Public policy analyst Hugh Donahue and I have been chatting since just before the M2M Evolution Conference & Expo about the implications of existing computing capabilities for machine to machine (M2M). Now as a PhD, I have to warn you that the conversation goes deep, historical, long and thorough. I recommend grabbing a cup of coffee as you start to read this, and my true hope is that you respond and get Donahue in a dialogue. Most importantly, I think the meta message here is that Intellectual Property in a lot of fields is going to come into play in M2M, and for that reason alone we are a good read.
Carl Ford: Welcome, Hugh Donahue. You come to Crossfire Media and the Internet of Things through innovative communications and energy applications. Can you please tell us a little about your work?
Hugh Donahue: Thanks so much Carl, it’s really great to speak with you. The breadth of topics and depth of speakers’ domain competencies at the M2M Evolution Conference in Miami really impressed me. The conference’s concentrations on cognitive computing, standards setting for machine to machine connectivity, sensors, points of sale and supply chains, user-authorized data sharing, remote monitoring and control, medical monitoring, distributing real-time and near real-time intelligence across distributed networks to mobile users and manufacturing productivity all confirm big data as the crucial innovation of the 21st century. From all the momentum, capture, storage, search, sharing, transfer, analysis and visualization in their various iterations and applications will emerge comparably to steam in the 19th century and oil in the 20th, it certainly seems.
All these communications capabilities, applications and visions address ongoing work on communications and energy applications. Communications applications focus on monetizing data and information in financial markets; think also of such applications as financial asset tracking and metering, clarifying the net present value of risk in real time and near real-time.
Energy applications develop energy dispersing and absorbing technologies and energy generating technologies; think of them as both horizontal technologies reshaping specific industry segments, say coated fabrics, as well as vertical technologies redefining garments, interior design, the built environment and industries from security to architecture.
CF: Can you please elaborate on the subject of communications application? For instance, what do you mean by “financial asset tracking”? Also, how do you see these applications contributing to machine to machine adoption and deployment?
HD: Absolutely, I am advising Marketcore, an intellectual property (IP) firm, whose robust suite of IP equips information technology developers and engineers with untapped, new capabilities to employ and deploy big data to make generational contributions to finance through machine to machine connectivity. These reach to the consumer, a capability exceeding many financial data services providers.
Marketcore’s transformative IP brings transparency to largely opaque financial markets. Marketcore IP promotes liquidity and increases volumes of trades of bonds, contracts, insurance policies, lines of credit, loans or securities. Equipped with Marketcore IP, software developers and engineers will be able to systematize and modularize big data across many sectors at multiple points of intermediation in these multi-trillion dollar financial markets, either by leveraging existing relational data base and structured query language or by innovating with parallelization and search to create brand new big data functionalities.
With this IP, essentially, IT developers and engineers get both a sword and a shield: A sword to penetrate new markets, and the shield of patent protection to maximize first mover advantage. IT developers and engineers simply employ the IP in software to capture risk events and to present wide varieties of valuable information in real-time and near real-time through applications and programs across wireline and wireless networks to wireline and wireless displays, monitors, portable digital assistants and phones.
Smart electric metering is already deployed for electricity billing; asset tracking addresses physical products. Think of Marketcore as vastly more robust and orders of magnitude more dynamic.
CF: And what specifically is the Marketcore IP?
HD: Data repositories and transaction credit, which is Marketcore’s trademark term for incentives for risk-detailing revelations. All of its work focuses on risk assessment.
Data repositories comprehensively and dynamically framework risk detection by tracking valuation over the life of risk instruments and financial contracts from pre-trade inquiry through maturity or ultimate disposition with real-time and near real-time information and data. Data repositories essentially open up price discovery for software developers and engineers to add value with fresh information like pricing data, pending orders and executed trades in the value cycle of a financial contract. IT developers can create software that reveals and tracks the net present value of risks. Data repositories aggregate transaction credits, the second pillar of the IP.
Transaction credits generate risk information that does not currently exist -- creating phenomenal opportunities for IT engineers and developers -- by incenting information revelations. For instance, a market participant grants an incentive to other market participants to contribute updated information. Participants receive credits from the grantors of the credits to offset the cost of future transactions and/or to access system-generated analytics and other data to execute trades quicker and with vastly clearer risk due to the granular information that’s being revealed and shared for appropriate risk matching. Apply this to consumers (critical participants in consumer finance products, such as mortgages, auto loans, credit cards and peer-to-peer lending) and you can see the unique advantage: This inventive method has an optional and voluntary full market reach. Consumers can receive benefits for updating their intentions.
CF: That is quite interesting. So why do you think now is the time for machine to machine implementation by IT developers and engineers?
HD: The time is now for machine to machine because the technology is really coming out now, the M2M Internet, Internet of Things, etc. And as it so happens, development of the various applications of Marketcore’s IP express generational opportunities for M2M IT developers and engineers to exert meaningful, transformative impacts.
Marketcore IP creates an ontology for handling information. The suite of IP describes a “protected” space for those interested in capturing a control position of any aspect of the following: A risk matching machine that enables all sorts of financial transactions by looking at even the most complex risks; it creates a risk assessment platform for every type of “risk shedder” and “risk taker” in an enterprise through which risks are identified and aligned for transfer (i.e. matching), using incentives for disclosure; the incentives “buy” better pricing on either other transactions or information access; across the entire product life cycle, risks are determined, valued, scored, updated, revalued; the result is expressed and seen as a continuous near real-time revaluation of contracts for any level of risk management; iterations of the process create individualized “risk lenses” that facilitate analysis of individual (or grouped) risk components.
Think about it. Data repositories dynamically aggregate and sort all pertinent market data. Transaction credits not only make for appropriate risk matching between buyers and sellers, they also create new information, made possible by big data, indicating the causes for market moving decisions.
For instance, one market participant grants a transaction credit to another, and the second market participant reveals that he or she is transferring risk from one risk vehicle A for risk vehicle B at such and such a price point. Each transaction credit clarifies each risk transfer. All the transaction credits together combine to reveal risk tolerance, sensitivity and, crucially, marketplace preferences for risk vehicles. In this way, transaction credits become grounded, verifiable, real time indicators of market moving conduct and behavior.
The distinguishing values of the IP: IT developers and engineers will be able to manage relevant data and decision rights, which clarify causation, not simply correlation, in one place or in as many distinct places as they choose throughout value cycles by writing “protected” software that embody Marketcore IP.
Marketcore’s distinct strengths are especially timely due to the projected deployment of cognitive computing, as Erik Brynjolffson and Andrew McAfee chart so cogently noted in The Second Machine Age, and potentially disruptive developments in financial data markets as Aaron Tims discusses in the Institutional Investor.
Marketcore IP uniquely incorporates numerous opportunities for consumers across risk instruments and vehicles at many points in time, a crucial value-add for IT developers and programmers and their enterprises in financial data lines of business. There’s a demo of the system as it relates both to its architecture and to systemic risk detection.
The IP’s twice licensed, a significant litmus of value that occurs for less than 2 percent of patents.
CF: That is all huge. Hugh, can we assume that it can all be extended to other opportunities?
HD: Great question.
Device adoption
Any IT engineer or developer building applications with the Marketcore IP will inflect adoption of all kinds of displays, digital assistants, phones and sensors to convey and to alert users about the time-sensitive, potentially market-moving intelligence that appears likely to occur in huge cloud and network volumes.
Web Services
Marketcore IP enables big data Web services, said Ernest Tedesco, president of Web services firm Webesco. “Essentially, Marketcore enables IT developers and engineers to hybridize transaction platforms and risk assessment frameworks. If you think about it, before big data, broker dealers handled transacting and rating agencies managed risk assessment. Now, with big data, Marketcore IP positions web developers to offer web services that combine both capabilities in one place and to enable their users to continuously reevaluate contracts. Marketcore outpaces current Bloomberg and earlier Cantor machines; it’s big data on steroids. Totally transformative for Web services.”
Data Scientists
Any organization adopting Marketcore IP will enjoy competitive advantage hiring and retaining data scientists. The most talented data scientists will flock to it because the innovative challenges of developing big data to parse causation from correlation for trillions of dollars of assets in play are actually stimulating the brightest data scientists for the largest financial interests jump to launch or join an organization working the IP.
Bond Markets
There’s a huge demand for the transparency and information symmetry across financial markets, which IT developers and engineers can create with Marketcore IP. That’s because volatility is back and illiquidity in secondary markets is widespread. Investors are jittery that the Federal Reserve is stepping back from buying residential mortgage backed securities on the scale that has existed, roughly $100B/year for each of the five largest banks. That concern throws off investment in emerging markets, because there may be better bets in the U.S. If interest rates rise here in conjunction with the tapering of FED RMBS purchasing, investors will continue to pull out of emerging markets. Volatility expresses one feature of investor quandaries gaming these risks.
Just take a look at bonds. David M. Walker, honorary chairman of Marketcore and former comptroller general for Presidents Clinton and Bush, “Cracking the Risk Code: A Trifecta Win Is Finally Possible,” has a brilliant essay that describes what may result from deployment.
Walker’s an absolute genius, totally ethical, completely top shelf guy; had to be, running the Government Accountability Office all that time for two such different presidents.
Anyway, Walker points out that “despite record-setting volume in new issues in the primary market for corporate bonds only an estimated 2 percent of all outstanding issues trade annually. The Federal Reserve has bought in excess of $3 trillion in bonds since the start of the quantitative easing policy, creating holdings of more than $4 trillion. By comparison, the Fed owned less than $900 billion in bonds when the crisis began. In the very thin market of today, prices are not readily available for trades in excess of $500,000. Average bond volumes in the corporate bond market have dropped from a pre-crisis average of $700,000 to about $400,000 now, according to published reports last November. An important measure of secondary market liquidity has fallen much more. ….[B]lock trades, a focus of institutional holders, have fallen from 4 percent of outstanding U.S. corporate bonds to less than 0.5 percent. At the same time, the dollar volume of mortgages guaranteed by FNMA and FHLMC, numbering into the multiple trillions of dollars, represents roughly half of all mortgages outstanding. This is an obligation that the government would like to privatize if only there were a viable market.”
IT developers and engineers, followed by any kind of market maker, can directly stimulate liquidity across all these bond markets and instruments with the Marketcore IP -- ditto for the consumer loan markets.
Search and Parallelization
Search and parallelization technologies are the ways to go. As IT folks know, parallelization is the computational technique of breaking a task up into many thousands of independent parts and executing the pieces simultaneously followed by gathering the results after the fact. This is largely the technique that allows Google to search a terabyte-sized data file in less than a second by spreading the calculation over 5,000 or 10,000 processors.
Adoption paths and opportunities migrating to parallelization and search from relational data bases and structured query language are all manageable. Existing relational data base and structured query language operations can export key information (e.g. trade terms and conditions) into self-describing documents with thoroughly documented semantic structure. That structure can be standardized with something like Financial Products Markup Language – FpML -- so routines will exist to read the documents and extract the data needed to perform a specific task on the underlying entity (e.g. a specific trade.) And, “binders” come into play to perform this extraction and send the results to an appropriate process for execution if formats remain with no standard translation.
Most relational databases are designed to support this data export process. Third parties could participate and relational data base customers can write them as well often without the permission of the database vendor.
IT developers and engineers interested in big data would wisely check out risk analyst David M. Rowe, the top guy on all aspects of risk management and markets. David discusses parallelization and search innovations in “Beyond Relational Databases,” his current column Risk Magazine column.
Scalable, Extensible IP
As an extensible and scalable body of IP, Marketcore allows IT developers and players to play with incumbent relational databases and structured query language systems as well as new entrants deploying parallelization and search. Rowe has a great roadmap essay about it.
Stay tuned for Part 2 of this Q&A session with Donahue, which will go into more detail about big data, government regulation and IT engineers for the Internet of Things.
Edited by
Rachel Ramsey
