What really is this "Managed Market Place" anyway?

I work for a division within eBay Inc. called "Managed Market Places". The name is a bit curious. I was asked, more than once and by range of people, what really "managed marketplace" is? Is it a new type of marketplace by eBay (no it is not!), is it a vertical/niche marketplace within eBay (no it is not!), some one on Quora even interpreted it as it means that eBay simply "manages" the marketplace as oppose to growing it! ( if this was the case why would eBay announce that to the whole word by labeling it as such?)

So then what exactly is MMP (as it is known internally) and why is it important?

the nature of the Internet lends itself perfectly to the basic concept of a "marketplace": a mechanism for buyer and seller to find each other. Marketplaces were and still are an important and growing part of the internet. The growing list of niche marketplaces include etsy, zarrly, odesk, airbnb, taskrabbit, yardsellr, zimride and many many more. (not to mention marketplaces from facebook, google, yahoo and other major players)

At the first glance, it looks simple enough: create a site that brings the parties to a transaction together (from buyer and seller of antique to two people who want to share a ride or a room), and either take a cut of the transaction or make money by advertising. This is indeed the basic concept behind a marketplace - or an unmanaged marketplace. Marketplace itself is not a party to any transaction. Buyer and seller deal with each other directly and take the risk (or bulk of the risk) of direct transaction. EBay operated, more or less, as an un-managed marketplace for a while too.

In managed marketplace on the other hand, neither party to a transaction takes a risk, in other word marketplace guarantees the success of transaction, no risk (at least ideally). Of course a managed marketplace can "manage" other aspect of interaction such as inventory, quantity, price, promotions etc. as well but for now we only focus on risk as it is the focus of eBay MMP as well.

The evolution of simple internet marketplaces to managed marketplaces is an important trend, as the Internet users become more sophisticated and demand more from services they use online. The AirBnB incident back in July of 2011 is a perfect illustration of how "unmanaged" marketplaces will be forced to offer a higher level of assurance/risk mitigation and become managed marketplaces.

What does it mean from systems and architecture point of view? Here are five main aspects that is particularly different in dealing with managed marketplaces

1- The first significant change is that of people's mind set: You have to see yourself in risk management business, or at least assume that risk management is a major part of your operations. What this changes first, and foremost, is that you now have to identify, assess, prioritize, mitigated (or plan to) and measure risk. In all likelihood all of these activities (and the tools and systems you need to perform them) are new to you if you are dealing with a simple/un-managed marketplace.
2- Central to any consumer risk management scheme is "Identity", and I don't mean OpenID or OAuth or SSO... I meant attribute, assurances, verification, accuracy, uniqueness or mapping a real world entity to a digital identity (Entity Resolution)
3- Data is the core to efficient risk management, and big data and your ability to collect and analysis them becomes central to your ability to operate the marketplace at a reasonable cost (minimum losses)
4- Coherent Architecture become even more important. Simply because your systems becomes more complex and more integrated. A simple marketplace is just that, a marketplace site/application. A managed marketplace would include identity provisioning and verification, risk definition, measurement, management at user and at transaction level, a system for filing claims and disputes, systems dealing with ever changing legal and business landscape that enforces what you can and can not do with data you collect and finally integrating all these system in a productive way (seamless but without coupling them)
5- Even Driven and Complex Event processing: This already has a big role in distributed system, but it plays more and more important role in distributed risk management. Real time assessment of risk becomes critical and due the cost/performance of risk assessment, incremental assessment or risk based on primitive and complex event generated over entire session (or even life time of a user) will be the only practical solution.

Recall and Precision: It is not how many bad guys you caught, it is how many good guys suffered

The measurement of "Recall and Precision" is front and center in all of our fraud prevention measures and algorithms, you can read a general description of this concept and the mathematical definition in Wikipedia, but I have had better luck explaining the concept with this example:

Imagine there is a band of armed rubbers (say 5 guys) in your town and you sent your best cops to round them up. After a day they come back arresting a group of men. How do know if they did a good job?

The obvious answer is whether they have arrested ALL the gang members. So the measurement is "how many gang members have they arrested?" in this regard 5 is better than 4 and 4 is better than 3. Simple

But is that enough? Let's imagine three out comes

1 - The cops came back having arrested 5 guys, all of them gang member. This is perfect, they arrested ALL the RIGHT people, and ZERO WRONG person, recall = Precision = 100%.

2 - The cops came back having arrested 10 guys, 5 gang members of 5 random and innocent guys. In this case recall=100% but precision is 50% - which in this case is clearly not acceptable (even worse they could have arrested all men in the community, recall still would be 100% but precision would be near zero - that is called Carpet Bombing)

3- The cops came back with 3 guys, all gang member, no innocent guys was arrested. In this case recall= 60% but precision=100% - this is called Proof Beyond the Reasonable Doubt i.e. a philosophy of design whereby it is better to let a bad guy go free then to harm a good guy.

In modeling risk and fraud and designing algorithms to prevent them, we always have to measure the algorithm based on their recall and precision. Low precision methods typically cost a lot in term of customer support and friction in user experience, low recall algorithms and method result in higher losses for the company.

in designing a Risk Management strategy, I tend to side with lower recall then lower precision and then manage the ratio of loss/revenue with the higher revenue generated by higher precision - or right customer who were let in.




What if the cops came back with 10 guys, 5 are gang members and 5 are innocent? in this case they arrested all gang members (100% catch rate or 100% recall) but