AI Powers Payment and Transaction Processes

By: Retail CIO Outlook | Tuesday, July 30, 2019

AI-based chatbots are increasingly being used by payment firms to interact with customers, answer their queries, help them navigate through the company’s website, and for other interactive services.

FREMONT, CA: The payment industry is a safety-critical sector that cannot afford security breaches. However, fraudsters are using innovative techniques to gain access to merchandise pages and transactions. Artificial intelligence (AI) is helping industries across verticals with safety-critical processes, so the payments and financial services industry must leverage the same.

AI against Fraud Detection

As e-commerce has transformed the way people shop and sell online, the traditional rule-based security measures are not effective enough to deal with modern frauds and attacks. The current system involves real-time payments and thus requires real-time fraud detection. With umpteen numbers of transactions being done electronically, it’s not possible for the humans to monitor them. As per a report by Capgemini, global payments digitally are expected to reach almost 726 billion by 2020. Machine learning (ML) patterns can monitor and analyze massive data sets and identify unexpected commonalities between fraudulent and non-fraudulent transactions. Moreover, AI systems can send notifications to the consumers if they detect an activity that doesn’t seem normal based on the past transactions for that user.

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Personalized Experience

Personalization is among the top in the companies priority list when it comes to adding business value. Organizations are using AI in other areas of the business as well. AI-based chatbots are increasingly being used by payment firms to interact with customers, answer their queries, help them navigate through the company’s website, and for other interactive services. AI is also allowing the lenders to experience a hyper-personalized look that will help them to know the creditworthiness of an individual. Traditional applications had inherent flaws that led to the inaccurate distribution of people. However, machine learning (ML) algorithms are enabling the lenders to analyze a variety of data sources and create personalized profiles to approve loans to people who are worthy but were previously deemed unworthy for credits.

Computer Vision-Driven Payment Transactions

An Ai-driven store involves recognition sensors that can automatically detect what people are picking and charge them for the products without having them to go for the traditional check-out processes. Thus the customers will be saved from the hassles involves with long queues. Companies like Amazon are pioneering the concept with significant advances being already made for the framework.