The revolutionary movement of the digital payments landscape is well underway, with new entrants and technologies in the B2C and peer-to-peer lending (P2P) sphere evolving continuously. However, there has been one sphere where the rate of innovation hasn’t yet been reflected by other industries, specifically the B2B payments domain.
According to CB Insights, the B2B payments sector is set to become a $20 trillion business by the end of this year. A multitude of payment providers, including PayPal and various other Fintech startups, have already sought to reduce the burden and repetitive processes associated with B2B payments. But the decisive question here is why has it taken so long for B2B payments to make its way to the digital age.
“Today’s $3 trillion worldwide SMB credit gap is narrowing because the criteria to secure loans are changing, and increasingly, embracing alternative data sources.” – Ken So, Founder and CEO at Flowcast
B2B transactions include analog procedures, and obsolete technologies and are a major pressure point for small and medium businesses (SMEs), which account for 80% of total labor and processing expenditure in the U.S.A, while SMBs expend almost $2.7 trillion on accounts payable alone. In the midst of all this, the digital payment movement buoyed by machine learning and artificial intelligence (AI) systems has begun revolutionizing processes by abolishing repetitive administrative tasks altogether, making legacy systems obsolete, and reducing a host of other inefficiencies.
AI-powered virtual assistants such as chatbots popularized by consumer technologies have now become a mainstay in B2B purchasing, aiding customers along the procurement complexities journey and simplifying B2B payments subsequently. Vendors are of the opinion that more such AI-enabled bots will help improve procurement efficiency, further assisting users in expediting processing efficiency and diminishing errors. These tools are part of more overarching initiatives to utilize AI to automate and ease sophisticated B2B processes.
The Evolution of AI and B2B Payments
Until a few years ago, payments included manual procedures and legacy systems, which was a big pressure point for SMEs. These difficulties can be reduced or rendered obsolete by AI-enabled solutions.
Today, AI is deeply entrenched in the payment environment. Traditional banking, lending, and financial institutions have boosted their active investment in AI and integrated it into their technological infrastructure. In fact, the rate at which it’s going, the global investment in AI by the Fintech market will reach USD 22.60 billion by 2025 at a CAGR of 23.37%.
A majority of these technological disruptions help processes such as transactions and/or detection of fraudulent activities. Alongside this, there is also greater attention to the evolving requirements of the consumers. So much so that chatbots operated by AI are increasingly emerging and becoming native to customer-oriented approaches.
Chatbots are simplifying and automating the dynamic B2B acquisition process. They significantly minimize the time spent producing invoices, seek out substitutes for customers, guarantee timely and correct compensation, and provide buyers with the right details.
These technologies are increasingly transforming the digital and offline transaction process dramatically, eventually resulting in increased conversion rates and enhanced protection. AI is expected to have a major influence on the whole industry by strengthening the following areas: operational performance, growth & innovation, and risk mitigation.
In our diverse regulatory, technical, and socio-economic environment, enhancing operating effectiveness is indeed one of the first areas where AI has produced numerous benefits. It can simplify routine, rule-based, labor-intensive activities to increase output quality, and free up resources.
Indeed, the value of robotic process automation (RPA) is expected to reach $4.3 billion by 2022. This can be utilized to drive accounting efficiencies by information management to boost consolidation, the company’s cash flow, and the reliability of financial management.
In fact, the automation of accounts receivable and payable is now a popular use-case. Furthermore, according to a Paystream Advisors report, the greatest benefit experienced by organizations that adopted AI tools for their accounts receivable & payable was a significant decrease in paper invoice volume.
AI has now become non-invasive to the point where minimum convergence with current systems infrastructure is needed. This, in essence, boosts efficiency by doing away with the human efforts needed to boost labor-intensive activities. Other systems apart from accounting and finance have also been implemented, for example, in payroll and insurance, application management, and sales-related jobs.
There are several other use cases of AI where it can improve operating performance, such as enhancing the efficiency of procurement processes. One instance is contract management, where AI bots can be deployed to collect data and illustrate contract content.
This will facilitate the restructuring and re-negotiation of a large number of contracts, minimize possible conflicts, and improve the output. In more general terms, AI can also be used to boost the process improvement.
How Do AI Tools Simplify B2B Payments
AI, though in its nascent stages, is having an indelible effect on B2B payments. In the coming future, it will inevitably transform the way institutions of all sizes handle financial management. Smart chatbots will also be used to ease workflows, digitally connect systems and accounts, and allow everything from automatic record-keeping to new types of digital payments.
As time evolves, companies will depend heavily on digitalized processes that will enable them to concentrate on what counts as the most important to them: building their brand. Here, we will take a look at how AI can simplify B2B payments in the years to come.
1) Automating accounts payable
Most SMBs pay almost $16 – $22 to process invoices manually. However, Goldman Sachs says that businesses can reduce this down significantly to almost $6-$7 straightaway by automating accounts payable.
Automation helps companies to remove several unnecessary elements, dramatically reducing the time and expenses involved with processing and handling payments. Standardizing financial transactions with automation software also helps to minimize the risk of operator error and to control payments.
2) Improving access to credit
Apart from standardizing accounts payable, automation technology eases the process of receiving financing by SMBs. This comes as a huge relief for 81% of SMB invoices whose invoices are due for at least a month. Moreover, the average SMB, which has only 27 days of cash on hand, can simplify its cashflow a lot through automation.
AI-enabled credit scoring can evaluate businesses for far less than it would have had they done it manually. In addition, AI tools can abolish any bias and use contemporary as well as historically available data to make credit decisions where conventional financial information may be lacking.
3) Detecting and preventing fraud
Did you know that 58-68% of respondents in a CFO Insights report claimed that transaction security was the attribute of utmost concern when it came to a payments solution? Couple this with the concern that at least 78% of B2B businesses experience payment fraud, and it’s easy to see how AI can intervene to help resolve such security risks.
AI and ML are now not only driving fraud detection but also fraud prevention. Many fraud prevention tools already use AI to encrypt or safeguard client and supplier information. More sophisticated tools are now incorporating ML to help identify and assess potential risk factors and to discover any suspicious behavior or vulnerabilities that might otherwise go unnoticed by humans.
In summation, AI has made it possible for important players in the Fintech and payments ecosystem to easily bypass the risks associated with both their front and back-end processes. It can eradicate repetitive processes that curtail business development and let SMB(s) free up resources and money to focus on more relevant issues. This will consequently lead to increased investor confidence in B2B Fintech entities as the B2B payment area continues to grow and evolve.