The American Dream: How artificial intelligence helps small business.
The Rafael del Pino Foundation organised, on 26 September 2019, the Master Conference ".The American Dream: How artificial intelligence helps small business."which was given by Karen MillsSenior Fellow at Harvard Business School, former member of President Barack Obama's Cabinet.
Following the lecture, Professor Mills spoke with Mercedes DelgadoProfessor at the Copenhagen Business School and research scientist at the MIT Innovation Initiative.
Karen Mills a Senior Fellow at Harvard Business School, worked until the arrival of President Trump in the White House executive team, known as the Cabinet of the United States. She was nominated by President Barack Obama to lead the U.S. Small Business Administration and was unanimously confirmed by the U.S. Senate. She is Chair of MMP Group, Vice Chair of Envoy, Chair of the Private Capital Research Institute's Advisory Committee, Co-Chair of the Bipartisan Policy Center's Main Street Finance Task Force and a member of the U.S. Securities and Exchange Commission's Small Business Capital Formation Advisory Committee, as well as the Milken Institute's Fintech Advisory Committee. He is also a member of the Board of Directors of the National Bureau of Economic Research and the Harvard Corporation. Karen G. Mills is an expert on competitiveness, entrepreneurship and innovation and an undisputed authority on the role of small and medium-sized enterprises in today's economy, a knowledge that she has poured into a number of publications, including her latest book "Fintech, Small Business & the American Dream. How Technology Is Transforming Lending and Shaping a New Era of Small Business Opportunity".
Summary:
On 26 September 2019, the Rafael del Pino Foundation hosted a conference by Karen G. Mills, Senior Fellow at Harvard Business School and former member of President Barack Obama's Cabinet, entitled "The American Dream: How artificial intelligence helps small and medium-sized enterprises". In his speech, Mills wanted to address two issues, which are related. The first is artificial intelligence. Many people think that the first way artificial intelligence will affect us is autonomous cars. This, however, still belongs to the distant future. By contrast, the impact of artificial intelligence on banking and, in particular, on small business banking is going to happen much sooner. Eighteen months from now, or at most two years from now, its effect on small business and consumer banking will be felt. The other thing I want to talk about is the importance of small businesses and the impact that artificial intelligence will have on them. For both of these reasons he wrote his book Fintech, Small Business & the American Dream: How Technology Is Transforming Lending and Shaping a New Era of Small Business Opportunity. The reason for doing so came ten years ago, when he was working in Barack Obama's administration as head of small business. One of the things that made the job difficult was the timing. I took the job in the first quarter of 2009, when the recession caused by the financial crisis started. The crisis hit SMEs much harder than large companies, so the job destruction was much more intense in SMEs. The reason for this different behaviour lies in the fact that, in financial crises, the companies that suffer most are those that are most dependent on credit. This is the case of small businesses. That is why the White House had to do something to help small businesses regain access to credit. To this end, a credit guarantee system was created for this type of company, which covered the 90% of the loan. The impact of this measure was immediate. More than a thousand banks in less than six months resumed lending to small businesses. This showed him the enormous degree of dependence on credit that these companies had, as well as the impact that can be generated by making credit available to them. Today, the importance of this issue can be fully appreciated when you consider that half of the people in the United States, and 70% in Spain, work for a small business. Despite this, governments and economists have not paid enough attention to small businesses. This is because governments and economists think of consumers first. Then they think about investment in equipment, which is mostly made by large companies. Then they think about public spending. That is why most large macroeconomic models tend to ignore small businesses. That is why it should be remembered that small businesses in Spain contribute 70% of employment and 90% of GDP. Another point to bear in mind with regard to small businesses is that, when we refer to them, we are not talking about Silicon Valley. What we are talking about are those small businesses that are part of people's daily lives. There are thirty million small businesses in the United States, twenty-four million of which have no employees. The latter segment, moreover, is growing because of the gig economy. Most of the remaining businesses are, for example, cafés, dry cleaners, etc. There is one particular segment that is important, which is small businesses that act as suppliers to other companies. This is a segment that needs particular attention because it is a segment that needs capital to be able to run its business. What is the problem? Banking has not changed in the last fifty or a hundred years. A small business asking for a loan needs to provide a pile of paperwork, which the bank goes through exhaustively. But because they can't see inside companies, they usually ask for personal guarantees to be able to grant the loan, because if they can't see inside companies, they can't know how small companies make money. This problem is known as information opacity. Technology, however, helps to solve it because, through big data, etc., it allows banks to see inside small businesses. The second cause of friction that hinders the financing of small businesses is the delay in the lending process, due to the time it takes to analyse a multitude of businesses all belonging to different sectors. The use of big data can be of great help, as it would provide the bank with information on hundreds of businesses in the same sector as the credit applicant and would allow it to know whether it is doing as well, better or worse than the others. Therefore, big data, machine learning and artificial intelligence can remove the barriers that hinder the lending process and, consequently, shorten it. Innovation, in the field of technology, starts very slowly. Then it accelerates and reaches maturity, but someone comes along and introduces a new disruption and the acceleration continues. In the case of banking, the first Fintech companies appeared in 2010. In 2014 it seemed that they were going to eat the world and that banks were doomed to disappear because they seemed unable to change. Banks, however, have great assets that they can mobilise against these new disruptors. In particular, they have two great assets that have proven to be very important. The first is their customer base. Fintech has spent a lot of time trying to attract customers who trust these companies when it comes to taking out a loan. The second asset is money. Banks have low-cost deposits that they use to lend money. Fintech, on the other hand, gets money from hedge funds, but that money is much more expensive. So the first Fintech companies had funding problems and were forced to retreat. Suddenly, however, the world was transformed by the entry of the big tech companies, such as Amazon, which became lenders to small businesses. Then banking woke up and started investing in technology. Who is going to win? Who is going to lose? The big banks, the big credit card companies, the big technology companies, the Fintech companies and the payment technology infrastructure companies are the four groups of players in this market. This is the environment, but we do not yet know who the winners will be. This transformation is taking place right now. It happens through APIs (application programming interfaces), which extract bank account data as well as credit card information. This information is put together in a black box in which algorithms can create intelligence that enables the transformation of the vision that a company offers. From this, lenders can immediately see on their screens the graph reflecting the creditworthiness of a credit applicant. This graphical representation can also be used in small businesses, for example, to predict cash flow. This is what it calls the small business utopia. In this case, the system uses the same information as banks, but to see what the cash flow is going to look like. This allows businesses to know in advance if they are going to need a loan and get early approval for it from the bank. By sharing the information, the bank, in turn, knows if the company is going to need that credit in two weeks because it can see the cash flow projection. This is going to be a big change for small businesses, because they will be able to avoid crises arising from a lack of liquidity at any given time. However, there is also a dark side to this. It is about what would happen if a company's or an individual's credit history, which is stored in the black box, contains an error. In that case, it would have to be corrected, as it is done now if one detects an error in one's account or in one's credit card charges. But what if the error is in the algorithm? Moreover, if the algorithm is locked down so that it cannot be accessed by third parties, where will regulators get the expertise they need to do their job? For example, how will they know how the machine makes its decisions? How will they know that there is no bias in the data? Finally, who owns the data? In Europe, the owner of the data is the customer. This is one of the key questions to determine the future evolution of Fintech and banking, because it will be necessary for customers to give permission to banks to use this data so that they can offer them better services. In the United States, on the other hand, things are not so clear-cut. There are seven federal regulators, plus two more in each of the fifty states, who can act on this issue. And they are not able to agree, so no progress is being made on regulation. To try to figure out where things are going to go in the future, three questions need to be asked. The first is who has the customers. Who has them are the big banks, the small banks, the credit card companies and the big technology companies. The second question is who provides the capital. Here the banks have an advantage, which is that they get the capital more cheaply through customer deposits. And the third question is who has the best technology. There are many technologies, but the key is who has the best structure; who understands algorithms, artificial intelligence, and who gets the best customers. And here the best are the big tech companies. So what is going to happen? First, technology is going to transform small business lending two to four years from now. Second, the winners will be the banks and the big technology companies because they operate at lower costs, because they are going to focus on specific products for small businesses and because they are going to create a lending relationship. This will happen because more creditworthy borrowers will get credit, because the customer experience will improve, and because illiquidity situations will be avoided. Third and finally, financial regulation regarding data ownership will determine the success of Fintech as an industry. But today regulators are not prepared to deal with corporate monopolies like Amazon, Paypal or Square.
The Rafael del Pino Foundation is not responsible for the comments, opinions or statements made by the people who participate in its activities and which are expressed as a result of their inalienable right to freedom of expression and under their sole responsibility. The contents included in the summary of this conference, written for the Rafael del Pino Foundation by Professor Emilio González, are the result of the debates held at the meeting held for this purpose at the Foundation and are the responsibility of the authors.
The Rafael del Pino Foundation is not responsible for any comments, opinions or statements made by third parties. In this respect, the FRP is not obliged to monitor the views expressed by such third parties who participate in its activities and which are expressed as a result of their inalienable right to freedom of expression and under their own responsibility. The contents included in the summary of this conference, written for the Rafael del Pino Foundation by Professor Emilio J. González, are the result of the discussions that took place during the conference organised for this purpose at the Foundation and are the sole responsibility of its authors.
