, so no one knows how many resources should be allocated to prevent them.
Banks used to run in batch mode in the middle of the night.
As such, any problems were cleared before the working day would start.
But the current load causes systems to go wrong during the day, and the mediaquickly spreads the word.
Having versatile IT teams that can quickly address and resolve problems have long been the standard method.
Artificial Intelligence, however, offers a different path.
Artificial Intelligence programs are software that are self-programmed.
This is what makes AI seemingly intelligent and has enabled it to outperform humans on several occasions.
In simple terms, since AI relies on big data, it can form a dynamic baseline.
A high CPU use, for instance, might be normal behavior when there are many online users.
Simultaneously, a much smaller load can prove to be unusual if there are no users on the system.
The dynamic baseline model has several advantages.
On the other hand, it can warn about and prevent issues before they turn into problems.
The system can self-heal.
Using AI in this context offers several advantages, especially on complex networks.
Until the actual problem is detected, much unnecessary cost is imposed on the business.
We do have old problems in the financial industry.
But perhaps new solutions can solve them.
