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The Credit Score Analogy; Part 2

Now we look for a similar situation for Knowledge Markets.

In the cuurent times, the hiring manager is the person to know if you want to get a job. The manager would read your resume and compare it with “bell curve” in their brain about what has worked or not worked in their past. This was a great system for the industrial economy, but it falls far short in the innovation economy.

The world is evolving so fast with new technology, new disciplines, and global cultures that what worked in the past may not work in the future. Innovation favors different combinations of knowledge where the Industrial economy favored similar knowledge. A hiring manager may not accumulate sufficient experience in a lifetime to make a proper assessment in the complexities of a diverse, global, and technical future market.

If we look in society, there are many vetting mechanism in place. Social networks are by far among the most exciting and important new technology that can serve this purpose. Social networks must now evolve to become a local vetting mechanism for knowledge assets.

Just like the reporting agencies in the credit system, Social Networks can serve an extremely valuable function in permitting human knowledge to emulate a financial instrument by acting as the “Recording Agencies” who have verified the asset in terms of quality and quantity. The knolwedge Inventory acts as the independent variables that are used to calculate the probability of market success. The difference is that the credit score measures mostly negative events while the new system will seek only positive events and can be designed to give the participants much greater influence on how they appear to the market.

One thing is missing. The credit score uses the FICO equation; Innovation Economics will use something called the Percentile Search Engine.

The Credit Score Analogy; Part 1

We have defined the currency, the factors of production, and the inventory of the Innovation Economy; we destroyed the old resume system and turned it into a computer language that makes knowledge appear like money in the eyes of the entrepreneur.

Now, we need a system that keeps the game free and fair. For example; EBay does little more than protect the feedback system, Craigslist uses community flagging, Linkedin keeps track of comments and contacts, etc. All markets must have a vetting mechanism in order to operate efficiently. Entrepreneurs do not invest in places without a good legal system and where property rights are not protected. When vetting fails, investors leave – It is that important.

In the Innovation Economy, the knowledge market is analogous to the credit market.

In the old days, the banker was the person to know if you wanted to be successful in town. If you needed to borrow money to start a business or buy a house, the banker would review your work history and financial records as well as your reputation in the community where you both live. If you were deemed an acceptable risk, the banker would lend you money from the deposits of local companies and individuals.

Then an engineer named Bill Fair and mathematician Earl Isaac created the first behavior scoring system to predict credit risk. They formed the Fair Isaac Corporation FICO and their invention came to be known as the FICO credit score. With the credit score, the local banker is almost irrelevant; now a Saudi Billionaire can lend money to a young couple in Boise to buy their first home – and neither of them are aware of the other. The credit score is responsible for the creation of a lot of wealth because it made many more entrepreneurs who invested borrowed money in business. The credit score even allows you to recover if you hit hard times – you just pay more a little interest until you prove yourself solvent again.

The credit score isolates about 22 or so measurements of financial activity and puts them on a bell curve relative to everyone else. These include how much debt you have, how much your assets are worth, your income, etc. These ratings are run through the FICO Equation and out pops your credit score. Anyone can now predict the likelihood that you will default on your obligation.

All of the data that feed FICO are collected from public records, your employer, and the people who you borrow money from – all of these organizations have a vested interest in a system of correct credit scores.

It is interesting that you and I do not compete for our credit score because it is not a ranking system. The old saying “No credit is worse than bad credit”, although inaccurate, is cited often because with bad credit, you are visible to the system and it can adjust to find a suitable interest rate. With no credit, you are simply invisible.

We lose some privacy with FICO, but we accept these terms well because they provides us with tremendous benefit to finance a business, automobile, or a home without needing to save cash. Likewise, we lose some privacy engaging each other on the Internet and in our community, however, the benefit of Social Networks far exceed many perceived privacy issues.

My personal complaint with credit scores is that they track largely negative events and seem to predict failure. What if we had a system that tracks success and used that data topredict varying degrees of success.

In the next section, we will identify the institutions that exist in society and how Social Networks can act to duplicate the benefits of the credit score without the downsides….watch

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