Next, financial analysts review the impact of Artificial Intelligence on Capital Markets. House Financial Services subcommittee examined ais impact on minorities. Cyber security measures, encouraging more young people to Study Technology and how the us can remainglobally competitive. The task force will come to order. Without objection the chair is authorized todeclare a recess at any time without objection. Members of the full committee not on this task force are authorized to participate in todays hearing. This hearing is entitled robust onwall street, the impact of ai on Capital Markets and jobs and the Financial Services industry. The chair will now recognize himself or five minutes or an Opening Statement area thank you all for joining us today for what should be avery interesting hearing of this task force. Today were looking at exploring how ai is being deployed at Capital Markets from automated trading to Portfolio Allocation to Investment Management decisions. Were going to consider how the use of this technology is changing the nature of work in Financial Services and rendering some jobs obsolete and changing the skill sets needed to excel in others. It would not be much of an exaggeration to say wall street quite literally is run by computers. Long gone are the days when traders would be screaming orders on the floor of the stock exchange, financial analysts would use the ical chelators and pour over the tickertape to glean insights into a companys value. I hear about those days from the limo driver who takes me back used to be a floor trader on the market. Today, trades are automated and orders are executed in milliseconds or microseconds. The path of ots relying on algorithm models to ensure the one holding and shares are properly weighted to whatever index or benchmark its tracking. Hedge funds use algorithms thats. Scour all sorts of market data to find the stocks and have the most momentum or highest dividends or look for correlations that will in the market and an external data feeds to provide the most now you for investors. And i think its notable that a lot of the shakeout that were seeing in those markets is really a question of serving winner take all nature of digital economies that any Digital Business purely Digital Business is an actual monopoly and is as more plans become digitized you will see more of the rewards go to a smaller number of dominant players. Id like to emphasize it doesnt mean theyre evil, its simply a natural reflection of the nature of the digital marketplace. Other Asset Managers may use algorithms to form complex research and analysis in realtime on big data sets this can include towering of social media sites, satellite information, web traffic, onlinetransactions and just about anything else you can think of. This is i guess good in terms of having the market reflect all known data but there are abusive corners. Imagine what it would be worth if you had a 10 second early look at trumps twitter feed. How much money you canmake trading off that for example. The three types of computer managed index funds and quantum funds make up 35 percent of the approximately 31 trillion American Public equities market area human managers such as trench funds and other managed 24 percent of the market. The rise of the computerization of our stock market has a number of benefits, the cost of executing trades has gone down sometimes to zero dollars and theres more liquidity in the market. Funds charge less than one percent of management while active managers charge 20 times thatmuch. It certainly creates additional questions as well. As in the 2010 last crash and the more recent many flash scratches have shown Algorithmic Trading can sometimes cause unpredictable consequences that create market volatility and also exacerbate information asymmetry between different types of investors as firms with more and fasteraccess to enormous data sets are able to obtain a competitive advantage. Another broader question is how these developments are impacting the nature of jobs in the Financial Services industry. Recent Wells Fargo Research report estimated technological efficiencies would result in about 200,000 job cuts over the next decade in the us banking industry. While these cuts will certainly affect backoffice call center and Customer Service positions the pain will be widespread. Many frontoffice workers such as financial analysts could see their headcount drop by almost a third according to a mckinsey and Company Report released this year. The report found that 40 percent of existing jobs and Financial Firms could be automated with current technology. If you spend your whole day staring at a big screen and particularly if youre receiving a large paycheck your job will be at risk area understanding the skills that will be needed to excel in the Financial Services industry and how we can encourage these skills is one of the issues that we must tackle head on and tackle early area in a world where many functions can be done by automated ai models, what role did that leave for humans . I look forward to hearing from our witnesses on these issues with that i like to recognize the Ranking Member my friend from georgia mister loudermilk for five minutes. I want to thank each of our witnesses here today. Thank you for taking time to be here to discuss this issue while the rest of america is fixated on other things going on here. This is something that may not resonate on themajor networks but it is something thats very important , has an impact on our lives positively but also potentially negatively and its important we be looking into this. And as you note today the task force will examine the intersection between technology and the Capital Markets. In recent years there have been many Technological Developments including the adoption of Artificial Intelligence and automation that have redefined and reshaped trading and investing. The first trades on the New York Stock Exchange were made in the late 1700s using a manual paper intensive process. For many years buyers and sellers communicated about orders over the phone. Today trading and investing are done on digital platforms and investors can trade securities from anywhere in the world using modern technology. Trading has benefited the markets in many ways it has been positive for investors by leading to lower overhead and transaction cost which has contributed to investment returns over the last decade. Avril major asset managementfirms offer zero percent commissions which means investors can buy and sell stocks essentially for free and can capture more of the growth of their investments. This would not be possible without electronic trading area Digital Trading platforms provided investors with lowcost Financial Research and advice 24 hours a day using robo advisors. Electronic trading also makes markets more efficient by allowing faster searches for prices, better processing of large sets of data and more transparent price information. A proliferation of technology and lower firms barriers to entry, foster more competition and increase Market Access for investors. In addition to these core benefits there are many other cases of Companies Using ai to improve efficiencies in the Capital Markets in unique ways. For example some Clearing Companies are using ai to optimize the settlement of trades and enhance Cyber Security and fraud protection. Some selfregulatory organizations are also using ai in market surveillance while there are many benefits to electronic trading it can also present new challenges. One challenge which is at the forefront of our discussion today is the disruption of job markets. While the rise of automated trading has displaced many floor traders, Job Opportunities like code writing, cloud management, telecommunications, Data Analysis are growing area there is some concern highfrequency trading can contribute to volatility but new evidence suggests highfrequency trading does not increase volatility and can improve liquidity theres also some concern that firms dont have the latest technology , firms that dont have the latest technology could be competed out of the markets reared its important to keep in mind not all types of electronic trading are the same and i look forward to learning more from the witnesses about the differences between automated trading , Algorithmic Trading, highfrequency trading and Computer Trading and i look forward to exploring the legislative and regulatory issues in this space. One issue i think needs to be addressed is the protection of source code because algorithms are traders core intellectual property. They must be protected. We passed out a bill of this committee in the house on a bipartisan basis last time to ensure the Security ExchangeCommission Issues a subpoena before obtaining these other rhythms rather than getting themthrough a routine exam andmister chairman, i hope we will be able to Work Together on a bill this congress. I think you and i yelled back. Thank you and today were welcoming the testimony of doctor mcilwain, vice provost for development and professor of mediaculture and communication at nyu. Doctor marcos lopez de prado, Cornell University and chief Investment Officer of true positive technologies. Ms. Rebecca offender, cfa, senior director of finance at charterfinancial analysts. Miss kiersten wagner, chief executive officer modern markets initiative. Miss martin rachel, head of affect market surveillance, Nasdaq Stock Market area witnesses are reminded that your oral testimony will be limited to five minutes and without objection your full written statement be made part of the record. Doctor mullaney, youre now recognized for five minutes to give an oral presentation of your testimony. Chairman foster and Ranking Member loudermilk, thank you for inviting me to testify. While my written remarks cover 14 areas focused on two. The implications of automation on the workforce and mitigating algorithmic discrimination. We have ample reason to be concerned about automations future in the Financial Services sector. First, the Financial Services sector is right or automation. Second, the sector is on the rise, the large number of workers will likely be be displaced in the Financial Services sector even if automation and Ai Development is projected to create new types of jobs area if all this is true and the cost of concern is clear. It lies with the fact that africanamerican workers and latin workers are unrepresented in the Financial Servicessector workforce. African americans , hispanics and asians take up 22 percent of the Financial Service industry workforce. Africanamerican representation in the Financial Services sector at entrylevel and seniorlevel jobs climbed from 2007 to 2015, less than 3. 5 percent of all Financial Planners in the us are black or lacking. African americans make up 4. 4 and hispanics 2. 9 of the securities actor. Asians take up just 2. 8 of the central banking and insurance subsets. My point is simple. Racial groups that are already extremely underrepresented in the Financial Services industry will be most at risk in terms of automation and escalation of development. This is especially true given the vast underrepresentation Latin Americans in the adjacent Technology Sector workforce. If we are to mitigate the likelihood automation will disproportionately and negatively affect those already underrepresented in the Financial Services industry, you must plan ahead long into the future rather than allowing the market to run its course towards predictable outcomes. Now to the subject of deterring algorithmic bias. Certainly one way to mitigate the algorithmic bias is to develop best practices by instructing and deploying algorithmic systems, providing more oversight from industry, government and nongovernment bodies are able to assess how much systems are used and the outcomes they produce area this includes Technical Solutions and make algorithms more transparent and mitigate against potential biases before such systems gain widespread use rather than trying to simply correct their effects once their damage is done but i want to emphasize that especially when it comes to mitigating the potential disparate outcomes that biased algorithms might have on individuals and communities of color, a simple reliance on technical face axis is not a complete solution. I want to end by drawing on the wisdom of mayor ruskin, a formal civil rights leader who had a sophisticated understanding of algorithmic systems as they existed in his time. He said today the unskilled and semiskilled workers the victim but cyber nation invades the strongholds of the american middle class as once proud whitecollar workers begin sinking into the alienatedworld of the american underclass and as the newborn meets the old poor we find out automation is a curse ,but it is not the only curse. The chief problem is not automation but social injustice itself. Take as a final example the findings from a recent National Bureau of Economic Research study titled Consumer Lending discrimination and the thin tech era. Their researchers sought to determine whether an algorithmic system could reduce discrimination in mortgage lending as compared to traditional face to face lending process. Their findings were mixed area the system gets discriminated 20 percent less but the process still discriminated against a large number of applicants. Further even though the algorithmic system did not on balance effeminate in terms of loan approval it did discriminate against black and latin users in terms of price. One of the key conclusions of the study states that both thin tech and facetoface lenders may discriminate through pricing stress, we are just scratching the surface of the role of Pricing Strategy discrimination and the algorithmic area of data use. In short algorithmic lending me reduce facetoface lenders and it is not sufficient toeliminate discrimination and lower pricing. Even with the aid of a fair accurate and transparent algorithmic system, racial disseminationprocess. Iq again for allowing me the opportunity to contribute. Thank you and doctor lopez de prado you arerecognized for five minutes. Chairman. Ranking member loudermilk and distinguished members of this task force. Its an honor to be asked to contribute today. As a result of recent advances in supercomputing and big data today Machine Learning algorithms perform tasks that until recently only computers can accomplish. One area as investments. For two reasons, some of the most accessible trades in history happened to be algorithmic area their decisions are objective, their producible and can improve over time. The distinct advantage is their commission enables cost reductions. A committed task includes order execution, construction, forecasting, Credit Rating and protection and it creates a number of challenges for over 6 Million People employed in the finance and insurance industry, many of whom will lose their jobs not because they will be replaced by machines because they have not been trained to work alongside algorithms. The returning of these workers is an urgent and difficult task but not everything is bad news. These skills and become more important than privileged upbringing or genders and other classifications should narrow. It could be a great equalizer. Retraining our existing workforce is of particular importance but it is not enough. We must make sure that the talent that american universities have contributed and develop remains in our country. The next google, amazon or apple is at this morning attending a class at one of our universities and what unlike in the past , these entrepreneurs are in our country on a student visa and they will have a very hard time remaining in the United States to help them. And as we help them they will return to their countries of origin. We their fellowstudents compete against us. On a different note i would like to draw your attention to two practical examples of fintech thro