DISRUPTIVE INNOVATION

The recent wild roller coaster ride for Gamestop Corp. stock has made payment for retail order flow a hot topic. Missing from this conversation is the potential for a disruptive innovation to the benefit of both big retail orders and institutional orders. For retail investors with big orders to fill there is a huge cost in terms of the time required in using their brokerage firm’s online trading platform and continually trying to camouflage what they are trying to accomplish; especially important for thinly traded stocks. Otherwise, market participants engage in front running which technically is not illegal since they don’t know with certainty the exact size of the big retail orders.

Ideally, a new trading platform would allow big retail orders to connect with institutional orders and trade close to the midpoint of the bid-ask spread—a better price versus the status quo. Importantly, the time to complete the big retail order would be measured in seconds, not days. Of course, this would exclude payment for order flow although commissions could be charged due to the value delivered to customers. Note that existing SEC regulations fit the bid-ask market structure and ensure a “best price” for a tiny order that is meaningless to big retail investors.

LIQUIDITY BUILDER OVERVIEW

The problem is straightforward.

• The customer is knowledgeable about trading and wants to avoid payment for order flow due to the substantial size of the order to be filled.
• Online trading platforms entail a hugely expensive cost in terms of personal time.
• Ideal execution for the client would be a rapid fill of the entire order by matching with an institutional order at a price within the bid/ask spread. Such an execution deserves a significant commission consistent with the price achieved and the trading time saved.

Solution

• One patented concept is that at a specified limit price, priority is based, not on the time when the order was received, but on order size, which incentivizes placing larger orders. 
• Additional issued patent claims concern variable prices on limit orders depending on the number of shares traded and other technical details for new ways to facilitate the matching of institutional orders with large retail orders.
• The reason this platform would actually build liquidity is because of the preference given to the largest orders. In operation, a slight price advantage is achieved by the larger investors while the counterparty smaller investors achieve a very quick fill of their entire order.

Strategic Benefit and Implementation

A proven way to create substantial value in the New Economy is to successfully expand a trading platform business in which higher value is delivered to customers as the customer base expands. For example, MarketAxess Holdings developed a particularly successful trading platform for fixed income securities and will generate revenues in 2020 of about $660 million, yet the firm’s market value exceeds $20 billion due to its extraordinary profitability and competitive advantage.

The ideal implementation of the Liquidity Builder would involve a large brokerage firm with a large client base of investors with a need to efficiently trade larger orders. The Liquidity Builder platform would provide more liquidity and higher value to participants as more institutional investors and retail clients participated. A sensible approach is to begin by focusing solely on institutional trading via the Liquidity Builder platform. This approach would expedite building a business without the added complications of dealing with large retail orders, which involve a time delay due to securing SEC approval. A successful startup of the Liquidity Builder with institutional participants could be followed at a later date by expanding to include large retail orders.

SS&P PLATFORM

I have received approval from the Patent Office for patents involving three innovative ways (MONETIZER, OPTIMIZER, and ECONOMIZER) to use AI as part of a system to improve a consumer’s experiences in Search, Shop, and Pay. SS&P is unique in that three major innovations constitute a mutually reinforcing system to the ultimate benefit of consumers.

(1) MONETIZER
Managements of Google and other search engine providers have conflicting goals. Providing the most relevant data to users, as a practical matter, becomes secondary to accommodating companies that pay for preferential display of information about their products/services. The Monetizer takes a diametrically opposite approach by paying users for their information and searches.
Fees are earned by generating unique, AI-based value to advertisers. Particularly important for advertisers is an AI-derived probability that a consumer will purchase a particular product/service at a particular time.

Consumers benefit from a digital bank that stores purchasing units earned from past searches, past purchases, and provision of personal information (verified data such as ownership of cars and real estate plus non-verified data). In addition, the digital bank stores unexpired dynamic digital coupons, i.e., dynamic in the sense of variable coupon terms and variable expiration dates generated by real-time AI analyses.

(2) OPTIMIZER
At the same time that a consumer indicates (via search engine, online store or physical store, or phone app) an immediate interest in purchasing a particular product, both the product supplier and its competitors have the opportunity to win an auction for immediate delivery of a customized digital coupon (or advertisement) to the consumer. Consumer data enables AI to assist suppliers in quantitatively optimizing both a bid to provide a digital coupon and the terms offered as part of the digital coupon.

The fast-growing GetUpside app, https://www.youtube.com/watch?v=k38Og4vzzGk&t=187s, enables business operators to compete for the opportunity to send digital coupons to consumers for immediate use at gas stations and other local businesses. This is clear proof of concept that the Optimizer patents offer a practical means to build a platform business. In addition, this platform can be expanded to attract online consumers ready to purchase a wide variety of products or services.

In addition, the Optimizer’s claims cover hardware and software that offer advantages (including lower costs) to retail stores seeking to eliminate checkout lines. The Optimizer approach is a low-cost way for large stores like Walmart to scale the patented technology. These economic advantages compare favorably to the recently introduced Amazon’s GO concept that uses expensive cameras and software for small stores.
 
(3) ECONOMIZER
By eliminating usage of credit cards and the associated transaction fees, merchants can increase profits while enabling consumers to receive lower prices on their purchases. AI enables merchants to make decisions that optimize the expected value of future profits from each customer. By dynamically analyzing consumer data, including past purchases in the merchant’s store (online or retail), AI-assisted decisions are made as to how much to lower Economizer product prices and possibly, how much to adjust store credit limits for the customer.

At checkout, customers review the potential savings from the use of store credit and bank withdrawal if a purchase exceeds their credit limit. Customers then choose Economizer price or credit card price. Customers receive periodic updates that communicate the AI-determined future credit limits corresponding to different levels of future purchases.

The following figure illustrates how these three innovations are mutually reinforcing.

In conclusion, in addition to earning a share of the payment market, a major objective of the SS&P Platform is to gain share of the digital advertisement market which amounts to approximately $330 billion in 2019. A firm that implemented the SS&P Platform and earned a 2% share of the digital ad spend would achieve revenues of $6.6 billion.