The AI-ML Technology Twin Upgrading the Banking Services
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The AI-ML Technology Twin Upgrading the Banking Services

By CIOReview | Thursday, June 13, 2019

FREMONT, CA: The banking institutions are at the dawn of technological transformation. Tech advancements have opened a scope to improve numerous aspects of their services and functioning. Although a vast number of inter-related technologies have played essential roles in driving the transformation of the banking industry, Artificial Intelligence (AI) and Machine Learning (ML) have been playing the most significant parts. In the latest survey, 32 percent of financial institutions have said that they have adopted AI-based solutions already. The banking areas which stand a chance to make the most of these developments are discussed in this article.

• Better Assessment of Borrowers

The credit facilities in banks are now substantially better. It has become easier for the banks to assess a potential borrower with much more speed and accuracy by utilizing AI. AI promptly checks whether or not an individual is safe for credit by evaluating records and unearthing risks from available data.

• Fraud Prevention

Financial institutions are perpetually under the threat of frauds. AI and ML together can prove to be the perfect solution for banks looking to mitigate scams. AI and ML driven tools can constantly monitor transactions and decode patterns from the data that has been analyzed, helping banks to flag suspicious transactions in real-time.

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• Better Services and Personalized Approach with Automated Tasks

Repetitive tasks can now be automated, and employees are free to work at better things. Customer services win big time as AI and ML handle the communications systems and run customer care round the clock with sufficient expertise. It also becomes convenient for banks to provide customer-centric and personalized services to consumers.

• Mitigating Security Risks

Analyzing transactions and credits has never been simpler. The twin technologies have features that allow banks to successfully predict risks based on several factors, including the history of threats. Algorithms can point out loopholes in the system with much more accuracy and speed than their human counterparts.

Increasing competition and enhanced customer expectations have made it essential for banks to overcome challenges and adopt AI and ML. The technologies are incredibly favourable for both banks and their customers.

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