In his recent Harvard Business Review article Forget Citibank – Borrow from Bob John Sviokla talks about how in the current credit squeeze peer-to-peer lending will not only become more popular, but will also be embraced by some of the traditional lenders.

For another, peer-to-peer lending is cheaper than consumer credit. Lending Club’s rate for the best credit risks is 7.88%, whereas the bank rate for personal loans, on average, is over 13%. A credit-worthy borrower gets the money faster and for 5% less.

Why now? First, the internet and social networks enable peer-to-peer interaction on an unprecedented scale. Second, electronic mechanisms for assessing potential customers are emerging. Lending Club starts with traditional credit scoring and adds a proprietary assessment of customers’ reputations within their social networks. You may think of Facebook as fun and games, but important underwriting information is hidden in there for those who know how to look.

What we have here is a classic case of two alternative ‘business designs’ satisfying the same function (see my earlier post on the 3F’s of Business Design) - the function here being collecting money from people who have an ‘excess’ of cash and giving them to people who need them. In the bargain, the person willing to leave the money in the bank for safe-keeping gets an interest (i.e., savings rate) and the person borrowing money from the bank has to pay an interest (i.e., lending rate) to the bank that lends it. For the privilege of mediating this transaction the bank gets a good slice of the difference between these two rates (i.e., the spread). In a peer-to-peer lending, institutions such as Lending Club and Zopa play a similar function.

However, there are two fundamental differences between these two models: (a) How they make profits or Profit Patterns? and (b) How they use information or information patterns to generate these profits?

Profit Patterns: The form (one of the 3F’s from my earlier post) of the traditional lending and peer-to-peer lending are entirely different. In the case of traditional lending there is a big ‘distance’ between the organizational area that sources these funds (e.g., customer deposits or savings accounts) and the destination for these funds (e.g., consumer loans). In fact, given that money is a ‘fungible’ resource, matching the source and destination is not needed and does not occur in traditional lending. However, in peer-to-peer lending the ‘distance’ between the source of funds and destination of funds is very small – in fact, the lender can hand-pick the borrower to whom he or she is lending. This leads to a fundamentally different way of making money or ‘profit pattern’ as Adrian Slywotzky would call it (see Profit Zone by Adrian Slywotzky et. al.).

In the case of traditional lending, profits are made through ‘scale’. The lender wants to increase the ‘spread’ between the savings rate offered to savers and the lending rate charged to borrowes. Scale provides an advantage in at least two ways. Scale allows the lending institution to reduce its ‘cost of borrowing’ from the capital markets and it also lowers the cost of processing each deposit-taking and lending transaction. In other words, traditional lending is based on the Transaction Scale Profit Pattern.

In the case of peer-to-peer lending, profits are made through ‘matching’. The P2P lender has to create and mediate a social network where it can match borrowers with lenders and give them the confidence that they can transact in a safe and secure manner. Of course, to facilitate this matching the P2P lender needs to have a certain scale – but scale is a secondary factor. Adrian Slywotzky refers to this as the Switchboard Profit Pattern.

Information Patterns: In any business design, in addition to how profits are made, how information is processed is also a critical component. In any good business design there is a good ‘fit’ (the third of the 3F’s of Business Design) between the profit pattern and the information pattern.

What is an information pattern? An information pattern is the process by which an organizational entity turns Information into Insight and Insight into Action (or the I-I-A cycle). In the case of traditional lending the I-I-A cycle is basd on Collect-Organize-Analyze-Decide-Act or COADA pattern. Data is collected from different parts of the organization, organized into different information domains, analyzed to generate insights, disseminated to roles that can make decisions, and decisions conveyed to individuals to act. The COADA pattern is the default pattern that most traditional organizations adopt to manage information complexity. Traditional lending follows the COADA pattern and hence it is no surprise that such organizations invest in IT to make this process as efficient as possible.

In contrast, peer-to-peer lending adopts the Connect-Share-Decide-Act or CSDA pattern. Individuals connect to each other, choose to share information or not, and based on what they see make a decision and act. Notice that there is very little collection, organization, analysis of the information. The success of this ‘switchboard’ profit pattern comes from being able to entice the right groups of people to the social network so that ‘connections’ can be formed to share the information. The peer-to-peer lender needs to faciliate the making of these connections and also have the necessary guarantees in place to provide lenders and borrowers to have the ‘confidence’ to lend and borrow.

In his post, John Sviokla shows that the peer-to-peer lending is beneficial to both the borrower (who gets a lower rate than from a traditional lender) and the lender (who gets a higher rate than from a traditional deposit taker). One of the primary reasons for this is, I believe, the information advantage of the peer-to-peer lender compared to the traditional lender. By matching borrowers and lenders and facilitating their transactions, the P2P lenders have eliminated the need for collecting, organizing, and analyzing lending information that traditional lenders do a lot of. In addition, decision making has been delegated to the edge (one could even argue ‘outside’) of the organization.

Finally, note the ‘fit’ of the profit pattern with the information pattern. Traditional lending, based on hierarchical organizational structures, uses the COADA information pattern that requires transaction scale economics to make profits. In contrast peer-to-peer lending is based on a social network structure and uses the CSDA pattern that requires matching or having a switchboard to connect buyers and sellers to make profit.

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3 Responses to “Business Design and Information Patterns”

  1. Francois Ramette says:

    Thanks Anand. Great post that really helped me think about the 2 lending models. Just had a question regarding the following statement:“In contrast, peer-to-peer lending adopts the Connect-Share-Decide-Act or CSDA pattern … “

    If peer to peer lending generates some momentum, liquidity increases, and professional investors start using peer-to-peer lending platforms, wouldn’t analytical models be developed to decide whether transactions should be pursued or help borrowers/lenders select their counterparts. For instance, if I am a professional investor and want to lend large amounts on a peer-to-peer lending platform, I would probably collect, analyze and compare the information of several potential borrowers before engaging into the transaction. In this case, wouldn’t the Collect-Organize-Analyze-Decide-Act information pattern apply?

  2. Anand Rao says:

    Francois – You are right. When the traditional players start using P2P networks their default pattern would be to Collect-Analyze-Decide-Act. They will try and collect and analyze information about the connections and sharing that is going on within the CSDA cycle. Also, as we are now seeing with Twitter and Facebook, even the social networks might change their business model and try to ‘monetize’ their connections. When they start doing that they will revert to a Collect-Organize-Analyze-Decide-Act pattern. The key principle here is that we can identify certain information processing and decision making processing with particular business models or profit patterns.

  3. I think I will try to recommend this post to my friends and family, cuz it’s really helpful.

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