Connecting the Dots: US SEC, ABS Mandates,

Financial Modeling and Python

Presented by

Ann Rutledge, R&R Consulting

Diane Mueller, ActiveState

Speakers

• Ann Rutledge

• R&R Consulting

• rrcons@nyc.rr.com

• Diane Mueller

• ActiveState

• dianem@activestate.com

Founded 1997

2 million developers, 97% of Fortune 1000 rely on

ActiveState

Development, management, distribution solutions

for dynamic languages

Core languages: Python, Perl, Tcl

Other: PHP, Ruby, Javascript

About ActiveState

We’ve got your universe covered

About R&R Consulting

• R&R Consulting is a 10-year-old leader in cybernetic finance

• A standards firm for debt capital markets

• Balanced emphasis on risk-responsibility and value creation at each

link in the global supply chain of debt capital

What we will cover

• eGov & the Appearance of Transparency

• Case Study: Financial Content at US SEC

• Why Reg AB was not enough

• Python & Financial Models – the next Wave

Premise

• “Open” Gov’t Data needs “Open” Tools

• Tool Vendors need Open Source technologies

– Expedite delivery of consumption tools to market

– Ensure consistency in interpretation of the data

– Ensure equal access to tools across the supply

chain

So what is eGov?

• The way in which government has to adapt itself to a world in

which most people regularly use the internet

– http://poit.cabinetoffice.gov.uk/poit/

Motivation

• Transparency and engagement

– holding government accountable and promoting choice by

informing citizens

• Efficiency and enhanced public services

– enabling re-use of information within the public sector

• Innovation and economic growth

– encouraging and supporting data-driven innovation

eGov in US: Open Government Directive

January 2009

• President Obama issued a

memo on transparency

directing his top officials to

develop plans for an Open

Government Directive to

promote transparency,

participation, and

collaboration.

Growing availability of Open Gov Data

• US, UK, Australia,

Netherlands, Denmark,

Sweden, Spain ...

• Washington, Madrid, London,

Vancouver, ...

Publishing Data on Data.Gov

• XML

– Industry, agency, project-

specific

• PDF

• RDFa

• Shape

• Excel

Unraveling Open Data

• It’s more than just documents for people to read

• Need to enable machines to

– traverse, aggregate, analyze, answer

• Tim Berners-Lee's vision of a “Semantic Web”

– "Semantics", "Ontologies”

– RDFa, Linked Data

More Context

• Open government data is a reality

– “Open” doesn’t necessarily mean:

• “Equal Access”

• “Free”

• “Transparent”

• Semantic Web is a vision

– Should be nurtured, supported and encouraged

• But we’re in the middle of a Financial Crisis

– We need to work with the tools we have now

Financial Content @ US SEC

http://www.xbrl.org

http://www.xbrlnetwork.com

• A Case Study

• Lessons Learned the hard way

Part One: The Data

XBRL @ SEC

• A standard format in which to prepare financial reports that can subsequently be presented in a variety of ways

• A standard format in which information can be exchanged between different software applications

• Permits the automated, efficient and reliable extraction of information by software applications

• Facilitates the automated comparison of financial and other business information, accounting policies, notes to financial statements between companies, and other items about which users may wish make comparisons that today are performed manually

• *Responsible* Publishing of data

• *Easier* for people to consume financial data

• *Solve* some snags other approaches miss

Why did XBRL make sense for US SEC?

10 years later…

more rules, rss feeds & a viewer

It’s still a black box world

• Processing Financial Content

– requires specialized tools

– proprietary processors

• Business Decisions are all about timing

– access to data to make decision that happen in *nano*

seconds

– driven by algorithmic, computerized trading

Lesson Learned in First Phase:

Open Data at US SEC

• Appearance of transparency

• Granting of Access is insufficient

• No Open Standard API for XBRL available (yet)

• Asynchronous access to data (latency)

But what if the data isn’t enough

• A little structure goes a long way if you combine it with

– A human being with a lot of intelligence/domain

knowledge

– (tools, protocols, means of communication)

– (browser, http, share)

• Complex legalese in Filings & Prospectuses

– Logic embedded in them needs to be interpreted

http://benbittrolff.blogspot.com/2008_12_07_archive.html

Off to the Next Crisis

Enter the Financial Ninjas

http://en.wikipedia.org/wiki/Subprime

_crisis_impact_timeline

Seeds of the Latest Crisis

• Industry participants have real problems interpreting how the

cash flow is allocated

• The lack of certainty creates serious valuation problems for

holders of the securities

• Investors and their custodians also have very real settlement

problems

Regulators/Watchdogs

Assets

• Corporate credit is stochastic: YES/NO. ABS is statistical, not stochastic: YIELD/% OF PAR?

• Corporate data disclosures are public. ABS data disclosures are private.

• Corporate data are a moving target—ratios change with business flows. ABS credit-sensitive data is taken on a static pool basis.

• Corporate disclosures are a snapshot of performance, easily “doctored.”ABS data should be updated: when the pool amortizes, so does risk.

Liabilities/Capital Structure

• WYSIWYG/Not WYSIWYG.

• Deal waterfalls defines value.

• To implement the standard form or defined amortizations, modeling skills and knowledge of finance are required.

• Waterfalls are not always unidirectional (as we intuit them). Some are complex, with recursions and nonlinearities.

• At origination, Sellers and Buyers are supposed to be risk-neutral. Modeling mistakes totally change the game.

Credit Ratin

gs

ABS is the new black box

How a Deal Waterfall Works, Conceptually

• The whole thing is a state machine that needs to be precise in every detail; as generally once the deal is set up, the trustees and managing agents have no discretion

• They have to follow the script precisely as set out in the deal prospectus

Sample Waterfall (AmeriCredit 2001)

26

Copyright 2010

What Real Waterfalls Look Like

(This One Has Loops)

Copyright 2010

Distribution Structure:

Calculate Available Funds

using the SWAP Payment

and Yield Maintenance Cap.

The result will be distributed

across all tranches in the

liability structure.

Allocation Structure:

Use a Trigger to determine,

“Which Allocation Plan do I

call, A or B?”

Trigger

Sample Waterfall (Bear Stearns 2005)

Here, the Master Waterfall Has A Trigger

28

Sample Waterfall (Bear Stearns 2005)

Distribution

…If Tripped, Pro Rata Becomes Sequential

…Mezzanine Class Credit Enhancement Is

Linked to 60+ Delinquencies

A simple difference linking two

complex calculations: 60+

days’ delinquent accounts as a

percentage of the current pool

balance and a run-rate target

enhancement percentage.

Sample Waterfall (Bear Stearns 2005)

Asset Trigger Event

Enter Regulation (“Reg”) AB

The necessary, robust disclosure framework developed by the

SEC for structured securities.

• Necessary because:

– ABS use different (private data) and different measures (static pool

delinquencies, defaults, losses)

– ABS have a different risk/return profile than corporate debt

securities—the risk amortizes as the pool amortizes

• Robust because:

– Reg AB incorporated all key disclosure items as recommended by the

market

– It was strongly endorsed by large pension funds and institutional

investors

Why Reg AB was not enough..

Regulation AB: Evolving, Closing

Loopholes

2005 Version

• Requires disclosure of static pool

data in prospectus, website

disclosure of performance data

– Delinquency

– Loss

• Sets a 5% standard of materiality in

misleading disclosures

2010 Proposal

• Requires updated disclosures.

• Lowers the threshold of materiality

to 1%

• No shelf registration without risk

retention

• Waterfalls must be published, as

part of the data set

Disclosure,

Feedback,

Enforcement

How Access to Financial Models

helps..• Today, it’s hard to Price Securities

– complex prospectus documentation

– write your own waterfall program

– data must be mined from investor reports

– determine the cash flow every month

• Proprietary analytic packages that do this, but it’s expensive

– pay 100K USD for the model to find out the securities are fairly priced

• Having the model & updated data freely means:

– Securities can be valued in a far more cost effective way

– Leaves less up to interpretation

– Run scenario’s on the portfolio and access the impact on the underlying

securities in real time

http://www.sec.gov/rules/proposed/2010/33-9117.pdf

What is the SEC asking for?

• Python code to document the waterfall model

– decision logic which determines the cash payouts made to

all the securities attached to the a specific mortgage pool.

– depending on specific events the cash flows distributed to

securities will change over time based on events occurring

in the underlying portfolio

• This is documented in the prospectus which can be > 600

pages of detailed legal language

http://www.pylaw.org/demonstration.txt

Why Python makes sense for US SEC

• Open Freely Available now

• Available libraries for working with complex algorithms

– Numpy, matplotlib, Rpy

• Bindings exist for other proprietary numerical Financial libraries

• Already widely used for Financial Modeling

• Python is a very readable language when coupled with the other proposal that detailed asset level data be also provided in machine readable (XML) format

http://jrvarma.wordpress.com/2010/04/16/the-sec-and-the-python/

Next Steps

• Key: Give Feedback to SEC on it’s Proposal

– Depends upon economics, politics, culture and

technology

– Which could easily change in radical ways..

• Through an invention

• Through a insight into a practical application of an existing

technology

• Fostered by Open Collaboration, Open APIs

It’s still a black box world

• Collaboration across constituencies..

– “Open” Gov’t Data needs “Open” Tools

• Open Source technologies

– Expedite delivery of consumption tools to market

– Ensure consistency in interpretation of the data

– Ensure equal access to tools across the supply chain

Q & A

www.activestate.com

business-solutions@activestate.com

Twitter: @activestate

www.creditspectrum.com

rrcons@nyc.rr.com

Twitter: @annrutledgerr

Thank You

Speak to a representative about

ActivePython Enterprise or OEM: 1-866-510-2914

business-solutions@activestate.com

www.activestate.com