Generative artificial intelligence (AI) has taken the world by storm with its ability to answer complex questions, write novels and create music and art. Platforms like ChatGPT and Bard — today’s most well-known examples — have become household names. Meanwhile, generative AI is quietly revolutionizing payments.
Generative AI is a type of artificial intelligence that uses machine learning techniques. It can review raw data, find patterns and make connections on its own. Its primary strength is its ability to quickly process enormous amounts of data. The average person can read about 238 words per minute. ChatGPT was trained on 300 billion words — equalling roughly 2,400 years of reading.
In the payments industry, which depends on dense data, generative AI is set to become a widely utilized tool. It is expected to significantly improve fraud detection, support and underwriting. However, new, innovative use cases for AI in payments are already emerging. A decade from now, there will likely be few business areas that aren’t touched by this emerging technology.
Improving Payments Fraud Detection and Prevention
Because AI can analyze massive amounts of data (in very little time), it’s ideal for catching and stopping fraud. Every card transaction generates dozens of data points — some of which can be used to identify fraudulent transactions. When a new transaction is processed, the AI tool can instantly analyze the data against everything it has learned to make an accurate, real-time decision to approve, deny or quarantine the payment.
As payments increasingly digitize, they become more lucrative targets for fraudsters. Unfortunately, older, rules-based detection systems and limited supervised AI solutions are no longer enough; they are highly static and require human intervention. Instead, advanced AI-powered fraud detection systems like Kount are becoming the standard, and they’ll only get better as generative AI advances.
Enhancing the Merchant Support Experience
The payments landscape is competitive. To compete, providers must offer the best merchant support available. The faster and more efficiently providers resolve merchant issues and questions, the stickier customers will be. Generative AI allows forward-thinking payments companies to deliver high-value support in a more cost-effective, consultative way.
AI Support Bots: Standard support bots are helpful when answering basic questions or redirecting customers to the right department. However, their limited responses can be frustrating—especially for consumers with complex problems. It can also be time-consuming to program these bots with the appropriate answers.
Generative AI systems enable customers to have dynamic, human-like conversations with chatbots. Instead of providing general responses, generative AI tools can assess a merchant’s request, understand it in context and create highly targeted responses. That gives human support agents time to address more complex issues, improving quality and merchant satisfaction.
Internal Knowledge Bases: When human support is needed, agents often depend on internal knowledge bases for answers. However, most knowledge bases are enormous, with inaccurate search functions that require agents to sift through pages of results.
Generative AI tools streamline this process by allowing agents to enter questions or merchant issues through text or voice commands. The system then scours the knowledge base and returns the answer in real time. This saves the agent time and effort while allowing them to provide helpful responses right away.
Refining Underwriting Models and Making Decisions Easier
Solutions like NMI’s automated underwriting and risk management tools use advanced AI to help payment providers underwrite merchants faster and more efficiently by performing checks at superhuman speeds.
Generating Training Data
AI-based systems need data to learn, and where that data comes from matters. In some cases, as with public-facing AI tools like ChatGPT, developers need permission to use certain intellectual property, like articles and novels, for training. Privacy is also a concern since training sets often include personal data. Unfortunately, there isn’t always enough data to fully optimize a system.
Generative AI can solve these problems by creating synthetic training data with the same statistical properties as real-world data. Users can customize this data so the AI program can better identify potential risks and red flags. This accurate, fictional data can train the associated machine learning models to achieve higher accuracy rates. Synthetic data is already used in the insurance industry, and the payments space will likely follow.
Decision-Making Assistance
AI-based underwriting tools are already capable of assisting in or making approval decisions for underwriters. In complex cases, human underwriters may need to investigate or reanalyze the decision the automated system has suggested.
However, generative AI-based tools make this faster and easier by automatically identifying any potential risks or red flags associated with a merchant’s business. Underwriters can then review the information and approve, decline or pend it for further investigation. This technology allows underwriters to approve or deny merchants up to 10 times faster than traditional workflows.
AI-Powered Change Awaits the Entire Payments Industry
Fraud detection, support and underwriting represent three areas in which generative AI already impacts the payments space. In an industry largely defined by data, generative AI can transform payments beyond anything we see in the industry today.
NMI has been leading innovation in the payments space for over 20 years, and our partners have access to valuable AI-driven tools like our automated underwriting tools and advanced fraud protection. To learn more about generative AI in payments and our cutting-edge payments technology, reach out to a member of our team.
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