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Stress Tests Require Continuous Tech Upgrades, Bankers Say

Federal stress tests are forcing banks to continually upgrade their technology in order to meet the shifting demands of banking regulators.

For instance, while banks are used to tracking loan losses by portfolio, many are now being asked to track the performance of individual loans over time.

And while the numbers they generate for the stress-test forms may be acceptable, regulators are increasingly asking them to show, through reams of documents, how they got to those numbers.

The upshot is that banks of all sizes must continue to invest in technology that will help them better manage data, document processes and stress-test models, according to bankers and consultants who attended a stress-testing conference in New York hosted by American Banker. And these will not always be one-time investments. Observers say banks will need to keep making improvements to their infrastructure as regulators and bankers themselves find gaps in their processes.

"The industry will spend millions to manage this process," said Daniel H. Bley, executive vice president and chief risk officer at $20 billion-asset Webster Bank in Waterbury, Conn.

Mark Levonian, managing director and global head for enterprise economics and risk analysis at Washington, D.C., consulting firm Promontory, said that banks need to do significant work on data and infrastructure and that's not necessarily a bad thing.

"It's rarely a waste to do that good data feeds good decision making of all kinds," Levonian said at the conference.

One challenge for banks is that they, like many other types of companies, often keep data in silos. Financial information is in one place, loan-loss data is in a different system, and compliance data is stored elsewhere. Stress tests require synchronized data from all three sources.

"To me, everything starts with data management," said Ed Schreiber, an executive vice president and the chief risk officer at Zions Bancorp. in Salt Lake City. "The industry as a whole doesn't manage its data and it's never had to. Everybody has disparate systems that don't talk to each other. Nobody's paid attention to data governance."

Schreiber advises banks to set up a centralized warehouse for stress-test data and spend the money to get it right.

"As you're growing, if you don't take time to get your systems in order, that will be a mistake further down the road," he said. Stress-test-related data includes loan performance information; current capital levels; loan-loss provisions; planned capital distributions, such as dividend payments, stock repurchases, or planned acquisitions; and local economic conditions.

Those that don't address this area will pay a high cost, he said. For one thing, where banks fail to fill in fields on the regulators' stress-test forms, regulators will provide their own values. For instance, if the bank doesn't enter a 70% loan-to-value ratio for a borrower, the regulators will enter their own number, say a 100% loan-to-value ratio.

"Your losses will be a lot higher. It will cost you money and make you hold more capital," Schreiber said.

One reason stress-testing data gathering is hard for banks is that the data requirements for stress testing are different from the traditional requirements of calculating loan losses, said Shaheen Dil, managing director at Protiviti. "Stress tests require things banks didn't think they needed."

For example, banks tend to track loan losses on an aggregate basis, and once a loan goes on to a watch list, it moves into a different system. If a client starts out as a small business and later grows into a much bigger company, that loan is moved into another portfolio. "Banks don't have a good way of tracking that," she said

Regulators are increasingly indicating it's not enough to look at portfolios of loans; banks need to predict the risk of individual loans, too.

The specific stress-testing models banks use to evaluate their loans are another area in need of improvement. Some banks create their own models, others use those provided by third parties such as Trepp.

There's a lack of general lack of model accuracy in the industry, Dil said, and a lack of appropriate model governance in many banks. "A number of banks passed [stress tests] based on numbers, but failed because of their process and governance not being good enough," she said.

Banks that rely on vendors' stress-testing models need to validate them, several at the conference said. It's also a best practice, many observers say, to triangulate estimates with different modeling approaches and methodologies, in order to challenge the models' results.

Documentation of the stress testing process is another issue that's come out of the early rounds of stress tests.

"If you don't have documentation, from the point of view of the [Federal Reserve, the Office of the Comptroller of the Currency and Federal Deposit Insurance Corp., it doesn't exist," said Zions' Schreiber. (Zions, as a holding company with eight banks of varying sizes, is regulated by all three agencies.) "You can talk till the day is long, but it doesn't exist."


(2) Comments



Comments (2)
This comment is on the mark. The challenge is on a couple fronts for the business who owns the data. First, creating the realization that the data is important. Making everyone aware that providing accurate data every time is a high priority is difficult, because, as the author notes in the article, some of the data is information that bankers have historically not needed. At least, we have not needed to provide the data in as much detail as stress testing now requires. Education of this principal is essential. It needs to be clear to each employee why this data is important and how it effects their job. The second challenge is to make documenting the data as natural and streamlined as possible. Employees are being asked to do an overwhelming amount of work in the work-week these days. They are naturally going to spend the most time and attention on the tasks that they see as being most directly tied to their success. Typically, this is booking business. The more we can incorporate gathering and documenting all of the detailed data requirements into the processes already in place for underwriting/booking business, the higher likelihood that the data will be documented consistently and accurately. One option is creating some specialty functions to support the traditional functions. This is expensive, but it concentrates the "new" data gathering activities with the specialists. This aligns each employee's responsibilities more directly with the primary results they are being measured and compensated on. The technology support to the business needs to be holistic and the business' requests for technology support need to be comprehensive enough for IT to understand the business process. This process takes a lot of cooperation and a lot of education.
Posted by SSuits | Wednesday, May 28 2014 at 9:19AM ET
RE: Stress Tests ... Tech Upgrades
The issue I have is in the title of this article ... getting the banking data in the shape needed for supporting the needs of the regulatory authorities (and, as the author Penny Crosman helpfully asserts also supports important banking operations) is distinctly not a "technical" exercise. I suspect strongly that the reason many banks have not addressed this adequately is directly because it is treated as an "IT" issue. While "technology" plays a role, it is a supporting one but the tasks involved in getting the right data management infrastructure ought to be squarely a business-owned and managed function.
The business management, particularly senior business executives, need to "own" the data they decide to capture and use in the business processes that support banking activities. "Ownership" means - among other factors - that the business, in addition to explicit involvement in deciding what data elements are important to capture (think loan applications, for one), they also need to provide precise, business-oriented definitions of these data elements in a rigorous, structured governance program. It should be obvious that if data elements like "Customer Address State" or "Interest Income" do not come with precise, approved and generally recognized definitions, reports containing these are likely to be ambiguous. For example, if "Interest Income" includes commissions in one report and does not in another, this invites time wasted at meetings figuring out which number is the right one. Or, "State" where we may not know if it is part of the customer's home address, the jurisdiction state where the loan originated, the customers billing address ... An IT person charged with rationalizing this will ultimately need to get clarification from the business for all of these terms.
An effective data management and governance program needs to have active involvement by the business by participation in a data governance committee, with a system of stewardship, administrative support, and actively managed structures that support data management. Yes, databases are involved, but the content is the full responsibility of the business.
Posted by davidselib | Thursday, May 22 2014 at 9:35AM ET
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