State Street Tests a ‘Rosetta Stone’ for Bank Databases


By Penny Crosman, Editor-at-large, American Banker

July 14, 2016

Anyone who’s ever worked on a technical standard knows it can be thankless, unrecognized effort.

But David Saul, chief scientist at State Street, believes what he and his bank are doing with a little-known data standard called Financial Industry Business Ontology could change much about the way risk management, financial product pricing and even marketing are handled today, and make blockchain technology feasible for banks.

“The work we’re doing on FIBO is a prerequisite to doing anything with algorithms,” said Saul, who was one of American Banker’s Innovators of the Year in 2013. “First you have to get the data right, and that’s the whole point of FIBO and what we’re doing with our proof of concept.”

FIBO provides a description of the structure and contractual obligations of financial instruments, legal entities and financial processes. It’s used to harmonize data across repositories, kind of like a Rosetta Stone for banks’ databases. It’s expressed in machine- and people-readable language. It allows for the consistent tagging and formatting of data across an organization and an industry and could allow many things to be automated that today must be done by humans.

“Every bank has master files that define the terms, conditions and characteristics of their financial instruments,” explained Michael Atkin, managing director of the EDM Council, a trade association that’s been the main driver of the standard. (That stands for “enterprise data management,” by the way, not “electronic dance music.”) “The first requirement is to map it to common meaning, so we’re all calling things the same names. That’s our part, the humble ontology.”

Some of the goals Saul and others have for FIBO echo what’s hoped from blockchain technology: the ability to reframe financial transactions as self-executing “smart contracts”; the ability to execute transactions between banks without a need for middlemen or a clearinghouse; the ability to completely automate complex products like mortgages and over-the-counter derivatives; and the possibility that all parties could have complete transparency around deals. Indeed, FIBO and blockchain may eventually be interdependent: For distributed ledgers to work, the parties involved have to agree on a common language; for smart contracts to be completely hands-free, some kind of shared database would be required.

A reason for banks to implement FIBO now is the Basel committee’s BCBS 239 regulation, which outlines data governance principles for global, systemically important banks. FIBO isn’t a complete answer to these principles — there are aspects of data ownership, management and governance it doesn’t address.

“But when it comes to knowing precisely what you have, FIBO at this point is the most complete and comprehensive solution to the mapping of data not just within an organization but across organizations, and that includes regulators and regulatory reporting,” Saul said.

Stress test and transparency regulations also call for banks to report data using a common standard.

“Data aggregates are sent to regulators, who have to unravel all the aggregates to feed things into their models because they’re looking at different stuff,” Atkin said. Regulators can only do that if they receive consistent data from the banks.

“The world is coming rapidly to the agreement that harmonizing data to common meaning is what we need,” Atkin said. “More and more banks are saying they’re interested in using this, and we’re on a happy path toward adoption.”

Proving It Works

Earlier this year, the EDM Council asked Saul to do a proof of concept of FIBO, to show it actually works with real data.

To test the standard, Saul’s team pulled data on thousands of interest rate swaps from its transaction system and integrated it with an external data set from Dun & Bradstreet, the business credit reporting agency. They mapped all the swap data to FIBO.

“We focused on swaps specifically for Dodd-Frank compliance, because all of us have to report on these and this has the potential for giving us a standardized way of reporting,” he said.

They can now create things like heat maps that show the flow of money to and from all the legal entities that are parties to the swaps.

They can also see aggregations of all the legal entities that roll up to a larger corporate one (for instance, all the subsidiaries of a large financial firm). “It’s time-consuming to do all that using traditional methods,” Saul said. “With the semantic model, since it knows and is mapped in that hierarchy, we can get that directly.”

When Lehman Brothers failed, for instance, financial institutions had a very short time to aggregate all their exposures to the firm.

“More than half of the Lehman entities didn’t have ‘Lehman Brothers’ in the name, so we didn’t know they were part of the larger corporate entity,” Saul said. “Now we have that information in the ontology and we can see that directly.”

Decoder: The Rosetta Stone, a replica of which is shown here, allowed translation of Egyptian hieroglyphics into Ancient Greek. The FIBO standard seeks to create a common language, readable by machines or humans, for financial contracts.

This raises a top use case for the Financial Industry Business Ontology — risk management. If risk is expressed in a common way across departments and products, using the proper legal entity identifiers, risk data can be gathered and analyzed in a central place, and an organization can clearly see its risk exposures. JPMorgan Chase could have identified the positions of the London Whale before they became so large, for instance. Analysts could also catch risky trends early, before they cause a problem.

They could also see opportunities.

“This is a powerful analytic tool that can be used to create greater insights, so you’ve got the prevention side but also the possibility for creating greater insights into financial markets,” Saul said.

With FIBO fully implemented, anyone in a bank could ask what-if questions and slice and dice data. “That’s one of the opportunities it opens up,” he said.

Smart Contracts

FIBO could enable the use of smart contracts, something on the minds of many bankers (despite the inauspicious performance of an early example known as the DAO).

“Every financial transaction, from the very simplest buying and selling of an equity to the most complicated over-the-counter derivative, can be defined in terms of a contract,” Saul said.

A smart contract allows all the terms and constraints of a financial agreement to be executed and verified without human intervention. “They’re also standardized so they can be exchanged and immediately understandable as they move from one party to another,” Saul said.

Three things are needed to make smart contracts viable, he said. One is a precise definition of all the data elements in the contract, including the legal entities that are parties to the contract, geographies, currencies, and collateral. That is FIBO’s role. “That’s the starting point,” Saul said.

Allan Mendelowitz, a key member of finRenaissance

The second element is definitions of all the terms of the contract, such as the length, rate and payback conditions of a mortgage. This is where the ACTUS standard, spearheaded by former regulator Allan Mendelowitz, comes in. ACTUS has defined 30 algorithms that either singly or in combination provide all the calculations needed for a contract.

The third piece is a way to securely transmit contracts from one party to another.

“You need to make sure somebody hasn’t altered them in some way,” Saul said. Blockchain technology could be used to provide that security and immutability. Alternatively, a startup called finRenaissance has created a secure “wrapper” for ACTUS-based smart contracts called BlackIce that encrypts the smart contract data at rest and in transit.

Though State Street is interested in all these aspects of smart contracts, it has poured most of its effort so far into the FIBO proof of concept “because if you don’t get the data right to begin with and on an ongoing basis, it doesn’t make sense to do anything yet with the algorithm,” Saul said. The next logical step for his team is to start experimenting with ACTUS.

When the FIBO standard has been fully implemented throughout State Street, Saul said it will help investment managers make better decisions by looking at areas where they’re getting the greatest returns. On the risk management side, it will help staff spot early indicators of stress or risk — for instance, too high of a concentration in a particular currency that’s under pressure.

“If you start to get an early indication that something anomalous is taking place, it gives you the opportunity to slow down or even shut down before it creates a larger problem,” Saul said.

FIBO could become the standard for most kinds of financial reporting, Saul predicted.

“If that happens, we’re likely to see a real rush to use it,” he said. He noted that the Office of Financial Research’s last annual report devotes an entire chapter to data standards. The only way the office is going to be able to meet its legislative mandate is with data standards that are created by the industry, he said. “That’s precisely what FIBO is.”

American Banker’s Editor at Large Penny Crosman welcomes feedback at