BlockchainIntel believes that blockchains are a big part of the future. We also believe blockchains enable financial freedom and governance unparalleled in traditional systems. In order for blockchains to flourish, it’s important to trust the person or machine you’re interacting with in a network and detect criminal abuse of the technology. BlockchainIntel provides evidence you need to trust the entity with whom you are transacting or exchanging confidential information.
With over 20 years of experience in software, Karen is a cryptocurrency miner and co-inventor of 5 patents. For years at BlockCypher, she worked with startups and enterprises early in the blockchain space to create applications that interoperated across permissioned and public blockchains. Before joining the blockchain industry, she led Data Quality, Data Integration and Data Science projects at companies such as Informatica and startups acquired by SAP and IBM. As part of these roles, she worked with financial standards organizations such as SWIFT, NACHA and ACORD. Karen co-founded BASES, one of the largest organizations at Stanford dedicated to entrepreneurship and remains on its Board. Karen co-founded Blockchain by Women to build diversity in and share current and reliable information to blockchain communities. Karen has a Bachelors of Science degree in Management Science and Engineering from Stanford University.
Chuck Lam is a serial entrepreneur and experienced technologist. After completing his PhD from Stanford on machine learning, Chuck used his data science expertise to build financial systems for micro-financing. He has been a big data pioneer, publishing Hadoop in Action in 2010, a book that teaches readers how to write simple programs and outlines best practices and design patterns. He also co-founded and sold RollCall, a mobile application to StubHub. At Stanford, he co-founded BASES, Business Association of Stanford Entrepreneurial Students, with Karen, and continues to be on its board today. Chuck holds 2 patents and has a Masters and PhD from Stanford in Electrical Engineering.
Dorothy specializes in Regulatory Compliance Policy & Procedures Implementation; Regulatory Compliance Monitoring & Audit; Enterprise-wide Regulatory Compliance Risk Assessment. She started her career at Union Bank, NA in both Lending Operations and Consumer Lending Compliance departments. Most recently, she has spent time focusing on BSA/AML/OFAC/CFT Compliance in relation to FinCEN's Money Service Business (MSB) Regulatory Requirements for Blockchain/Cryptocurrency/Virtual Currency. She has a Master of Business Administration – International Business Administration from National University, San Diego, California; and a Bachelor of Science in Business Administration from United States International University – Africa. She is a member of the Association of Certified Anti-Money Laundering Specialists (ACAMS) and holds the Certified Anti-Money Laundering Specialist (CAMS) certification.
Katya has deep technical expertise combined with experience in identifying and working with new business models. She completed both her M.S. and PhD in Electrical Engineering at Stanford University. After Stanford, Katya went to New Enterprise Associates (NEA), where she worked with a number of startups on their business and product plans. She then went to Data Domain which was acquired by EMC-- one of the largest and few acquisitions of that time. Katya also had executive roles at Ringcube Technologies, an early software virtualization provider and Atheros Communications, which was acquired by Qualcomm. Leveraging her expertise and experience with data, Katya has built financial systems and continues to add to BlockchainIntel's platform for blockchain analytics.
The Risk Score API provides a risk score for each entity, address and/or transaction. The score is based on the Blockchain Data Score™, known social media profiles and blockchain activity such as geographic location, fraud, and interactions with exchanges, mining pools, Darknet or other sites. For devices, the score is also based on data coming from the device itself and other industry data.
BlockchainIntel enables clients to customize the existing risk scoring methodology based on requirements. BlockchainIntel provides use case workshops, architecture reviews and application development as needed.
BlockchainIntel provides reports for one more addresses or transactions, in batch or real-time. See “Explore Crypto Scoring” for an example of scoring for a single cryptocurrency address. Examples of scoring for other blockchains can be supplied upon request.
Risk score testing will be performed in a test environment to ensure quality of scoring in production.