how to coordinate regulation (basel iii), market and business strategy in the planning of a...

Optimize or dieHow to coordinate regulation (Basel III), market and business strategy in the planning of a financial institution

Ramon TriasCEO

AIS Aplicaciones de Inteligencia Artificial

[email protected]

www.ais-int.com

Madrid, September 2013

Motivation

Balance Sheet and P&L Projections

Conclusions

Agenda

2 | © 2012 Global Association of Risk Professionals. All rights reserved.

Motivation


Conclusions

Agenda


Traditionally we have focused on separated risks: credit, market, liquidity…

We have learnt numerous methodologies and developed technologies which are useful to treat them separately – siloed approach - .

Now we are able to plan the optimal strategy considering the whole business: calculating the optimum distribution of the portfolios in order to meet the

A Little History…


calculating the optimum distribution of the portfolios in order to meet the bank’s business objectives, taking into consideration all types of restrictions and all kind of risks.

This has been the evolution…

Financial Modeling Evolution

Credit Macroeconomics

Other risks

Failure –oriented (bankruptcy / default )

CreditPortfolioView,Stress testing, RDF

Operational, reputational,liquidity, ...


Market CorporateMerton

COSOBasel II

Stresstest

Business Integration

Optimization

Main attention to prices. speculation, volatility

B/S Projection

What happened in the PAST is not the best answer to forecast the FUTURE.

WHY?

Statistical methods are based on historical information

Control and regulation based on ratios have sense in stable times or quiet noise evolution.

Where Are We Going To?


evolution.

Complexity has raised (and goes on arising) from different sources.

But, risk management makes more sense if it does integrate all risks with business objectives.

To do so, it is necessary to OPTIMIZE.

We, risk experts , are also the best qualified on modeling business functions in Financial Institutions:



Rescuing well known tools and concepts

The next step into this new position is


Strategic Planning


Tools for Balance Sheet and P&L projection, subject to optimization criteria , in a changing environment.

Motivation


Conclusions

Agenda


To implement a system that really helps managers to make decisions about which strategy to follow, by laying out the optimum asset and liabilities structure from the leading objective pe rspective .

Integrating –convoluting- all sources of profit and loss – risks, earnings, funding ...

Our Proposal


Considering all limitations and restrictions (Basel III, market, business…)

Mixing economic forecast from a formal model with extra model scenarios.

Using a dynamic view, not a still photograph.

Our Proposal

Current Portfolio, regulatory

Results• Balance• Results

Macro-economy Macro Scenarios

Financial System Dynamics

Scenarios Generator


Current Portfolio, regulatory restrictions, market restrictions

Proposal• Cash Flow

Statement• Req. capital• Regulatory

capital• RAROC/ROE• Bank value• Liquidity

Feedback

Risk ToleranceOther Restrictions

Optimization Criteria

Risks: Credit, ALM, Liquidity,

Interest Gaps, Treasury, Other

Example

How Should This System Work?

The effect of anticipating the schedule of implemen tation of Basel III short term liquidity ratio.

Let’s see how, the anticipation of this ratio affects the forecasted assets and liabilities in the optimale plan.


We consider the optimization of a balance sheet of a hypothetical bank. The optimization criteria is the maximization of profit. The active restrictions are Basel II and Basel III frameworks.

Comparacion_Proy1

The maximum


The maximum profit that could be reached is lower

than before.

The first victim would be the

trading portfolio. 1 2

Comparacion_Proy1

Mortgage loans


Mortgage loans would fall

The debt structure would change

Comparacion_Proy1

Cash increase


Cash increase

Lower profit

1 2

Optimization. All the Limitations Together.

ratio Cooke

leverage%

ratiocoveragestablenet

ratiocoverageliquidity

amount finacing termLong

available financing termLong

FlowCashNet

==

==

===

rc

ap

nscr

lcr

IRFE

FDE

SHL

tsLiquidAsse

developers State Real SMEs toLoans

CapitalTotal

CapitalTier11

1TierEquity:CapitalCore

%80LTV Mortgages

===

==

<=

AL

CR

CT

C

CB

M


Basel II Basel III

1*85.065.0

1)*25.0,max(

103.0

≥+

+=

≥−+=

+=≤

CRM

sLongliabilitieCTnscr

outinout

depBCcashlcr

CRM

Cap

[ ][ ][ ]

[ ] [ ]BICTBIICT

QISdelIIgoupparaaprox

CRMBIICT

CRMBIIC

CRMBIICB

≅

+≥+≥+≥

2010

08.0*)75.035.0(

04.0*)75.035.0(1

02.0*)75.035.0(

[ ][ ]

[ ]BIICTCT

BIICC

BIICBCB

QISdelIIgoupparaaprox

CRMCT

CRMC

CRMCB

≅≅≅

+≥+≥+≥

175,01

5.0

2010

105.0*)75.035.0(

085.0*)75.035.0(1

07.0*)75.035.0(

50

100

150200

250

300

350

400Hipo

RetornoscapEconomicomax PyMEsmax HipotecasLiquidez LargoApalancamientoCapital TotalTier1 AmpliadoCapital BasebalanceRestricciones

50

100

150

200

250

300

350

400Hipo

50

100

150

200

250

300

350

400Hipo

Optimization. All the Limitations Together.


50 100 150 200PyMEs

50 100 150 200PyMEs

50 100 150 200PyMEs

50 100 150 200PyMEs

50

100

150

200

250

300

350

400Hipo

50 100 150 200PyMEs

50

100

150

200

250

300

350

400Hipo

When calculating the best plan to reachthe business objectives of the bank, it is

a must to consider all the restrictionsinvolved: regulation, market, policies... Any single change gives a new assets

and liabilities position.

Required Technology To Make This System Work

• Macro variables forecast : VAR models. Multiequational and multivariable. Cointegrated.

• Conditional distributions mixes extra-model scenarios with formal forecasts.

• Microeconomic models links macroeconomic scenarios with internal flows –PD, LGD, credit demand, cost of funds, ...

• Risk drivers: Macroeconomic together with residual variables from micro models.

• Capital Economic : optional (Vasicek multifactor, RDF …)

Macroeconomic Scenarios


• System dynamics: modeling the accounts and flows. • Optimization gives us the best values of controllable flows – New

credits, portfolios sales, new funds, capital issues, ...• Limits: ratios, accounts and flows, orthogonal and combined• Restrictions: lineal and non-lineal. Internal point method• Objective function: SVA, EVA …• Computing modules : NRC, IPOPT, C++

Optimization Engine

Macroeconomic Scenario. Building The Models.

MacroEconomicVAR model

[ ] ttYB ε=Φ )(

Scenario

[ ] [ ] TttTttt YYY ,1,1*

∈∈ ⊂→∃ConditionedGeneralized Forecast

[ ]*,ˆ; YYY ΣΩ

It would be useful that the methodology used to build the

macroeconomic scenario model allowed to automatically

computed projections of the non-defined variables

B/S, Parameters, Coefficients,


Micro Economicflows models

[ ]itt

iit YLz ε,=

[ ]*,ˆ; TnTnTnTn YYY ×××× ΣΩ

Portfolioscovariance

[ ]YPortfolios G Σ=Σ

Economic Capital model

[ ]YLK tt ≤

ε as Risk Appetite [ ][ ]

( ) [ ]YLVaR

YLCDF

tt

t

=⇒=

εε

FeedsOptimization

Model

Coefficients,Maturity

Macroeconomic Scenario. Building The Models.

Optimization assumes as restrictions equalities and

inequalities about accounts and flows

System DynamicsAccountsand Flows

FeedsOptimization

Model

[ ] [ ]

xXWZ ttxt

,max =Optimization

Objective Function [ ]

[ ] LTt

Tt

xXSVA

xXEVAZ

∈∀

∈∀=,

,max


Accountsand Flows

[ ]11 ,,,, −−= tttttt xXxXGxX [ ]

[ ] nitxXF

xXGxXts

tt

itittt

,1,;0,

,,..

∈≥= −−

Output to BudgetingExecutive FormatNew scenarios

Macroeconomic Scenario. Macro Variables Forecast.

ForecastedScenario

ExpertValidations


Macroeconomic Scenario. Conditioned Forecast.

ForecastedScenario

ExpertValidations


FUNDS

PORTFOLIO

Collection

Formalizations OustandingInterest

Recoverd

Outstanding capital

recovered

Partial amortization, Prepayments

AssociatedCosts

Installments

Optimization Engine. System DynamicsThe system should be able to simulate the progression of the accounts and

flows


DEFAULT

RESULTS

Default

Recoveries

RECOVERED ASSETS

Total Debt

Bad Loan Losses

CurrentInterest

Default interest

FUNDS

PORTFOLIO

Collection

Formalizations OustandingInterest

Recoverd

Outstanding capital

recovered

Partial amortization, Prepayments

AssociatedCosts

Installments

Optimization Engine. System DynamicsThe system should be able to simulate the progression of the accounts and

flows

Eg. Mortgages(t)=Mortgages(t-1)-Amortizations(t)-Early Cancelations(t)-New Past due Loans(t)-Portfolio Sales(t)-Securitizations(t)+New Mortgages(t)


DEFAULT

RESULTS

Default

Recoveries

RECOVERED ASSETS

Total Debt

Bad Loan Losses

CurrentInterest

Default interest

- Amortizations is an “arithmetic” function of maturity and conditions.- Early Cancelations, New Past due Loans are statistical functions that depend on macroeconomic variables.- Portfolio Sales, Securitization and New Mortgages are calculated by the Optimization module.

Optimization problem can be stated as:

[ ]xXWZ tt ,max = ( ) xandX to imposednsrestrictiothedefinesit

linealnonbecanfunctionsionalmultidimenaisF

What Can Optimization Do For Strategic Planning?

An optimization based system explores automatically a

universe of possible asset, liabilities and capital structures

and chooses the best plan


[ ] [ ] nitxXGxX

ntxXF

ts

itittt

tt

,1,,,

,10,

..

∈=∈≥

−−

( )

( )( )nstransactioflowsofVectorx

accountsstatesofVectorX

criteriaonoptimizatitheDefinesW

nstransactioandaccountsofdynamicsthedefinesit

linealnonbecanfunctionsionalmultidimenaisG

xandX to imposednsrestrictiothedefinesit

What Can Optimization Do For Strategic Planning?

Asset

Asset

Asset

AssetAsset

Capital neededInternal capital

calculation

Giv

en

N assets to 1 capital

Ratios, states

Valuation

Usually…


Optimized Plan

Asset

Asset

Asset

Asset

AssetAsset

Capital Limits

Giv

en

Other RestrictionsInternal capital

calculation

Objective 1 capital to N assets (& funds)Calculated with iterations

Non lineal function

Prioridades

Priorities


If it is not possible toaccomplish all

restrictions, the systemshould allow to

establish priorities.

Optimization Engine. Restriction Analysis.

Mortgagesgranted


Restrictions can beactive or superfluous.

The system shouldthen show the

gap/excess amount.

Time

Financial prospects

Board Commercial

Commercial

Risk appetite

Strategic guides

Services

Who Takes Advantage of That?


Commercial direction

Financial direction First

commercial plan

Adjusted budget

TreasuryPortfolio manager

Detailed budget

Branches

Follow-up, risk, quality,

profitability

Funds offer

Services & credit demand

* Maximum value subject to: accounting constrains, Basel II & III rules, commercial limits, strategic guides, risk appetite

Financial prospects

Board Commercial

Commercial

Risk appetite

Strategic guides

Services

Who Takes Advantage of That?


Commercial direction

Financial direction First

commercial plan

Adjusted budget

TreasuryPortfolio manager

Detailed budget

Branches

Follow-up, risk, quality,

profitability

Funds offer

Services & credit demand

Strategic Planning

Tool*

* Maximum value subject to: accounting constrains, Basel II & III rules, commercial limits, strategic guides, risk appetite

Motivation


Conclusions

Agenda


“Financial Risk Management started as one thing and has ended as another.” (Manz, 2011)

We, risk experts, are also the best qualified on modeling business functions in Financial Institutions.

The next step into this new approach to Strategic Planning, tools for Balance

Conclusions


Optimize or die…

The next step into this new approach to Strategic Planning, tools for Balance Sheet and P&L projection, subject to Optimization criteria, in a changing environment.

Main attention to prices. Volatility. Stocastic proc esses, Fourier diffussion

Arrow, K.J. (1964), The role of Securities in the optimal allocation of Risk-bearing. The Review of Economic Studies Vol 31, no. 2 Apr 1964)

Bachelier, L. (1900), Théorie de la spéculation, Gauthier-Villars. Bankers Trust , VAR as a Risk Measure. See http://value-at-risk.net/proprietary-var-measures/ Black, F. and M. Scholes (1973), The Pricing of Options and Corporate Liabilities. The Journal of Political

Economy vol 81, 3 Elton, E.J. and M.I. Gruber (1981), Modern Portfolio Theory and Investment Analysis, John Whiley Fama, E. (1965), The Behavior of Stock Market Prices efficient-market hypothesis (EMH) Guill , D.G. (2009), Bankers Trust and the Birth of Modern Risk Management .Warton School,U.Pensivania

Market Risk



Guill , D.G. (2009), Bankers Trust and the Birth of Modern Risk Management .Warton School,U.Pensivania http://fic.wharton.upenn.edu/fic/case%20studies/Birth%20of%20Modern%20Risk%20Managementapril09.pdf JP Morgan (1996) ,Risk Metrix, Technical Document http://www.riskmetrics.com Macaulay, F. (1910), Money, credit and the price of securities, University of Colorado. Markowitz, H.M . (1959), Portfolio Selection: Efficient Diversification of Investments . New York: John Wiley &

Sons. Merton, R.C. (1973), "Theory of Rational Option Pricing". Bell Journal of Economics and Management

Science (The RAND Corporation) 4 (1): 141–183 Merton, R.C. (1995), Influence of Mathematical Models in Finance on Practice: Past. Present and Future . In

Mathematical Models in Finance, Chapman Hall. London Regnault, J. (1863), Calcul des chances et philosophie de la Bourse, Mallet-Bachelier, Paris Samuelson, P. (1965), Proof that ProperlyAnticipated Prices Fluctuate Randomly Savage, L.J. (1954), The Foundations of Statistics (John Wiley and Sons, New York). Trias, R. (1982), Rendimiento, Riesgo y Selección de Activos Financieros. Banco Urquijo Vasicek, O. (1977), An Equilibrium Characterisation of the Term Structure. Journal of Financial Economics 5

(2): 177–188.

Credit Risk


Failure – oriented (Bankruptcy / Default )----Actuarial model, Binomial Gamma Negative Binomial Distributions, Characteristic Functions

AIS (1987), Credit Scoring Models, Behaviour Scoring, shops channel.

Altman, I.E. (1968), Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. Journal of Finance: 189–209.


Beaver, H.W. (1966), Financial ratios predictors of failure Journal of Accounting Research, 4, p. 71-111.

Credit Suisse Financial Products (1997), CreditRisk+, http://www.macs.hw.ac.uk/~mcneil/F79CR/creditrisk.pdf

Fair Credit Reporting Act (1970), http://www.ftc.gov/os/statutes/fcradoc.pdf

FICO Credit Scoring History http://www.fico.com/en/Company/Pages/history.aspx

Trias, R. et al. (2008), El método RDF, El nuevo estándar de stress testing de riesgo de crédito, AIShttp://www.ais-int.com/wp-content/uploads/2011/12/RDF_Articulo_01.pdfEnglish version : The RDF methodology, the new standard stress testing credit risk http://www.ais-int.com/wp-content/uploads/2011/12/Article-01-RDF-Eng.pdf

Vasicek, O. (1987), Probability of loss on loan portfolio. KMV Corporation

Wells Fargo First Behaviour Scoring. In http://www.fico.com/en/Company/Pages/history.aspx

Other risks & other models


1990s Minor worries about .Basel II Pillar II – Systems, Pension, Concentration, Reputational, Liquidity and Legal Risk.

Actuarial approach: data collection, events distribution – Poison, Gamma distributions, Extreme Value Theory, Distribution Mixtures, Survival analysis, Statistics for rare events, convolution, characteri stic functions. …

Basel Committee on Banking Supervision (2004), Basel II New Basel Capital Accord – Pillar I. Operational Risk

Basel II Capital ratios


Basel II – Capital reinforcement. Capital ratios

COSO (1991), Internal Control: Integrated Framework. Committee of Sponsoring Organizations of the Treadway Commission.

Cruz, M., R. Coleman and G. Salkin (1998), Modeling and Measuring operational risk, Journal of Risk Vol1 No 1, pp.63-72

Hoffman, D.G. (ed.) (1998), Operational Risk and Financial Institutions. Risk Publicaations. London

Power, M. (2003), The invention of Operational Risk. Discussion Paper no. 16 ESRC Centre for Analysis of Risk and Regulation.

Baring Bank destruction (1995)

Macroeconomic


Green H.W. (1993), Econometric Analysis, Collier Macmillan

McKinsey & Co . (1997), Credit View. Research report, McKinsey & CoMcKinsey Credit Portfolio View. Econometric Model factor obtained combining real macroeconomic variables

Rösh, D. and H. Scheule (2008), Stress Testing for Financial Institutions. Risk Books

Ruiz, G and R. Trias (2011), Financial crisis and risk measurement: the historical perspective and a new methodology, in the book by Óscar Dejuan Ed.: “The first great recession of the 21st century”. Edward Elgar.

Trias, R. et al. (2009), El método RDF: Escenarios económicos para el stress testing, AIS http://www.ais-int.com/wp-content/uploads/2011/12/AIS-RDF-Articulo-02.pdf. English version: The RDF methodology:


int.com/wp-content/uploads/2011/12/AIS-RDF-Articulo-02.pdf. English version: The RDF methodology: Economic scenarios for stress testing. http://www.ais-int.com/wp-content/uploads/2011/12/Article-02-RDF-Eng.pdf

Corporate


Beazer F.W (1976), The Theory of portfolio choice and its applicability to bank asset management. Euromoney pgs 52-73

Cohen K.J. (1970), Programming Bank Portfolios under Uncertainty, Journal of Bank Research , vl1,num1 pgs 42-61

Cohen, K. J. (1972), Dynamic Balance Sheet Management: A Management Science Approach. Journal of Bank Research Winter, pgs 9-19

Cohen,K. J. (1979), A Linear Programming Planning Model for Bank Holding Companies. Journal of Bank Research Autum pgs 152-164

Monti, M. (1972), Deposit, Credit and Interest Rate Determination under alternative Bank Objective Functions. Mathematical methods in investment and finance, North-Holand, Amsterdam pgs 431-454


Pyle, D.H. (1971), On the theory of financial intermediation. Journal of finance vol 26, num 3 pgs 737-747

Sealey C.W., Jr and J.T. Lindley (1977), Inputs, outputs and a theory of production and cost at depositary financial institution. The Journal of Finance vol XXXII num 4 pags 1251-1265

Ruiz, G. and R. Trias (2012), Viabilidad de las entidades financieras y las nuevas metodologías reguladoras, Cuadernos de Información Económica de FUNCAS http://www.ais-int.com/wp-content/uploads/2012/12/RTrias-GRuiz_FUNCAS_2012.pdfEnglish Version::Viability of Financial Entities and New Regulatory Methodologies. Article originally published in FUNCAS “Cuadernos de Información Económica” (Funcas Economic Information Journal) nº 230 September-October 2012, redrafted in accordance with Act 9/2012. http://www.ais-int.com/en/viability-of-financial-entities-and-new-regulatory-methodologies.html

Tennent, J. and G. Friend (2005), Guide to business modellling, The Economist Newspaper Ltd.

Trias, R. and A. Rodríguez (1980), Simulación y optmización en planificación bancaria. Informática-SIMO.

Trias, R . (1980), El Modelo POTS de Planificación Financiera. Instituto de Economia Aplicada. Internal documentation for Planification Process Application

Van Loo, P.D. (1980), On the microeconomic foundation of bank behavior in macroeconomic models. The Economist 128 nr 4, pgs 474-495

General


Arvanitis, A (2001), Gregory, Jon. Credit, the complete guide to pricing, hedging and Risk Management. Risk books

Balternsperger, E. (1980), Alternative approaches to the theory of the banking firm. Journal of Monetary Economics 6 pgs 1-37

Bessis, J. (1998), Risk Management in Banking. Whiley,

Cannata, F. et al. (2011), Basel III and beyond. Risk Books

Malz M.A. (2011), Financial Risk Management. Models, History and Institutions. Whiley


Ong K.M. (1999), Internal Risk Models. “Capital Allocation and Performance Measurement”. Risk Books

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