“I think fintech is a broad term,” said Frank McKenna, Chief Fraud Strategist at Point Predictive. “It can apply primarily to technology that enables faster banking, and more digital banking that hasn’t been satisfied with kind of the traditional brick and mortar banks or finance companies. Fintech can be banks, it can be platforms that provide the backbone for that kind of streamline lending. Or it can even be considered companies like ours, technology that helps financial companies make better decisions.”
Fintech, which can take on any one of the forms McKenna described, has been causing transformations for over a decade and yet there are still processes in the lending world still ripe for improvement.
“[Fintech is] growing every day, it will be more because of timing,” said Richard Gusmano, CEO of BCCUSA. “I think we’re going to see more and more people doing it, especially with the SBA opening up lending to non-banks. You’re going to see more of it in many different fashions and derivatives and how they see it is going to continue to emerge.”
Gusmano’s company helps businesses secure bank lines and bank loans, a system that now includes its very own AI-powered solution. He’s already seeing how AI and machine learning technologies stand to disrupt processes in the small business finance ecosystem.
“There’s so many different ways to use it and it is not rocket science,” Gusmano said. “In the MCA space, it’s amount of deposits, it’s average daily balance, it’s business type, and other positions. AI can immediately pick up those things if programmed to do so. I would think that the MCA underwriters over time should be concerned because AI could likely do that and pick that up.”
But it’s not just about replacing manual processes, but also doing it in an efficient manner.
“Since most fintech is dealing in a non-face to face environment, you’re going to have a whole host of risk in fintech, more than you might have in a traditional bank,” said McKenna of Point Predictive, whose company collaborates with lenders to detect potential risks. “I can just name off five or six: you have higher rates of identity theft, use of fake IDs called synthetic identities, you have more falsified documentation, fake employers, people shot-gunning where they’ll go to multiple fintechs the same day and get as many loans as they can, as quick as they can. They call it shot gunning.”
McKenna added that if someone has no knowledge of how to navigate these types of strategies or does not have the right technology to handle it, they may fall victim to them.
The keyword there might be someone, as in a person
“The risks associated is that you still are going to need someone that can make human decisions, even with financial technology,” said Gusmano. “And if you don’t, you’re going to be keeping yourself away from businesses that you want to do business with. It can never be 100% tech.”
In today’s dynamic world of fraud detection, technology, and artificial intelligence (AI) are allies. The insights of industry experts, Yinglian Xie, a technology veteran with a background at Microsoft Research and CEO at DataVisor, Sandip Nayak, President at Fundation, and Andrew Davies, Global Head of Regulatory Affairs at ComplyAdvantage, discuss the transformative role of AI in fraud prevention.
When DataVisor started, it primarily offered advanced machine learning solutions, through an unsupervised approach. In other words, their programs can spot fraud without needing a loss or training labels; they can automatically identify suspicious activities. Xie explains that AI’s ability to make rapid decisions during real-time transactions depends on the amount of data available for this process. To achieve a proactive response, it must be synchronized with real-time data, as opposed to a manual or “supervised machine learning” approach.
“We need to kind of switch the traditional approach looking at fraud being very much kind of an isolated case, like a manual approach, and into something we need technology for, said Xie. “And we need to essentially be able to make decisions instantaneously as well.”
In addition to unsupervised learning algorithms, Xie explains that generative AI falls into another category of fraud detection. This method describes the data and communicates information back in human-like responses. Xie gives an example that as customers, some may not understand why a transaction was rejected and that’s where generative AI comes to rationalize the reason behind the rejection.
Echoing Xie, Nayak described solutions where traditional techniques fail, one of them being unsupervised learning algorithms. These algorithms can use techniques like anomaly detection to actually hone in on “the needle in a haystack problem.”
“Number two, the automated and advanced nature of AI can really solve the shortcomings of rules based and human based approaches in detecting fraud and can also self-calibrate itself as the nature of fraud evolves with time,” said Nayak.
Meanwhile, Andrew Davies pointed out that one of the biggest challenges faced by banks and financial institutions is “they are constantly playing catch-up.” With the accelerated pace of money movement and real-time settlement, he emphasized that fraudsters capitalize on this by being swift and innovative, continuously seeking out new vulnerabilities to exploit.
“Banks must update their legacy technology which leaves too many weak points in the control environment,” said Davies. “Additionally, as money moves more quickly and is subject to finality, fraud detection must be done in real time.”
And as the digital landscape continues to evolve, Nayak envisions the adoption of these technologies will be beneficial to the lending industry. Embracing different strategies not only reduces fraud losses but also enhances capital efficiency, paving the way for increased profitability and security in lending, according to Nayak.
“I do expect the lending industry, especially the ones who adopt the latest technologies of fraud detection, will have a competitive advantage compared to those who don’t,” said Nayak. “And what that will do is it will help them preserve more of their capital in the current tough macro environment by helping the overall unit economics…”
Unsupervised machine learning and generative AI are strategies reshaping fraud prevention. The ability to make rapid, data-driven decisions, adapt to evolving fraud tactics, and provide human explanations behind alerts has become a cornerstone in modern fraud detection.
“…It’s just been pretty impressive how we have this technology that came out that has literally changed everything, and it was almost overnight,” said Kareem Jernigan, CFO at Leasing Associates Inc.
Earlier this week the Black Equipment Finance Network (BEFN) hosted a webinar titled ‘Leveraging ChatGPT for Maximum Productivity’ for the equipment finance space. The panelists were Cheryl Tibbs, George Parker, and Kareem Jernigan.
Jernigan is already using ChatGPT in his daily work life. In one example, he said that he commonly uses it to analyze and find errors in spreadsheets. In another, he’s saving a lot of the time he normally spent on writing.
“…I also run HR, and so I have to craft communications and/or policies,” he said, “so, when you think of crafting a policy or a communication that you have to send out, before ChatGPT that would be something that would take 4 or 5 hours to do. […] That task today I could get that done in 30 minutes.”
Meanwhile, George Parker, Co-CEO at VenSource Capital, said “You can use ChatGPT with training staff. You can develop training material. You can give tests and quizzes. You can design training programs with time as an element, it can do all of that. You can even design courses with ChatGPT. You can tell ChatGPT to come up with a time frame for learning each part of a subject.”
Parker added that ChatGPT can be used for brainstorming, articles, planning, meeting content, customer service responses, and more.
Even in the finer details of equipment financing itself, the panelists said that ChatGPT can produce credit assessment profiles and analysis, analyze and summarize financial data, and scrutinize contracts,
Of course, all of this only works if one understands what to put in and takes the care to evaluate what comes out. It’s all about the proper “prompt.” One example offered of a prompt that wouldn’t work is: “teach me credit analysis.” Something like that would be too vague and would result in a response that was too broad. Part of the reason there are panels and webinars about ChatGPT to begin with is so the industry can learn how to leverage it for maximum productivity.
It’s tempting to accept that if the internet claims something is AI-operated, then it must be, but AI is being held to an entirely new standard in 2023, thanks to the introduction of ChatGPT. That means everyone needs to be prepared to examine whether or not something is actual AI or if the use of AI is even integral toward achieving a goal.
“I think [it’s] a really important thing for people to do right now is to look at how they evaluate the AI marketing promise because there’s an opportunity now that people are capitalizing on to just launch with the name AI, that they’re using it, but not really, or they’re not doing anything you need,” said Robert Burke Jr., Founder and CEO of Sobo, a company that matches businesses with consultants. Burke says that one way to try and distinguish fact from fiction is to ask questions about the company’s AI team, their data strategy, and patents they might have, if any.
Jason Feimster, Founder of Moonshine Capital, said that a more fundamental question should be asked first, whether or not the use AI of really makes a difference to achieving the objective. “What is it that you want to achieve,” said Feimster. “Do you want to get funded? Can I fund you? Yes. That’s the only question that matters. Now, if I claim that I can get you funding through AI, and you care about how they work, we’re muddying the water, you’re still not closer to getting funded.”
At the same time, one shouldn’t hesitate to at least experiment with the technology. Jared Schulman, CEO at Lendica, says that “There are probably some small, idiosyncratic risks to interacting with AI but largely speaking, it’s a really exciting time. I think it’s right to be curious and to try, and some really great things are going to come from it.”
Meanwhile, Burke at Sobo said “I think this is the key to remember that AI is not a magic wand that instantly solves all your problems and challenges. It’s a tool that when it’s used properly, can provide benefits. But it also comes with its own challenges and limitations because it is such early stages.”
“Let’s be honest, a lot of this AI to me is like a Black Mirror episode,” said Erica Gilerman, General Counsel at Triton Recovery Group. “It was something that three years ago when you’re first watching Black Mirror, you’re like, ‘Wow, that’s amazing,’ and suddenly it’s here.”
The most talked-about technology lately has been AI. The fast-paced, easy, and accessible tools that AI is giving life to have the rest of the world questioning how necessary humans will be for many business functions.
“I think anyone who says that jobs won’t be lost because of AI is not being honest,” said Shawn Smith, CEO at Dedicated Financial GBC, a commercial recovery firm.
Companies that are built straight from AI won’t have to cut back on hiring, Smith explained, but he believes that once more businesses begin integrating AI, the need for more people won’t be there.
“I think what you’re going to see more of is AI being leveraged instead of hiring more people,” said Smith. “They will be able to grow without needing to hire more and reallocate people to doing more of the connection piece and allow AI to do the process piece.”
Gilerman, at Triton, a firm that also does commercial recovery, believes that some roles cannot be fully replaced by AI.
“Will it fully replace people,” said Gilerman. “I don’t see that happening anytime soon, especially in our space.” An example she offered is the necessity of having humans oversee what an AI is doing when it comes to underwriting to make sure it’s not getting it wrong. She also thinks that AI could be useful in automating mundane tasks.
“And not in a way that is bad, but more so of busy work versus truly being able to delve deeper into what we need to get done and getting it done faster,” she said, “which is what I really think AI is going to assist us in, getting everything done faster.”
“Everybody used to type everything with a typewriter,” said Shmulik Fishman, CEO of Argyle, a fintech company that focuses on employment and income verification, “And when computers came out, there was a huge worry that everybody that was a typist, all those jobs would be eliminated, and that the office would have this huge decrease in the number of people inside of it. The exact opposite thing happened.”
This outcome could happen all over again.
“Humans have a really amazing ability to leverage tools to make their day better, and to graduate themselves to working on more important things that tools or computers cannot do for them,” Fishman said. “And I think a ton of that’s going to happen with AI as well.”
“Based on the balance sheet provided, the business appears to have a healthy financial position,” the report states. This is the opening line of the written Financial Health Analysis conducted by OpenAI’s ChatGPT. From there it elaborates at length with all the relevant financial stats that an underwriter could ever dream of, even going so far as to recommend all on its own that recent tax returns, among other stips, should be requested to move forward.
What the world is coming to know as a chatbot, is capable of much, much more, according to Dave Kim, co-founder and CEO of Harbr, Inc. Harbr’s flagship product, IntakeIQ, is taking online application technology to new advanced places thanks to the introduction of real artificial intelligence. But there’s a right and wrong way to do this because keeping applicant information anonymous and secure is paramount.
“…security is massive, right?” said Kim. “Like you have to know going in that if you’re going to use a GPT or a Large Language Model that’s being hosted and you don’t have control of it yourself, that the data is 100% being used for machine learning.”
And along with security is the science of data input. Roughly speaking, the more information you send to ChatGPT the more it costs to spit out an answer. That means data not only needs to be secure but condensed down to such compact bits of input that the cost is acceptable and scalable. This is no domain for amateurs who think they can accomplish this with a basic monthly ChatGPT subscription. And Kim is no amateur.
“My background is in enterprise software development,” Kim said. A previous company he co-founded, GoInstant, was acquired by Salesforce for $70 million in 2012. Kim was already developing AI-driven technologies long before ChatGPT became known to the world, more recently in the commercial construction business. The aspect of invoices and payments combined with OCR technology soon evolved into a separate use-case where it could be used in financing like factoring and more. But their tech had to understand the niche particulars of the information it was analyzing.
“So we essentially started training a natural language processing model using machine learning techniques around those sorts of phrases and terminology for the construction industry,” said Kim. “So we were building that kind of tech first and then it became relatively easier when dealing with broader information in documents and other invoices that were coming in for not just construction.”
In 2022, Kim first encountered the capabilities of ChatGPT. He said that while the AI is great at creating a diversity of answers, the way they engineered their prompts with financial data produced consistent output. That’s what’s key. Harbr’s technology does a lot of the work on its own side first before sending off a highly secure, highly redacted, anonymized and reduction-optimized prompt to ChatGPT. The process can start with a pdf statement because it’s automatically OCR’d and analyzed first before any of this happens. Harbr isn’t able to view or retain any of the data and ChatGPT does not know anything identifiable about the applicant. Only the lending company is privy to the applicant’s info and the results. Setting this up for a lender can be accomplished very quickly.
The object isn’t to entirely replace underwriting, but to make it more efficient.
“Today we work with businesses that are in asset based lending, factoring, supply chain finance,” Kim said. “We’re starting to look at equipment, transportation, equipment financing and leasing. […] I think the entire secured finance market, there’s a fit here as the technology grows.”
Anyone that’s ever faced a coding hurdle has inevitably ended up on Stack Overflow, the go-to platform for developers to solicit answers from more experienced professionals about their challenges. Users typically explain what they’re trying to accomplish and paste a copy of the code that’s not achieving the desired result. That’s where the community chimes in, coming forth with their own solutions while other users upvote the best answers. The end result is not just a grateful user but an ever growing public database of questions and solutions available for public consumption. The sheer scope of what’s been compiled has opened up the door for other users to simply find a similar enough question that’s already been asked and copy the answer. It’s a very valuable tool.
Stack Overflow has been around for 15 years but from March to April of this year, traffic plummeted by 17.7%, according to SimilarWeb. Tech blog Gizmodo has suggested that a contributing cause is ChatGPT-4, the OpenAI chatbot technology that can write its own code, edit a user’s code, and even converse about what a user is trying to accomplish. A spokesperson for Stack Overflow confirmed to Gizmodo that ChatGPT was partially responsible for its loss of users. “However, our vision for community and AI coming together means the rise of GenAI is a big opportunity for Stack,” the spokesperson added.
But what’s a coding forum for nerds and brainiacs got to do with the lending industry? Well, for one thing borrowers were already flirting with asking virtual assistants for help with financial services products before ChatGPT even entered the ring. According to the most recent Smarter Loans survey, 16% of loan applicants surveyed said that they had at some point used Alexa, Siri, or other voice search tools to find information about financial services. None of those come even remotely close to what ChatGPT-4 is able to do. And AI is popular, so popular in fact that ChatGPT became the fastest growing app in history, crushing even the likes of TikTok in pace of growth. ChatGPT already had 100 million monthly users as of February, before its signature ChatGPT-4 model was released.
Therein lies the threat because not only is ChatGPT-4 incredibly adept at making coherent conversation but it is also ready to explain a concept or make a recommendation, just like a very knowledgeable friend would. For example, when asking it to make a list of the top small business funding companies, these were among the names it spit out:
- American Express (Kabbage)
- Funding Circle
- Square Capital
- National Funding
- PayPal Working Capital
It’s not a vomit of names. ChatGPT-4 was familiar with their areas of expertise. When pressed further it said that OnDeck would help get the cash fast but working with Square Capital might work better if one is processing a high volume of credit card transactions. For strong credit and a large loan, it suggested Funding Circle. After expressing an interest in OnDeck, the AI provided instructions on how to apply via the OnDeck website and a phone # to call with questions. In this real-world example, the AI replaced both the online search and the role of a broker all in one and all within minutes. It can also read the contracts and alert borrowers to certain clauses. When pressed about an unusually high APR, for example, the AI even offers an encouraging explanation for how moving forward could still make sense.
“Be sure to also consider the potential return on investment from using the loan funds,” it said. “If the growth or savings you anticipate from using the loan funds exceeds the cost of the loan, it may still be a good decision despite a high APR.”