Do You Even Blockchain?

Blockchain buzz continues to drive intense interest in experimentation. But that fervor has cooled off significantly. Axios reported an 80% drop in the use of “blockchain” on corporate earnings calls in 2018. And a recent McKinsey article outlines “Blockchain’s Occam Problem.” The authors state that blockchain has failed to advance out of its early “pioneering stage” and the key to finding real value in blockchain is applying it when it’s the simplest solution available.

From the article:

“There is a clear sense that blockchain is a potential game-changer. However, there are also emerging doubts. A particular concern, given the amount of money and time spent, is that little of substance has been achieved. Of the many use cases, a large number are still at the idea stage, while others are in development but with no output. The bottom line is that despite billions of dollars of investment, and nearly as many headlines, evidence for a practical scalable use for blockchain is thin on the ground.”

Machine Learning vs Synthetic Fraud

One of Fuel’s most popular articles last year was about the emerging $20 billion dollar ID verification-as-a-service market. The need for innovation in biometric ID verification remains important. A recent McKinsey article states that “synthetic ID fraud” is now the fastest-growing form of financial crime in the USA. 

From the article: “Synthetic IDs are created by applying for credit using a combination of real and fake, or sometimes entirely fake, information. The application is typically rejected because the credit bureau cannot match the name in its records. However, the act of applying for credit automatically creates a credit file at the bureau in the name of the synthetic ID, so the fraudster can now set up accounts in this name and begin to build credit.”

The authors propose an approach that incorporates machine learning to uncover critical third-party data to verify if the info given matches that of a real person.

How AI Can Help Humanity

The World Economic Forum has a short write-up of McKinsey Global Institute research on how AI can help humanity. The 160 social-impact use cases are framed across the 17 UN sustainable development goals – aimed at helping hundreds of millions of people.

Among the examples highlighted in the research:

• Object-detection software and satellite imagery aided rescuers in Houston as they navigated the aftermath of Hurricane Harvey.
• In Africa, algorithms have helped reduce poaching in wildlife parks.
• In Denmark, voice-recognition programs are used in emergency calls to detect whether callers are experiencing cardiac arrest.

The MGI research concludes: “What we found is that AI could make a powerful contribution to resolving many types of societal challenges, but it is not a silver bullet – at least not yet. While AI’s reach is broad, development bottlenecks and application risks must be overcome before the benefits can be realized on a global scale.”

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