Artificial Intelligence (AI) with Supervised Learning | RegTech
May 23, 2018
3 Reasons Why AI Requires an Essential Human Component in RegTech
In the best interest of accurate data, enlisting a team of industry or topic-focused experts will give the AI the direction it needs to better analyze and classify data.
Machine learning explores algorithms that can learn from and make predictions on data. There are two types of machine learning: unsupervised and supervised learning. Unsupervised learning is when the task is to group a collection of unlabeled patterns into meaningful categories. This type of learning is typically associated with data mining and big data analytics. There are no labels assigned to the algorithm, leaving the machine to discover its own structure. This is useful in identifying hidden patterns and anomalies.
Supervised learning is when a collection of labeled patterns is provided, and the learning process is measured by the quality of labeling a newly encountered problem. With active learning, a computer can only obtain training levels for a limited set of instances but can optimize its choice of labels. It can be presented to the user for labeling.
On average, most AI algorithms are only about 80 percent accurate, which doesn’t live up to the business standards of accuracy. That leaves 20 percent flawed, which needs human input to bridge that gap. There is an inherent design flaw to any AI which does not use some human component in development. It is a general understanding that the most successful AI models use the 80:20 rule, where 80 percent is AI generated, and 20 percent is human input.
This human component is commonly referred to as “Human-in-the-Loop,” and is considered a best practice in the successful development of AI. The way it works is that machine learning makes the first attempt to process the data and it assigns a confidence score on how sure the algorithm is at making that judgment. If the confidence value is low, then it is flagged for one/many humans to help with the decision. Once humans make the decision, their judgments are fed back into the machine learning algorithm to make it smarter. Through active learning, the intelligence of the AI is strengthened, but the quality of the training data is taken in from human contributors. Some data analysis is specific and complex, such as the case with Financial Regulation. There are three major reasons why the human component is essential to AI integration in RegTech.
1. The evolving and complex nature of regulation is a tough subject matter to master.
AI in RegTech requires in-depth knowledge and understanding of the regulatory framework and how to read and interpret the text. In these types of fields, expertise is far more critical than the tool. However, if a tool could incorporate subject matter experts into the machine learning model, then the tool becomes exponentially more viable.
2. Expert-in-the-Loop takes Human-in-the-Loop to another level.
It makes use of expert contributors to train the machine while also flagging the machine’s errors. For example, a well-trained machine in the RegTech industry could eliminate countless hours a compliance officer takes in researching, reading, and interpreting regulations, by automatically classifying documents into topic-specific categories or extracting only the aspects of the document that have changed from the previous version.
The Expert-in-the-Loop model differs from Human-in-the-Loop in one major way: Human-in-the-Loop doesn’t differentiate between the aptitude level of the various participants to answer the particular question correctly. Human-in-the-Loop takes advantage of the “Law of Averages,” which states that if many people participate, the average response will yield the correct result. So the response from a high school student and a Ph.D. student would be weighed the same.
On the other hand, Expert-in-the-Loop, specifically looks at the experience level of the participant to determine how their result will be weighed. With Expert-in-the-Loop, a human is essentially supervising another human’s qualifications. While the cost is higher than both the Unsupervised and the Human-in-the-Loop models, the results of Expert-in-the-Loop models are proportionally more accurate, making them suitable for highly specialized and industry-specific topics.
3. Expert-in-the-Loop models are proportionally more accurate, making them suitable for highly specialized and industry-specific topics.
Companies leveraging AI realized that the need for expert input for document classification. In the best interest of accurate data, enlisting a team of industry or topic-focused experts will give the AI the direction it needs to better analyze and classify regulatory data. A high level of accuracy is required for use in security, banking, compliance and regulation, industries. With expert engagement, AI-based solutions should be able to create interactive graphs and trends. These provide marketing, IT and operational teams with a bird’s eye view of activity at whatever level they need.
The truth is, AI is reliant on its human counterpart in order to consistently improve its accuracy. Humans are using AI to increase efficiency and streamline analysis. The future holds endless possibilities for this evolving technology, and as long as it is guided by a human hand, it serves as a bridge to close the gap between information and the time it takes to compile results.
With more than 25 years of experience in hi-tech, Kayvan leads operations, strategy, sales, and marketing for Compliance.ai. Most recently, Kayvan led the identity strategy at RSA, and represented EMC on various industry alliances such as the FIDO board. He is Co-Founder and CEO of PassBan (acquired by RSA), a company focused on mobile identity assurance. Kayvan also led strategy at LiteScape (as CTO and later as CEO), creating security and mobile identity solutions for VOIP based networks. He was Co-Founder and CTO at BeNotified, a cloud mobile communication service provider.
Asif Alam
CEO & Board Member
Asif Alam is the Chief Executive Officer at Compliance.ai. A leader in shaping disruptive technology, his experience includes building products using AI and natural language processing for GRC, payments, lending, risk, trading, and new solutions, from Fortune 500 companies to startups.
In his most recent role, he served as the Chief Strategy Officer of ThoughtTrace, unlocking new revenue streams and markets, and reignite portfolio growth. ThoughTrace was then acquired by Thomson Reuters in 2021.
He brings more than 20 years of management and business experience; increasing profitability, unlocking new revenue streams and markets, and reignite portfolio growth for companies like Thomson Reuters, Crux Informatics, and Finastra. Asif is a forward-thinking expert driving engagement via client forums, public presentations, and white papers.
Cesar Lee is a Principal at WRV, a venture capital fund focused on early-stage investments in hardware, semiconductor, and other technology-related companies. Previously, he was an investment professional at Riverwood Capital, a technology-focused, late-stage venture capital, and private equity fund. He began his career at RBC Capital Markets, where he was part of the Mergers & Acquisitions group for two years and the Equity-linked & Derivatives group for one year. While at RBC, Cesar spent a majority of his time working on M&A advisory transactions for technology companies.
Cesar’s investment experience includes buyouts, later stage, early stage and seed rounds. Cesar has completed transaction in the U.S., Latin America, and Asia, and in technology sectors including data centers, software, semiconductors, consumer electronics, robotics, big data, and internet.
Maria Devassy is a RegTech, Content, and Technology leader with over 20 years of experience helping companies bridge the gap between technology, product, and business. Maria has held leadership positions with MetricStream, KPMG, Oracle Corporation, and other technology companies. She has launched several successful RegTech products, business partnerships, and advised Fortune 100 clients on risk management, audit, advisory, and compliance business across Industries.
Hugh Cadden is a recognized expert in derivative financial and trading markets including futures, options, and swaps. Hugh is currently a senior consultant and expert with OnPoint Analytics, Inc. an economic, finance and statistical consultancy specializing in expert testimony for complex litigation. He has been specializing in the organization, operation, and regulation of financial and trading markets for over 40 years. Hugh’s experience includes both the public and private sectors and he has held senior level positions with the U.S. Commodity Futures Trading Commission including serving as Director of the Division of Trading and Markets and Deputy Director of Enforcement. He has been qualified as an expert on financial and trading market matters before the Commodity Futures Trading Commission, the Securities and Exchange Commission, the U.S. Tax Court, Financial Industry Regulatory Authority, National Futures Association, American Arbitration Association and federal courts.
Drake Ross is a former bank regulator who specialized in compliance with consumer protection regulations while at the OCC, FDIC, and OTS. While at these agencies, he provided extensive training and guidance and developed materials to ensure full comprehension and proper application of rules, laws, policies, and guidance, and served as a Subject Matter Expert in numerous areas. Because of his expertise, he often presented at agency and industry events. He also played a significant role in successful windup of the 2008 IndyMac Bank failure, where because of his extensive knowledge of the FDIC deposit insurance regulations, he was called upon to administer highly-complex insurance determinations.
Carliss Chatman is an Assistant Professor of Law teaching Contracts, Agency and Unincorporated Entities, Corporations, and Transactional Skills. Her work is influenced by over two decades of service on non-profit boards and involvement with community organizations. Through leadership positions, she has developed expertise in corporate governance and non-profit regulation. She has also been instrumental in strategic planning and fundraising efforts. Prior to law teaching, Professor Chatman was a commercial litigation attorney in Houston, Texas. In practice, she focused on trial law, appeals and arbitration in pharmaceutical, health care, mass torts, product liability, as well as oil, gas, and mineral law. In addition to negotiating settlements and obtaining successful verdicts, Professor Chatman has also analyzed and drafted position statements regarding the constitutionality of statutes and the impact of statutory revisions for presentation to the Texas Legislature.
Sign me up for all regulatory updates
Get access to EITL Forum recordings
Mariam is an Operating Principal at Cota Capital. Mariam has experience providing guidance on strategic and operational planning to Venture and Growth stage companies. Prior to Cota Capital, Mariam spent her career in management consulting as a Director at KPMG. She has experience leading global transformation programs and developing innovative service offerings for Fortune 500 companies in the Technology sector. Mariam has an MBA from UCLA’s Anderson school of management with an emphasis in Finance and Entrepreneurship. She has a Bachelors in Science in Finance and a Bachelors in Science in Economics from Santa Clara University.
Chris Callison-Burch is an Associate Professor in Computer and Information Science Department at the University of Pennsylvania. His research interests include natural language understanding and crowdsourcing. He has served the Association for Computational Linguistics as the General Chair for the ACL 2017 conference, as an action editor for the Transactions of the ACL, as an editorial board member for the Computational Linguistics journal, and an officer for NAACL (the North American chapter of the ACL) and for SIGDAT (the special interest group for linguistic data and corpus-based approaches to natural language processing)
Tom Ladt is an experienced executive and investor. Tom has lead and served on the boards of several public and private companies serving highly regulated industries such as technology, healthcare, real estate, and food processing. Tom has also served in key governmental roles and on numerous community boards.
Jeroen Plink is a global executive with a proven track record of developing and growing businesses, teams, and technologies with innovation and passion. Jeroen was CEO of Practical Law US during its acquisition by Thomson Reuters. He now serves on numerous boards and acts as a strategic consultants for start-ups.
Global Legal and Compliance executive with 15+ years of success in the SaaS technology and financial services industries. Partner to the CEO and executive team in corporate transactions, business development, product expansion, and regulatory navigation during periods of intense growth and organizational change. An advocate of effective risk management that starts with sound business practices and putting the customer first.
Richard Dupree has held multiple Risk, Compliance and Operations positions at regional, national, and global financial services firms including Wells Fargo, Silicon Valley Bank, Bank of the West and BNP Paribas. Rick currently advises FinTechs and RegTechs and sits on industry panels, contributes to industry whitepapers, thought leadership efforts, and speaks at industry seminars on Risk and Compliance challenges faced by banks and FinTechs.
Brian advises clients on legal and regulatory compliance in the financial, tech, and procurement sectors. His passion is helping businesses succeed in heavily regulated environments. As counsel and trusted advisor to businesses of all sizes, and as a former regulator, policymaker, and federal official, Brian acutely understands the unintended burdens that even well-intentioned government requirements can put on innovation and business growth, as well as how to create policies that strike the right balance.
Brian served as National Ombudsman in the Obama Administration, leading the federal Office of Regulatory Enforcement Fairness in assisting hundreds of startups, entrepreneurs, and small business owners in every industry and every state.
Dr. Marsha Ershaghi Hames is Managing Director of Strategy & Development at LRN, a leader in advising and educating organizations about ethics and regulatory compliance, as well as corporate culture, governance and leadership. With the focus of inspired behavior versus required behavior, LRN is a leading voice in the industry for companies to build ethical cultures instead of “check-the-box” compliance approaches. She’s advised Department of Justice corporate monitors on successful program transformation under CIAs (Corporate Integrity Agreements. With over 20 years of experience in leading multinational ethics and compliance strategies, Marsha has become a highly sought-after thought leader on leading Corporate Compliance and Ethics practices.
Carla Carriveau is currently the Senior Managing Counsel at Wealthfront, an automatic investment service firm in Redwood City, California. Carla was previously Senior Counsel, Division of Trading and Markets, at the United States Securities and Exchange Commission. As a former regulator with over 15 years of experience in helping small businesses navigate legal and regulatory needs in the financial services sector, Carla advises Compliance.ai on financial services regulation, the regulatory landscape and industry practices.
Automatically monitor regulatory updates to map to your internal policies, procesures and controls. Learn More
