BANKING TIPS : Artificial intelligence impact in banking

By Kelvin Mkwawa

Artificial intelligence (AI) is creating the single biggest technology revolution the world has ever seen. AI is a field of computer science that consists of the construction of intelligent machines.

The purpose of these intelligent machines is to replace human intelligence to a certain extent. Across all industries, AI is being used to address a wide range of challenges by making interactions between the machines and systems simpler and smarter.

There are huge amounts of data being generated in the banking industry which need to be analyzed and AI can easily examine that data and provide outcomes which can be used to create more opportunities for the banks and its customers as well. However, the penetration of AI in the banking industry is somewhat limited to date because of distinct databases and the risk of confidential data. In addition, it takes time for the banking industry to adopt AI technology compared to other industries because of the dependency on human involvement.

Nonetheless, as advanced technology becomes more available in our daily lives, more tech-savvy customers, exposed to advanced technologies in their day-to-day lives, expect banks to deliver seamless experiences which enable them to access most of the banking services at their fingertips, anytime, anywhere. To meet these expectations, the majority of banks now are shifting more into offering digital services which have resulted in an increase in online transactions.

And this is where AI can play a significant role in ensuring the digitization of the products and services in the banking industry. AI has an immense potential for the banking sector and can have an influence on many different aspects. It brings automation and simplifies processes, speeding up the response time, keeping humans apprised of latest regulatory changes, and saving time by preparing reports faster. In this article, I will share how AI can impact the banking industry:

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• Fraud detection and anti-money-laundering – Avoiding fraud and money laundering activities is a challenge for many banks. AI has the potential to help the banks become more efficient in the process of detecting fraud and money laundering activities. Currently, banks are struggling to keep up with sophisticated methods fraudsters use as their systems are not equipped with capabilities to read and interpret data fast enough to detect suspicious/dubious activities.

To be able to quickly identify potential fraud and money laundering activities, AI brings the power of advanced data analytics systems to combat fraudulent transactions and improve compliance. In addition, AI has tools and systems that automatically compress data, and interpret the data within a few seconds, which otherwise takes a lot of hours and days to understand. By collecting and utilizing data faster to identify a whole host of patterns, AI systems can predict suspicious activities and anomalous transactions. This capability will ultimately make banks more efficient, safer from frauds and compliant with anti-money laundering regulations.

• Effective credit risk management – Credit risk refers to the probability of loss due to a borrower’s failure to make repayments of any type of credit, and credit risk management is the practice of mitigating the probability of loan loss due to a borrower’s failure to make loan payments at any given time. Therefore, the credit risk management process is a critical process in the banking industry. It requires both accuracy and confidentiality. AI can help banks to have an effective credit risk management process by simplifying the analyzation of data of the prospective borrower. AI can combine the personal data of a prospective borrower with market trends, his/her most recent financial activities and transactions to identify the potential risks in giving out the loan to the prospective borrower. Also, AI will help banks to get an idea of the prospect’s behaviour through AI’s behaviour algorithms hence lowering the probability of lending to a riskier individual.

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Next week, I will share more how AI can impact the banks.

Written by Kelvin Mkwawa, MBA

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