Smart ways to use Artificial Intelligence in Payments

The Payments Association has released new research showing how artificial intelligence (AI) and machine learning (ML) are being used in the payments, finance and banking sectors and how they may be used in the future.

Using AI Intelligently: Smart ways to use Artificial Intelligence in Payments, completed in collaboration with several important figures in the payments industry, shows that the majority of financial services organisations with over 5,000 employees are using some form of AI.

These technologies allow companies to scale processes faster than human beings, process data far more efficiently than current decision-making programs and, most importantly, can find patterns and make inferences.

The concept of artificial intelligence (AI) has been around for a long time and is now making major inroads into financial services.

AI has a significant impact in areas such as fraud and compliance, credit scoring, financial distress prediction, robo-advising and algorithmic trading in many financial services firms.

For example:

• 70% of all financial services firms are using machine learning to predict cash flow events, fine-tune credit scores and detect fraud
• 54% of financial services organisations with 5,000+ employees have adopted AI
• It is forecast that the AI market will hit $360.36 billion by 2028

This is because AI can carry out processes at scale faster and quicker than humans. It can also make inferences that a human would miss when it comes to spotting patterns and linking up seemingly disparate sources of information.

However, the application of AI in payments has not been well researched, nor is its application in payments well understood.

At a time when financial technology (FinTech) companies are working to make their products more personal while also making them efficient and seamless – as 92% of consumers expect a fast, frictionless experience while also getting one that is as trustworthy and secure as possible – AI offers a way to combine the best elements of human operators and traditional digital automation.

The efficiency savings are potentially astronomical, but more important is the ability of AI to improve itself in real time by analysing results and spotting patterns.

Use cases for AI range from giving more accurate credit scores to document processing and anti-fraud applications.

The research shows how interest and uptake in AI was slow but steady pre-COVID, but following the pandemic interest increased dramatically as financial organisations sought ways to become more efficient.

This in turn caused a rise in regulatory interest in AI to mitigate risks relating to privacy, unlawful discrimination, and security.

Venture capital has also flowed into the industry, with AI-orientated start-ups in the finance and insurance industry being the seventh largest sector for investors.

“The financial services industry is going through a period of profound change and disruption. Technology is providing the means for firms to reimagine the way in which they operate and interact with their customers, suppliers and employees,” says Naushad Contractor, Chief Executive and Founder of Fable Fintech.

“One significant area of development is the effective utilisation of artificial intelligence (AI). AI is fashion but it’s at an early stage and we are not really seeing it applied across the board on a consistent basis in a way that we all recognise and understand.

AI is big Data, Big Processes but when AI starts to predict rather than just correlate, then we will see the true value of what it brings.”