Open source project & research paper: Blockchain proof of concept

Late last year I wrote a small paper (for my MBA program) and developed an accompanying proof of concept (Javascript/Node/P2P) on the implementation of blockchain in the retail or food distribution network around protecting goods from food fraud.

Source Code: https://github.com/paschmann/blockchain_origin

Abstract

Food fraud is a crime which has the potential to negatively affect the brand image, financial resources and impact multiple parties in the supply chain paradigm of food distribution. The ability to track and trace the origin and touch points of products throughout the network is imperative to limit the impact caused by a food fraud incident or a food safety issue. Blockchain has the potential to disrupt multiple industries by providing a shared and trusted ledger of transactions which no single company controls. One practical application of blockchain is utilizing the platform as a static register – a distributed database for storing reference data. In this paper I will describe a technical implementation of a blockchain in a practical scenario which shares the details and a proof of concept of a food origin scenario. The implementation will share a simplistic JavaScript application of a digital ledger based blockchain allowing manufacturers to register data on the food origin in the static registry and vested parties the ability to augment and view the data for the purpose of traceability and accuracy. read more

King Kullen

It’s a relevant and intriguing story of how one employee at Kroger, Michael Kullen, wrote a 6 page letter to a Kroger VP, encouraging them to consider a different business model. He was not taken seriously, resigned from Kroger and opened his own grocery chain called King Kullen. It is considered Americas First Supermarket due to it having separate departments; self-service; discount pricing; chain marketing; and volume dealing. In 2007 King Kullen had revenues of $800 million and operates 32 stores in New York state.

Side project: Golfedout.com

Like a lot of my side projects, golfedout.com was built out of a personal need. Golfedout is intended to track the variety of golf courses I have played over the last 6 or 7 years since I took up the game a little more seriously. When I started the project it was a simple list of courses, and then evolved into a more elaborate application which allowed you to follow other golfers, partake in a leader board, view course details such as architects or addresses and I also added a gamification aspect. Another aspect I was interested in, is how many of the top 100 golf courses have I played? How many PGA tour courses have I played? In the end I believe I may have made golfedout.com considerably more complex than others might have needed. If you are a avid golfed or interested, here is a link to my golfedout.com profile: https://golfedout.com/profile/rangerat read more

Dee Hock (Visa) – Quote

I like this quote from the founder and CEO of Visa. I believe “thinking out of the box” is a challenge for many of us when your mind is fulled with preconceived notions and ideas. I am also reasonably convinced there is strong correlation between the longer you continue to use and believe the existing ideas, the harder it is to get them out …

Open Source Project: Rasa UI

Rasa is an open source machine learning framework to automate text-and voice-based conversations.

Rasa UI is a web application built on top of, and for Rasa. Rasa UI provides a web application to quickly and easily be able to create and manage bots, NLU components (Regex, Examples, Entities, Intents, etc.) and Core components (Stories, Actions, Responses, etc.) through a web interface. It also provides some convenience features for Rasa, like training and loading your models, monitoring usage or viewing logs.

I developed Rasa UI to help me manage my bots as well as creating and managing the training data. The app is developed on NodeJS, and uses a simple SQLite DB for persistence (previously PostgresDB). read more

Lending Club Data Analysis

LendingClub is a US peer-to-peer lending company headquartered in San Francisco, California, and has helped over 2.5 million customers simplify their finances in the last 10 years. LendingClub improves the loan process for borrows by offering a fast and easy online application. For investors, the company offers historical returns of 3 – 8% and anyone can invest with as little as $1000 [1].

Because LendingClub relies heavily on technology to evaluate their borrowers, getting an accurate risk analysis for each applicant requires systems which can quickly assess the applications, and upon approval, offer these loans to interested investors at a given interest rate. Of the $7.9 billion dollars loaned in 2018, $233 million was written off as defaulted loans. While this may seem insignificant at 2.9%, this does represent risks and losses which investors and the company would prefer to avoid. In order to mitigate risk, lending companies traditionally apply a fitting interest rate to each loan. For example, loans for a home or a car may have lower interest rates because the risk is reduced due to directly related collateral. In another example, someone with a poor credit history or having declared bankruptcy may have a higher interest rate due to the inherent risk of history repeating. read more

Springwise Ideas

If there has been one email/newsletter I am excited to receive monthly, its from a company called Springwise. They share innovative and creative ideas from around the world. It’s a great resource to find inspiration or follow emerging trends which you are interested in. A prime example: Snapchat 🙂