One concerned about profitability, the other concerned about growth

This is an excerpt from a transcript of The Axway Podcast, “One concerned about profitability, the other concerned about growth.

ANNOUNCER: Forbes writer Tom Groenfeldt recently published a piece titled “Compliance Efforts Can Bring Business Benefits for Banks,” and he quoted a risk consultant in it who noted that bankers he recently surveyed were “split into two groups — one concerned about profitability and the other more concerned about achieving growth. Those focused on profitability were concentrating on regulatory stress testing, model review and more operational issues that were a little more backward looking. The growth-oriented bankers were looking at capital planning and allocation.”

PETER BENESH: First of all, we need a clear understanding of what these two groups are. Best as I can interpret, one is a group of banks that actually have completed the stress tests that are required by the regulators. This is all part of what’s called the Basel III regulations. Some banks have gone ahead and actually done the stress testing, other banks are trying to figure out how they’re going about actually complying.

ANNOUNCER: That’s Peter Benesh, Axway’s director of solution marketing for the Financial Services industry. We asked him to explain to us what sort of technologies he would recommend to each group, what sort of actions he’d recommend those groups take to achieve their goals, and why?

PETER BENESH:  There’s a period of time that the regulators have given banks within which they can comply, so not everybody has to do it immediately. Some are being more proactive about it than others. The stress testing itself is a hypothetical exercise and essentially involves a scenario of very adverse economic circumstances such as very high unemployment, very high interest rates, such that people aren’t taking loans out as much. So a bank’s interest income might be declining. Concerns about stock market crashes. And people might be pulling their money out of the banks. It’s essentially a series of hypothetical scenarios that the banks need to quantify and see what happens to their balance sheet under such a situation. Meaning, if their income drops significantly due to less loans or if depositors pull a bunch of money out so that they have less money to loan, do they have enough capital in the form of stock that they’ve issued or income that they retained as reserves, to survive a crisis like that? Can they still pay all their operating expenses by pulling money out of their reserves?  Essentially the same idea as a household looking at how much savings they have, and could they survive for a year if the people making income for the household get unemployed, for example. So that’s the essence of what we’re talking about. The technologies that are required to do the stress testing — it’s a big data integration exercise and really integration of data that’s internal to the organization. They have to be able to pull information from all kinds of databases, both databases that track revenue from loans, databases that track how much investment money they’re keeping. They have to essentially create a hypothetical repository of all that integrated information out of which they will then create hypothetical balance sheets and income statements running those statements using the assumptions of the tests. So it’s data integration in more of the classic sense of pulling data from mainframes, servers, Excel spreadsheets, many, many different sources, internal to the bank. Transforming those and consolidating them into a data warehouse and then running financial analytics against that. The ones who are concentrated on profitability, those are the ones that haven’t actually done the stress tests yet. They’re trying to figure out “How are we going to build models? How are we going to quantify these adverse economic assumptions? How are we going to create the integration flows to create the database of information we need and then create the hypothetical financial statements?” They don’t know yet what the results of those stress tests are going to be. They don’t know if the outcome is going to show that in a real bad economic situation, perhaps they don’t have enough capital to survive. Naturally, they’re going to be more focused on “We got to remain profitable today” whereas the ones that have already completed the stress tests, if the test results show that they would be in danger of going out of business, then they are taking steps to increase their reserves, increase the amount of capital that they are keeping. That may involve they decide to issue more stock. They may decide that they can cut back a little bit on how much of their case reserves they’re actually loaning out. That’s why they’re able to look more forward, because they already know if their capital reserves are adequate or not. Technology is, again, classic data integration, ETL type of tools. You need a very powerful analytic server. There’s a lot of companies that offer that. Hadoop is a very popular tool for that now because you can store massive amounts of data in Hadoop and then do analytics on it. I think our accounting integration suite could also help these companies because we don’t actually do the financial reporting but we could help them create rules by which they could create a hypothetical G.O. under these types of scenarios. First, you have to collect all the information, all the financial information. Put it into a hypothetical general ledger with all the accounts, your income statement accounts, your balance sheet accounts. Then run your reports against that. It’s almost like creating a whole separate accounting and reporting system that’s all based on hypothetical assumptions.

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The power to better manage disparate data flows

This is an excerpt from a transcript of The Axway Blog Team’s podcast, “Key takeaways of the ‘Speed to Revenue and Improved Customer Service’ white paper.”

ANNOUNCER: Hello everyone. The Axway Blog Team recently had a chance to catch up with Peter Benesh, Axway’s director of solution marketing for the Financial Services industry, and ask him to share his thoughts on the key takeaways of the IDC Financial Insights white paper titled “Speed to Revenue and Improved Customer Service: How Data Agility Underpins Success for Financial Institutions in the New Digital Economy” by Alex Kwiatkowski. Key Takeaway 4: Advances in API technology create opportunities to leverage new channels on top of existing services and provide better user experiences, increase revenues, and reduce costs. Real-time integration has the power to better manage disparate data flows and deliver tangible benefits.

PETER BENESH: An immediate example that comes to mind is somebody like Fidelity. If you have a Fidelity account… And say you want to do a 401k rollover. Say you want to close out your 401k and pull the money out. Or let’s say you have an investment portfolio. You have a variety of money market funds, maybe some stock index funds. If you want the flexibility to shift that around very easily and quickly… My personal experience working with some situations like that is you have to call Fidelity, or at least put in a request through a portal. It takes a while for them to confirm that they’ve closed the 401k, that you have to wait seven days or something like that before the check actually gets sent to you. I’m sure a lot of that bureaucracy is created to ensure privacy, to ensure accuracy. But if you could have a technology like the API portal and gateway that provides companies like Fidelity the confidence that all of this is happening securely and within policy, but enables the customers to do it themselves in true real time, then that’s obviously going to attract somebody to that type of service much moreso than one that takes a lot longer. It’d be great if I could just log in to Fidelity and, on the fly, move my money from one market fund to another, rollover 401k, pull money out of a 401k, if I need to close it, and have that all just happen instantaneously.

To download the white paper, click here.

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