AI & B2B Payments Landscape — General Trends and Legal challenges
By Nanda Harish, VP — Legal and Company Secretary, PayMate (@NandaHarish146)
Artificial Intelligence (“AI’’), was considered a technical utopia a few years ago, has now become a reality. In fact, AI has already arrived in our everyday world; just think about your e-mail spam filter, natural voice recognition, online shopping recommendations — or simply about the predictive keyboard on your smartphone. Today the manner in which consumers and business pay each other is also driven by AI to a large extent.
AI and Payments Landscape
Let’s deep dive a bit further into the way in which B2B payments are evolving. Few years ago, these payments involved analogue processes and traditional systems, which was a significant pain point for small and medium-sized businesses (SMEs). These challenges can be minimized or made redundant by introducing new payment technology, most notably through AI and machine learning.
Today, AI has firmly embedded itself in payments landscape. Banks and Financial institutions have increased dedicated investments in AI and have incorporated it into their technical infrastructure. Most of these technical disruptions support process like transaction and/or fraud monitoring and also there is increased emphasis on dynamic needs of the customer. Chatbots and voice banking — both powered by AI are emerging in customer-facing solutions. They are gradually changing the online and physical conversion process significantly, ultimately leading to higher conversion rates and improved security. Going ahead AI is bound to impact the whole industry, significantly, in the years to come. In my opinion, AI will at some point become the key differentiator for technology and payment companies.
Let’s look at how risk decisions are made? As a merchant or acquirer, you do not want to accept a payment where there is an increased element of risk for a fraudulent action or a substantial likelihood for a charge back. On the other hand, rejecting a “good” payment normally results in conversion loss and thus, lost revenue for the merchant.
Risk decisions in payments are never 100% definite, therefore they are the perfect playing field for Deep Learning technologies.
To decide on acceptance or decline of the payment, many different factors are available to be taken into account, for example:
- Time & date — e.g., is a credit card used at normal shopping times?
- Is its self-financing transaction- validated through AML checks?
- Are the transaction exceeding limits specified by the Merchant?
- Merchant category codes — is it used at a supermarket or for online games
- IP-addresses — where is the-addresses — where is the device used located
As an alternate, Social information — the use of social media data, though in a nascent stage could a new AI application in payment risk detection
The payment industry has a long history of working with data to make qualified risk decisions. For sure, risk analysis is the “bread and butter” application of Deep Learning technology within a payment company, optimal checkout process and also on how to integrate payment in the right way.
In the upcoming years we expect many new applications, driven by AI and emerging technology that will significantly influence the industry, both in payment and commerce in general.
AI, while in its infancy is influencing B2B payments, AI ultimately will change the way businesses of all sizes run their financial operations. Smart digital solutions will simplify processes, electronically link systems and accounts and allowing for everything from automated data entry to new forms of automatic electronic payments. Businesses will heavily rely on digitized end-to-end processes that frees them up to focus on what matters to them: building their business and brand.
Legal Challenges and AI
Marrying AI with payments would lead to dynamic business payment opportunity. How does this integrate with legal and regulatory landscape is a million-dollar question? Questions on data privacy, data localisation, cross border transfer of data, and regulatory adherence will need to be effectively redressed.
Data security, fraudulent transactions and AML compliances is a major concern for all parties involved — financial institutions, third party service providers and account holders.
For customers, perhaps the key challenge within these trends, and across the entire payment’s ecosystem, is that of security — especially with the proliferation of digital technology.
Conclusion
To sum up, the remaining trends focus on the potential disruption of ever-evolving coding, the possibility of payments being made between anybody and on any device, the growing sophistication of fraudsters, and the changes that will be necessary to speed up transactions.
AI has enabled key players across the payments and fintech landscape to rapidly disrupt both in terms of their back and front-end processes. From cutting costs, automating time-consuming operations and shortening the approval process, both AI and Machine Learning will continue to pave the way for the significant disruptions in the payments industry. The changes we’ve already seen are just the beginning and personally I’m excited to see and be a part of the future payment landscape
Laws around AI are new and needs more understanding and comprehension e.g. the matter in which consent of a user may be stored, accessed by an AI app is huge. No doubt there is no one shop solutions to synergise AI with legal framework, however I am optimistic that going ahead we will have specialist AI lawyers working in Payment landscape disrupting technology in ways we never could have imagined.
