Artificial intelligence is slowly finding its way into the realm of payments and financial services. AI’s value in fraud detection is obvious, but it may also be used in other fields.

As per Juniper Research, the global number of mobile payment users is anticipated to reach 2 billion by 2020, and there’s little doubt that artificial intelligence will transform mobile payments and disrupt the banking system. Mobile payment apps are popular because of the convenience and efficiency they provide to the user experience. While AI and machine learning are used behind the scenes in many apps, they are set to transform the end-user experience. 

Impact Of AI On Mobile Payment

● Chatbot

The chatbot, a software that converses with clients through text or speech, is the most popular and possibly the most restricted application of AI in financial services. Chatbots are commonly used in financial services to engage with consumers for the first time, answering queries or guiding them to a specific section of the website. The bot transfers the conversation to a human representative for more complicated conversations.

Mobile users prefer to connect with chatbots and SMS text messaging, according to an Open Market study, with financial services becoming the top sector where they want to see better customer service and engagement.

With the debut of Erica, a chatbot that clients can speak with through voice or text message to help manage their money, Bank of America is just one example. PayPal is another payment service that connects its chatbots with social media apps like Facebook Messenger to allow customers to make payments directly from the app.

If you are looking for a chatbot for your business, O-Chat by ONPASSIVE allows you to simplify your conversations with your customers.

● Predictive Analysis

AI and predictive analytics can work together to help businesses find trends in data and tailor e-commerce to specific customers. Because predictive analytics can rapidly and efficiently mine vast amounts of data, many businesses turn to big data to better understand their customers’ purchasing habits. Predictive analytics data provides real-time knowledge of customers, which may lead to higher engagement and better business planning.

Predictive analytics, when combined with AI, may help organisations gain actionable insights. Capital One uses both to develop new products and offers for its customers depending on their spending habits. 

● Credit Score

Until recently, a consumer’s credit score was indeed a simple number, the time-honoured FICO score that was used by all banks in their underwriting. On the other hand, Banks are heavily focusing on dozens of ratings based on a variety of data sources, analytics, and AI technology.

Lenders may utilise AI to obtain a detailed look at someone’s creditworthiness and assess individuals previously judged uncreditworthy.

● Fraud Detection

One method AI technologies affect mobile payments and enhance end-user engagement is transaction filtering, which prompts only high-risk transactions with a security chargeback layer. By leveraging real-time features like geolocation, behavioural analytics, and physical biometric qualities to identify changes that may be fraudulent in origin, these techniques prevent discouraging “good” consumers from returning to abandoned carts or conducting frequent, low-risk transactions. AI is being used in mobile payment procedures to help reduce user friction, which might lead to an increase in mobile sales.

Leading fraud protection firms employ machine learning and artificial intelligence as hidden weapons in their fight against fraud. Consider Kount, a business that pioneered the use of machine learning to combat fraud with their patented product, Kount CompleteTM, the complete all-in-one solution for detecting and preventing fraud at every transaction.

Another example of how artificial intelligence influences mobile payments is fraud platforms that use new technology to combat fraud.

● False Declines 

Companies can’t always utilise historical transaction data to detect future danger on a big scale, and inaccurate denials of legal transactions aren’t a new problem.

According to Ajay Bhalla, head of Mastercard’s enterprise risk and security, AI may change the game, but only if it is clever enough to modify its expectations based on the conditions of each transaction.

Conclusion

As our world becomes more complicated, the desire for simple and hassle-free purchasing of products and services will continue to rise. Global giants like Apple and Samsung are increasing customer dependence on device capabilities that harness artificial intelligencemachine learning, and mobile payment apps as new technology is released with each smartphone OS update. As a result, customers will embrace future technologies such as digital and cashless payments. So, if you wish to switch to AI-based products, contact us.