This is a guest post by Anthony Sabelli, Head of Data Science at Kabbage, a data and technology company providing small business cash flow solutions.
Kabbage is a data and technology company providing small business cash flow solutions. One way in which we serve our customers is by providing them access to flexible lines of credit through automation. Small businesses connect their real-time business data to Kabbage to receive a fully-automated funding decision in minutes, and this efficiency has led us to provide over 500,000 small businesses access to more than $16 billion of working capital, including the Paycheck Protection Program (PPP).
At the onset of COVID-19, when the nation was shutting down and small businesses were forced to close their doors, we had to overcome multiple technical challenges while navigating new and ever-changing underwriting criteria for what became the largest federal relief effort in the Small Business Administration’s (SBA) history. Prior to the PPP, Kabbage had never issued an SBA loan before. But in a matter of 2 weeks, the team stood up a fully automated system for any eligible small business—including new customers, regardless of size or stature—to access government funds.
Kabbage has always based its underwriting on the real-time business data and revenue performance of customers, not payroll and tax data, which were the primary criteria for the PPP. Without an established API to the IRS to help automate verification and underwriting, we needed to fundamentally adapt our systems to help small businesses access funding as quickly as possible. Additionally, we were a team of just a few hundred joining the ranks of thousands of seasoned SBA lenders with hundreds of thousands of employees and trillions of dollars in assets at their disposal.
In this post, we share our experience of how Amazon Textract helped support 80% of Kabbage’s PPP applicants to receive a fully automated lending experience and reduced approval times from multiple days to a median speed of 4 hours. By the end of the program, Kabbage became the second largest PPP lender in the nation by application volume, surpassing the major US banks—including Chase, the largest bank in America—serving over 297,000 small businesses, and preserving an estimated 945,000 jobs across America.
Implementing Amazon Textract
As one of the few PPP lenders that accepted applications from new customers, Kabbage saw an increased demand as droves of small businesses unable to apply with their long-standing bank turned to other lenders.
Businesses were required to upload documents from tax filings to proof of business documentation and forms of ID, and initially, all loans were underwritten manually. A human had to review, verify, and input values from various documents to substantiate the prescribed payroll calculation and subsequently submit the application to the SBA on behalf of the customer. However, in a matter of days, Kabbage had tens of thousands of small businesses submitting hundreds to thousands of documents that quickly climbed to millions. The task demanded automation.
We needed to break it down into parts. Our system already excelled at automating the verification processes commonly referred to as Know Your Business (KYB) and Know Your Customers (KYC), which allowed us to let net-new businesses in the door, totaling 97% of Kabbage’s PPP customers. Additionally, we needed to standardize the loan calculation process so we could automate document ingestion, verification, and review to extract only the appropriate values required to underwrite the loan.
To do so, we codified a loan calculation for different business types, including sole proprietors and independent contractors (which totaled 67% of our PPP customer base), around specific values found on various IRS forms. We bootstrapped an initial classifier for key IRS forms within 48 hours. The final hurdle was to accurately extract the values to issue loans compliant to the program. Amazon Textract was instrumental in getting over this final hurdle. We went from POC to full implementation within a week, and to full production within two weeks.
Integrating Amazon Textract into our pipelines was incredibly easy. Specifically, we used StartDocumentAnalysis and GetDocumentAnalysis, which allows us to asynchronously interact with Amazon Textract. We also found that using forms for FeatureTypes was well suited to processing tax documents. In the end, Amazon Textract was accurate, and it scaled to process a substantial backlog. After we finished integrating Amazon Textract, we were able to clear our backlog, and it remained a key step in our PPP flow through the end of the program.
Big impact on small businesses
For perspective, Kabbage customers accessed nearly $3 billion in working capital loans in 2019, driven by almost 60,000 new customers. In just 4 months, we delivered more than double the amount of funding ($7 billion) to roughly five times the number of new customers (297,000). With an average loan size of $23,000 and a median loan size of $12,700, over 90% of all PPP customers have 10 or fewer employees, representing businesses often most vulnerable to crises yet overlooked when seeking financial aid. Kabbage’s platform allowed it to serve the far-reaching and remote areas of the country, delivering loans in all 50 US states and territories, with one third of loans issued to businesses in zip codes with an average household income of less than $50,000.
We’re proud of what our team and technology accomplished, outperforming the nation’s largest banks with a fraction of the resources. For every 790 employees at a major US bank, Kabbage has one employee. Yet, we surpassed their volume of loans, serving nearly 300,000 of the smallest businesses in America for over $7 billion.
The path forward
At Kabbage, we always strive to find new data sources to enhance our cash flow platform to increase access to financial services to small businesses. Amazon Textract allowed us to add a new arrow to our quiver; we had never extracted values from tax filings prior to the PPP. It opens the opportunity for us to make our underwriting models more rich. This adds another viewpoint into the financial health and performance of small businesses when helping our customers access funding, and provides more insights into their cash flow to build a stronger business.
COVID-19 further revealed the financial system in America underserves Main Street business, even though they represent 99% of all companies, half of all jobs, and half of the non-farm GDP. Technology can fix this. It requires creative solutions such as what we built and delivered for the PPP to fundamentally shift how customers expect to access financial services in the future.
Amazon Textract was an important function that allowed us to successfully become the second-largest PPP lender in the nation and fund so many small businesses when they needed it the most. We found the entire process of integrating the APIs into our workflow simple and straightforward, which allowed us to focus more time on ensuring more small businesses—the backbone of our economy—received critical funding when they needed it the most.
About the Author
Anthony Sabelli is the Head of Data Science for Kabbage, a data and technology company providing small businesses cash flow solutions. Anthony holds a Ph.D. from Cornell University and an undergraduate degree from Brown University, both in applied mathematics. At Kabbage, Anthony leads the global data science team, analyzing the more than two million live data connections from its small business customers to improve business performance and underwriting models.
7 Awe Inspiring AI Techs That Transformed The Digital World
For many people worldwide, artificial intelligence is slowly making its way into their lives without fussing. From our cars, homes, mobile phones, and our workplace, Artificial Intelligence is everywhere.
Apart from our personal lives, Artificial Intelligence has also made its way into various industries such as automotive, e-commerce, healthcare, and entertainment.
To better understand artificial intelligence’s impact on the digital world, we first need to know what it is. To sum up,
“Artificial intelligence reduces human intervention with the help of algorithms and tools that provide recommendations, predictions, and decisions through real-time data.”
Now that we know what artificial intelligence is, we can move forward and find out how it transforms the digital world. The use of artificial intelligence is every present and visible in our daily lives.
With the help of a machine and deep learning, artificial intelligence has found its way in computer vision systems, image processing, and voice recognition applications, transforming them in a way never seen before. If you want to know how Artificial Intelligence affects the digital world, this article will help you. Listed below are some of the applications of artificial intelligence in today’s digital world:
Computer Vision Systems
Computer vision analyzes data by using different images that show various objects of interest. It uses deep learning and image processing to recognize patterns and then provides predictions autonomously.
From simple everyday applications such as recognizing human faces to complicated ones such as detecting obstacles when driving autonomous vehicles, computer vision helps AI-enabled technologies and devices to perform their tasks more effectively.
An example of how AI affects computer vision systems is through its use in machine vision systems. A sub-field of computer vision systems, machine vision systems finds their use in automotive applications, such as detecting stop signs, detecting obstacles, etc. Machine vision technology reduces distractions and enables the driver to stay alert while driving.
Creating and Generating Online Content
Who wouldn’t want a machine that writes online content by itself? Although AI cannot write about their opinion for a political blog or its views about new emerging technologies, it certainly can create content for your website that can help attract an audience from every part of the world. It can also help you save money, resources, and a lot of time. You only need to feed it data that it can understand and learn, and it will take care of the rest.
Wordsmith and quill are examples of such programs, which companies such as Forbes and Associated Press use to create new and fresh content for them, leading to numerous visits on their websites. With the use of templates and keywords, these programs generate content readers feel that humans wrote it.
Curating Online Content
AI-based programs not only allow you to create content, but they also help you curate it. It enables visitors to interact with web pages in a better way, only showing them the content they want to see. It helps in providing visitors with more personalized user experience. For example, if you add a product to your shopping cart on Amazon, you will see suggestions relevant to your choice.
“Another example is Netflix. If you watch a movie or a drama serial on it, with the help of AI, Netflix provides you with relevant movie and drama suggestions that piques your interest.”
From a marketing perspective, imagine showing visitors the content they wish to see. With the help of deep learning and machine learning, you will surely increase your daily clicks.
Emphasizing user behavior and preferences, companies use AI-based marketing campaigns to make it easier to connect with potential clients. With the help of machine learning, companies can analyze trillions of megabytes of data to find out the time of day to engage with potential clients, what type of content to show them, the email titles and subjects that generate the most clicks, and its frequency.
Wouldn’t you want to know all these so you can save time, money, and effort? Some of the examples of such AI-based email marketing include Persado, Boomtrain, and Phrasee. It will transform how you perceive email marketing and allow you to generate tons of clicks, increasing your online presence.
Gone are the days of posting advertisements in the newspaper or the local radio channel. Artificial intelligence has made it easy for companies to find an audience that will be more prone to finding an interest in an advert. A sub-field of digital marketing, digital advertising sees the most benefits when adopting Artificial Intelligence.
“For example, Google Ads and Facebook Ads use Artificial Intelligence and machine learning to find people that will most likely have an interest in your Digital Adverts.”
With the help of AI, both these platforms analyze user information such as demographics and interests to detect users that suit a company’s advertisements.
If you think that a great website cannot exist without the help of a coder or a programmer, then we have news for you. Nowadays, various AI-aided website design programs exist that can easily design a website with the help of images, call to actions, and text provided by the user.
And all that without any need of a programmer or a website designer.It allows companies to save money and makes their website look like someone with a college degree designed it.
Artificial Intelligence Chatbots
Nowadays, brands usually communicate with their potential clients through Facebook messenger, WhatsApp, and other online communication platforms. As everybody already uses these platforms, it provides companies with a quick way to send the word out about their brand. Such a medium of communication leads to a requirement for faster responses. That is only possible through AI aided chatbots.
Chatbots are also available 24/7, which is not possible for a human being. For example, a big brand like Sephora uses chatbots to provide visitors with recommendations and make-up advice, depending on their interests, and without human intervention.
As you can see, artificial intelligence in the digital world provides numerous benefits, whether in marketing, advertising, or providing a great user experience to a customer. Also, to clarify, Artificial Intelligence is not here to replace human beings, but it helps them perform their task more effectively and efficiently.
However, for something like this to happen, they must give Artificial Intelligence a chance. Otherwise, they risk facing the inevitable.
Also Read Artificial Intelligence Myths and Facts
AI and Machine Learning Technologies Are On the Rise Globally, with Governments Launching Initiatives to Support Adoption: Report
Kate MacDonald, New Zealand Government Fellow at the World Economic Forum, and Lofred Madzou, Project Lead, AI and Machine Learning at the World Economic Forum have published a report that explains how AI can benefit everyone.
According to MacDonald and Madzou, artificial intelligence can improve the daily lives of just about everyone, however, we still need to address issues such as accuracy of AI applications, the degree of human control, transparency, bias and various privacy issues. The use of AI also needs to be “carefully and ethically managed,” MacDonald and Madzou recommend.
As mentioned in a blog post by MacDonald and Madzou:
“One way to [ensure ethical practice in AI] is to set up a national ‘Centre for Excellence’ to champion the ethical use of AI and help roll out training and awareness raising. A number of countries already have centres of excellence – those which don’t, should.”
The blog further notes:
“AI can be used to enhance the accuracy and efficiency of decision-making and to improve lives through new apps and services. It can be used to solve some of the thorny policy problems of climate change, infrastructure and healthcare. It is no surprise that governments are therefore looking at ways to build AI expertise and understanding, both within the public sector but also within the wider community.”
As noted by MacDonald and Madzou, the UK has established many “Office for AI” centers, which aim to support the responsible adoption of AI technologies for the benefit of everyone. These UK based centers ensure that AI is safe through proper governance, strong ethical foundations and “understanding of key issues such as the future of work.”
The work environment is changing rapidly, especially since the COVID-19 outbreak. Many people are now working remotely and Fintech companies have managed to raise a lot of capital to launch special services for professionals who may reside in a different jurisdiction than their employer. This can make it challenging for HR departments to take care of taxes, compliance, and other routine work procedures. That’s why companies have developed remote working solutions to support companies during these challenging times.
Many firms might now require advanced cybersecurity solutions that also depend on various AI and machine learning algorithms.
The blog post notes:
“AI Singapore is bringing together all Singapore-based research institutions and the AI ecosystem start-ups and companies to ‘catalyze, synergize and boost’ Singapore’s capability to power its digital economy. Its objective is to use AI to address major challenges currently affecting society and industry.”
As covered recently, AI and machine learning (ML) algorithms are increasingly being used to identify fraudulent transactions.
As reported in August 2020, the Hong Kong Institute for Monetary and Financial Research (HKIMR), the research segment of the Hong Kong Academy of Finance (AoF), had published a report on AI and banking. Entitled “Artificial Intelligence in Banking: The Changing Landscape in Compliance and Supervision,” the report seeks to provide insights on the long-term development strategy and direction of Hong Kong’s financial industry.
In Hong Kong, the use of AI in the banking industry is said to be expanding including “front-line businesses, risk management, and back-office operations.” The tech is poised to tackle tasks like credit assessments and fraud detection. As well, banks are using AI to better serve their customers.
Policymakers are also exploring the use of AI in improving compliance (Regtech) and supervisory operations (Suptech), something that is anticipated to be mutually beneficial to banks and regulators as it can lower the burden on the financial institution while streamlining the regulator process.
The blog by MacDonald and Madzou also mentions that India has established a Centre of Excellence in AI to enhance the delivery of AI government e-services. The blog noted that the Centre will serve as “a platform for innovation and act as a gateway to test and develop solutions and build capacity across government departments.”
The blog post added that Canada is notably the world’s first country to introduce a National AI Strategy, and to also establish various centers of excellence in AI research and innovation at local universities. The blog further states that “this investment in academics and researchers has built on Canada’s reputation as a leading AI research hub.”
MacDonald and Madzou also mentioned that Malta has launched the Malta Digital Innovation Authority, which serves as a regulatory body that handles governmental policies that focus on positioning Malta as a centre of excellence and innovation in digital technologies. The island country’s Innovation Authority is responsible for establishing and enforcing relevant standards while taking appropriate measures to ensure consumer protection.
Is GPT-3 the “Adam” of Natural Language?
OpenAI has long asserted that immense computational horsepower in conjunction with reinforcement learning is a necessary step on the road to AGI, or AI that can learn any task a human can .
The fathers of AI 2.0, such as Yoshua Bengio and Yann LeCun, argue that AGI is not possible to create from current AI technology. They think we need self-supervised learning (actually GPT-2 and GPT-3 are self-supervised) and advanced neurobiology-based advancements .
However, the fathers of AI 1.0, the grandfather’s of AI, such as Marvin Minsky and Andrew McCarthy, argued that an abundance of knowledge (data) and a “society” of common-sense reasoning specialists was the road to AGI .
GPT-3 is the existence proof that scaling up the amount of text (data), scaling up the parameters (model size), and scaling up the training computes results in better accuracy (scary performance) on a specialist for few-shot NLP tasks.
Do the model’s architecture, size of the model, and the amount of training computes realize a common-sense reasoning specialist? Do data and common sense reasoning get us to AGI?
Speculation About a Possible Future of Artificial Intelligence
So like, the biggest mistake that I see artificial intelligence researchers making is assuming that they’re intelligent. Yeah they’re not, compared to AI. — Elon Musk .
Sixty to sixty-five years ago, one of the first computers filled a room. Sixty years later, a computer core, about the size of my head, has scaled up about 1 billion times (maybe more) the first computer.
Suppose the first viable quantum computer fills an entire room. Will it be 60 years before a quantum computer core, the size of my head, scaled up about 1 billion times the first quantum computer?
Imagine a quantum computer, with an AGI (Artificial General Intelligence) model of a scale of 1 billion times the parameters of GPT-3 or about 3 million times the parameters of the human brain.
“I’ve predicted that in 2029, we will pass the Turing test,” stated Ray Kurzweil .
Note: GPT-3 is real close to GPT-3 passing the Turing test .
GPT-3 is quite impressive in some areas, and still clearly subhuman in others. — Kevin Lackey, Just, 2020.
Do you think we will have a Hawking-Musk nightmare or a Havens-Kurzweil dream [11,12]?
We may have both, or we may have neither.
I put money on our tool-making. I doubt we will change, or should we change this behavior.
I feel that Elon Musk, with the NuralLink project, is making a bet on our tool-making about the future potential of AI .
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