Download - OSIS at MeetFintech day 2016 - Trading
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Open Source Investor Services “OSIS”
Credit modeling 2.0
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PRIVATEANDCONFIDENTIAL
02/06/16 Credit Portfolio Management
3Main Cause of the financial crisis Bank balance sheet
Assets liabilities
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Open Source investor services
¡ Established in 2010, based in The Hague, The Netherlands
¡ Global client base: banks, bank groups & investors
¡ Our motto: Seeing through complexity of credit
¡ Structured data: bank data, CBS, Eurostat and publications from Central Banks.
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Dataquality
Datastorage
Dataanalysis
Datamodeling
Ra5ng&Valua5on Disclosure
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Data infrastructure 2.0 ¡ Low costs
¡ Low operational risk
¡ Timeliness update using automatically recalibrated credit models
¡ Analyst/ management in driver seat
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Data valida-
tion
Data- Mart
Credit Models
Prime: Analyst/Management
Solving data errors
Recalibration & portfolio info
Model outputs
Scenario input & recalibration based expert opinion
Loan Works
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Credit analysis & modeling 2.0 17
3rdgenera5onofmodels
Visual
QualityData
o Standardized data of better quality
o Focus on vizualisation
o New generation of self learning credit models
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To date
¡ We provide analytical services to over 40 banks in Australia, South Africa, Europe and
North America
¡ The volume of loans using our analytical software and models is larger than the entire
Dutch banking industry:
– EUR 600 billion, 13,5 million European mortgage loans
– EUR 150 billion, 1.5 million European SME loans
– USD 1,300 billion, 0.7 million US wholesale loans
¡ We entered into a cooperation with Bloomberg matching their library of ABS cash flow
models with our library of credit models
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Data quality amongst Dutch mortGage originators
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PDs compared with the same model 9
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Different PD per vintage 10
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PD’s at the same vintage 11
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Changes in the lending market
o According to research from Deutsche Bank, Barclays and Goldman Sachs about USD
8,000 bn of loans will shift from the regulated banking sector
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Risk takers in the driver seat 13
EndInvestor
Borrower
1.AssetManager/HedgeFund
3.InvestmentBank
2.Creditra5ngagency
¡ Much of the analysis of the End Investor is outsourced to
intermediaries
¡ 1-3 are making the best money, all can be leapfrogged
¡ Investors in the driver seat, making lending more efficient
– Lower costs
– Lower operational risk
– Better understanding hence lower information asymmetry!
1.
Bank
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Credit modeling 2.0
¡ Focus on standardized (Loan level) data:
– Banks have a huge advantage
– New lenders should work together and pool their data
¡ We put investors, senior managers and private individuals in the driver seat:
– Visualizing data
– Playing a rol in the calibration of models
– Understanding the risk.
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