AI, Payments Orchestration, Payment Intelligence
FinTech (Financial Technology) is the use of technology to address the financial needs of consumers and businesses. There are several verticals within financial services (i.e., lending, personal finance, insurance, wealth management, payments) and therefore, a variety of technologies that attempt to address the opportunities that have emerged from archaic infrastructure and rigorous levels of government regulation. According to an article posted by Crunchbase in Q1 of 2023, payments remain the “darling of the fintech space”. This particular area led in total funding and deals in the fourth quarter of 2022 when compared to every other vertical of FinTech. In spite of the decline of overall FinTech investments in 2022 when compared to 2021, about $3.4 billion was raised across 188 deals in the payments space in Q4 of 2022 alone. This is unsurprising as business and consumers continue to opt to pay for things digitally.
With global digital payments revenue expected to reach $14.79 trillion by 2027, having a proper technical stack to support a modern payment strategy is critical for eCommerce and digital merchants looking to grow, maintain and improve their customer base. According to Richie Serna, CEO of payments startup Finix, most merchants do not have the tools, data, or knowledge to develop or execute on an effective payment strategy that informs its technical stack and configuration; even those that do often leave significant opportunities on the table. An effective payment strategy needs both sophisticated orchestration and intelligence that are data driven. Artificial intelligence is the next wave of payments’ innovation to vastly improve merchants’ customer relationships and bottom-lines.
At a high-level, basic payments are processed the following way:
- Step 1: The customer pays with a credit card. The customer purchases goods/services from a merchant
- Step 2: The payment is authenticated. The merchant point-of-sale system captures the customer’s account information and securely sends it to the acquirer
- Step 3: The transaction is submitted. The merchant acquirer asks the credit card network to get authorization from the customer’s issuing bank.
- Step 4: Authorization is requested. Credit card network submits the transaction to the issuer for authorization.
- Step 5: Authorization response. The issuing bank authorizes the transaction and routes the response back to the merchant.
- Step 6: Merchant payment. The issuing bank routes the payment to the merchant’s acquirer who deposits the payment into the merchant’s account.
The four-party model (merchant, acquirer, network, and issuer) becomes more complicated when merchants have more bank accounts and payment providers with no integrated management solution. Other challenges include slow processing, high costs, inflexible payment methods, and integration limitations. Payment orchestration solves these pain points by providing an end-to-end payment that automates and optimizes the routing and processing of payment transactions to different payment methods, processors, acquirers, and other relevant parties. These platforms allow merchants to dynamically route transactions based on factors such as cost, availability, performance, and customer preferences, to optimize payment processing, improve authorization rates, and reduce transaction failures. The core of payment orchestration is a sophisticated rules engine.
According to 451 Research’s Voice of the Enterprise surveys, “61% of merchants agree that modern payments infrastructure will be highly transformative for their business over the next three years. In 2023, more merchants will pursue payments optimization strategies as they seek to meet their growth, customer experience and operational objectives”. Benefits of payment orchestration include increased revenue, reduced costs of processing payments, easier payment integration, ability to access various payment methods, increased acceptance rates. Think of the orchestration level as the brain to determine the best routing for transactions and the gateway as the technology that collects the consumers payment details.
In a complementary fashion, payments intelligence involves the analysis of various data points related to payment transactions, such as transaction history, customer behavior, device information, location data, and more, to gain insights and identify patterns or anomalies that may indicate fraud, risk, or other payment-related issues. Traditional payment gateways do not provide data reporting and visualization for merchants to action upon or inform their payment strategy. Having insights to detect and prevent fraudulent acceptance rates, improve payment-related decision-making, and maintain compliance are mission-critical for merchants as fraudulent charges have increased almost in parallel with the rise of e-Commerce transactions. Without the proper methods of monitoring fraudulent charges, merchants can suffer from lower authorization rates, increase in chargebacks, lower processing volume limits, lower customer satisfaction, and impact on overall business reputation. Complementary benefits of payment intelligence include additional support for increased volume and complexity of digital payments, including speed and accuracy in evaluation, while minimizing false positives and claims
Together, payments orchestration and intelligence provide merchants with a modern payment strategy filled with insights, automation, and optimization capabilities to streamline payment processes, improve operational efficiency, enhance the customer experience, and mitigate risks associated with payments in the digital commerce landscape. By leveraging data and technology in a strategic manner, payments orchestration and intelligence can help merchants make informed decisions, optimize payment operations, and achieve better business outcomes in the realm of digital payments.
A modern payment strategy can be further enhanced with artificial intelligence (AI) to streamline operations, provide real-time insights and reporting, and beef up anti-fraud efforts. According to Artificial Intelligence +, in a complementary fashion, AI in payment technology can play a very crucial role in a merchants’ overall bottom line by analyzing large data sets in real time and safely executing or stopping payments effectively. The opportunity is huge: global AI in the payments industry is expected to reach $22.6 billion by 2025, witnessing massive growth from $6.67 billion in 2019. AI can help optimize payment orchestration and intelligence in the following areas:
- Fraud Prevention: AI can help merchants identify and prevent fraudulent transactions. By analyzing transaction data, payment intelligence tools can detect patterns and anomalies that may indicate fraud, such as unusual transaction amounts, multiple transactions from the same IP address, or inconsistent billing and shipping information. This helps merchants protect themselves from financial losses due to chargebacks and fraudulent activities.
- Risk Management: AI can allow merchants to assess and manage risk associated with different payment methods, geographies, and customer segments. By analyzing historical transaction data and other relevant information, merchants can make informed decisions about which payment methods to accept, which customers to approve, and how to manage risk effectively. This helps merchants minimize potential losses and optimize their payment acceptance strategies.
- Business Intelligence: AI can provide valuable insights into customer behavior, preferences, and trends. By analyzing transaction data, merchants can gain a deep understanding of their customers’ purchasing patterns, spending habits, and preferences for certain products or services. This information can be used to optimize pricing, promotions, and marketing campaigns, as well as to identify opportunities for cross-selling, upselling, and customer retention.
- Payment Optimization: AI can help merchants optimize their payment processes for efficiency and cost savings. By analyzing transaction data, merchants can identify inefficiencies in their payment flows, such as high decline rates, long transaction processing times, or excessive fees. This information can be used to optimize payment routing, streamline checkout processes, and negotiate better pricing with payment service providers, resulting in cost savings and improved customer experience.
With the emergence of new technology, digital fraud, and cross-border payments, there are a variety of regulations and compliance processes that eCommerce merchants must comply with. By analyzing transaction data with artificial intelligence, merchants can identify and report suspicious transactions in real-time vs. traditional rules-based models, as well as ensure that they are conducting business with legitimate customers and partners. This helps merchants avoid penalties and legal liabilities associated with non-compliance with anti-money laundering (AML), know-your-customer (KYC), Payment Card Industry Data Security Standard (PCI DSS), Customer Protection Regulations, and International Money Transfer Regulations.
Startups that use AI for payment intelligence and/or payment orchestration business models include:
There are frequent exits and acquisitions within the FinTech ecosystem. Some of the most notable examples within payment orchestration and intelligence are Adyen, a Dutch payment processing company, which went public in 2018. Its IPO was one of Europe’s largest and valued the company at $8.3B. Another example is Braintree, a Chicago-based company that primarily deals in mobile and web payment systems for e-Commerce companies. The company was acquired by PayPal on 26 September, 2013 for $800MM. Investors are always looking for their next big bet and some of the most active players in the ecosystem include:
In terms of pricing, payment orchestration and intelligence platforms act as a single-entry point for merchants by aggregating and integrating with many Payment Service Providers (PSPs), acquirers, issuing banks and connecting with 3D party service providers. Companies like the ones listed above usually adopt a hybrid pricing model of a percentage fee plus a certain number of cents per transaction. Some may have a traditional B2B SaaS pricing model, transaction-based pricing model, customized pricing model, white-labeling model, value-added services model.
As the pandemic and consumer behaviors have accelerated shifts towards e-Commerce payments, the growth of digital payments has rapidly expanded within the last three years. With this unprecedented growth, there is ample opportunity for startups to innovate and compete on delivering a comprehensive solution to address both merchant and customer payment needs. As the use case for artificial intelligence expands to optimizing secure and safe payments, I am optimistic that artificial intelligence could be the differentiating factor for these startups looking to improve on fraud prevention, risk management, business intelligence, and payment optimization. While overall Fintech funding has decreased when compared to previous years because of the increase in inflation and interest rates, total investment dollars and deals for payments specifically in 2022 demonstrate that the demand for better payments systems remains inelastic.
Fintech remains Chingona Ventures’ largest category — below are some of our FinTech portfolio companies:
- Boom: Boom is an Android/iOS app that enables renters to build credit with the rent payments they already make, reporting to all three credit bureaus.
- Curu: Curu is a financial solutions platform that personalizes a credit acceleration plan for consumers and matches them with financial solutions tailored to their goals.
- Earlybird: Earlybird is a financial application to simplify investing for the next generation.
- Finix: Finix is a payment processing platform for businesses. Kudos: Kudos is a consumer smart wallet that maximizes consumer rewards and benefits while shopping online.
- Paerpay: Paerpay is a contactless payment and ordering solution for restaurants and vendors.
- Scout: Scout is a professionally managed retail investment platform with themed investment categories targeted toward Gen-Z.
- Sigo Seguros: Sigo Seguros provides affordable insurance solutions to Latinx, immigrant, and working-class populations via a bilingual mobile platform.
- Suma: Suma is a financial wellness company that inspires, informs, and empowers the Latinx community.
- Topl: Topl is a blockchain solution to prove and monetize sustainable and ethical practices.
If you’re an early-stage FinTech founder innovating at the intersection of artificial intelligence and payment orchestration and/or payment intelligence, who is currently raising its first round of institutional capital, we encourage you to submit your company here. We love companies that offer unique ways to engage with customers and generate value. Additionally, you can refer to this link for more information on what we seek in the next generation of Chingona founders.
