Evaluating credit-based transactions and portfolios is no walk in the park. Getting suited up with the right models is a gargantuan, expensive task. The analytics and data don't always talk to one another, at least not without a lot of translation. Banks must also build and maintain databases of counterparty and credit information to properly gauge exposures. And banks—even large ones—tend to be locked into a single view of risk. This conspires to make credit analysis a dicey affair.

CreditDimensions believes it has an answer to this problem. The brainchild of PricewaterhouseCoopers, this newbie application service provider will host an on-line smorgasbord of data and analytic tools. Banks will be able to access a posse of credit analysis goods in one place and can subscribe to the services they want. This should streamline the credit analysis process and enable investment and commercial banks and insurers to take more opportunistic views of risk. The ASP will also sponsor a database of static counterparty data.

When it launches later this quarter, the site will include analytic models, credit and market data, credit analysis process tools, news and research, as well as the counterparty database. Basic research and content will be available for free. Everything else will be available for license or, possibly, on a per-usage basis. The ASP's content will be provided by PWC and its collaborators: Algorithmics, Bureau van Dijk Electronic Publishing, Credit Suisse First Boston, Cygnifi, eCredit.com, Gifford Fong Associates, KMV Corp., RiskMetrics and Standard & Poor's. Other firms are expected to join the roster as the site grows.

"On CreditDimensions, the idea is for someone to be able to say, ‘I want to value my loan portfolio three different ways—once with S&P data, once with Moody's and once with KMV.'” — Scott Aguais

Once CreditDimensions is up and running, a bank should be able to upload a transaction or loan portfolio to the ASP and put it through its paces. A bank can price instruments, measure its total risk to a counterparty, calculate a credit probability using one of the site's three or four scoring models, and feed that information into one of various portfolio models—seamlessly. "A client can do aggregation, rating and portfolio processing all in one place,” says Jim Vinci, co-lead partner in financial risk management services at PWC. The likely result: IT efficiencies and cost savings.

The uploading must be done for the analytics to run, but it needs to be done only once, since the mapping can be saved and reused to load new portfolios. The first go-round probably won't be a lark, especially if a bank doesn't aggregate its loans within the organization or has 10 different systems, but these days data aggregation is an irrepressible beast, almost whatever a bank does.

While CreditDimensions' ambition is to make the market for credit risk management infrastructures more robust, it isn't offering cut-rate prices on models. "The set-up isn't too different from how HBO, Pay-Per-View and other premium channels operate,” says Vinci. "It's up to Showtime to decide how much it wants to charge you, the cable subscriber, to receive its programs. It's not up to the cable provider.” The sticker price for analytics won't differ too much from what it currently is for banks with full global on-site licenses, but the ASP will give service providers the flexibility to offer scaled-back versions of models or to charge users on a per-usage basis. For the ASP's content providers, meanwhile, CreditDimensions offers a new and—since it's the first credit risk ASP out the gate—significant distribution channel.

Multiple choice

One advantage to having analytics vendors and data providers share prime Internet real estate is that institutions will ultimately be able to take multiple views of risk. They'll be able to feed different ratings or views of risk into a transition matrix or valuation model. "Some pricing and portfolio models come bundled with their own view of risk, while others don't have the risk piece at all—you have to add it in,” points out Scott Aguais, director of credit risk solutions at Algorithmics. "On CreditDimensions, the idea is for someone to be able to say, ‘I want to value this loan or my portfolio and I want to value it in three different ways—once with S&P data, once with Moody's and once with KMV.' The user can then better understand the implications of those different views of risk on the portfolio or transaction price.” Right now, that's not something even the largest banks can do.

Another advantage to yoking together so much industrial-strength technology is that credit risk can be compared across institutions. This will be a handy trick in the shape-shifting regulatory world. As regulators move toward a more models-based approach to life, "having one location where you can really dig into and contrast different approaches to credit risk will be extremely valuable,” says Wilson Ervin, a managing director at CSFB and global head of strategic risk management. The site's multiple-choice configuration, for example, should enable third-party reference checks on pricing values and on the items most at risk in a portfolio.

Firm-by-firm risk comparability may also provide a leg up in the M&A business. If risk can be measured and quantified consistently across different businesses, M&A gurus may be able to see more clearly whether a new venture will add or shed risk to a firm's bottom line.

In addition to the site's analytical wares, CreditDimensions will house a repository of static data for (initially) about 80,000 companies worldwide, with the database holding counterparty details for some 300,000 legal entities. A large bank, for example, might have 30 different legal entities within the parent's hierarchy.

The database could prove a boon to banks. Currently, banks must build—from scratch—their own massive Yellow Pages of static information about counterparties. "Chase is maintaining Citibank's information,” says PWC's Vinci. "Bank of America is maintaining the same information about Citibank. Everybody is spending money maintaining this information about each other. With a common repository, it will be that much more cost-effective to get accurate data.” PWC will maintain the database and charge subscribers a fee to download it; firms that publish their static data to the site will get a price break on the database.

This may sound like a dull-as-nails offering, but static data is effectively the mouse that roars—and a symbol of how much redundancy there is in undeveloped markets. "We've thrown a lot of man-years at it,” notes CSFB's Ervin. "To do it right is a very expensive and challenging task.” A clean, off-the-shelf package of static counterparty data will therefore be a big advantage for "mid-sized banks that don't have 180 people doing risk management and measurement,” he says.

All this is well and good, but CreditDimensions is an ambitious venture—and with 10 participants, some are itching to get to the future faster than others. Vinci reports that CreditDimensions' initial slate of offerings will be rapidly expanded, based on what users want. But for the credit derivatives markets to truly mature, what's needed is transparency.

It's pricing and data transparency that should be the ultimate goal for CreditDimensions, advises John McQuown, chairman of KMV. Anything that improves the secondary credit markets is clearly in everybody's interest, because as markets get more transparent, they grow. Pricing transparency is needed for bonds, credit derivatives, loans and mortgages, he says, as well as for the data connected with individual obligations (such as maturity, coupon and call features). Some of this is currently available on Bloomberg and elsewhere, but the value would be to have it in machine-readable format so it can be integrated with analytics and other data needed to make pricing and transactional decisions.

The long-range potential of CreditDimensions, notes McQuown, lies in offering a context in which prices can become transparent. "That's the critical thing for the credit markets,” he says. "We need the same thing that has existed for 200 years in the equity markets. You know what General Motors stock trades at because you see the price, the time the transaction occurred and the number of shares traded. We need to be able to see the price GM debt is trading at. That will benefit the credit derivatives market.”

That's a tall order, but at least CreditDimensions has no competition. For now.