The document discusses the optimization of nostro reconciliation and the challenges faced in achieving an ideal settlement process. It outlines strategies for improving data quality, reducing system complexity, and leveraging cloud solutions for reconciliation services. The author emphasizes the importance of exception management and suggests a roadmap for enhancing reconciliation efficiency through technology and process improvements.

1. Frankfurt, 21 June 2012
STP in der „Cloud“ - Vision oder Realität ?
Frankfurt, 21 June 2012
Nostro reconciliation
In the past, the present and the future
Richard F. Zbinden
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2. Frankfurt, 21 June 2012
Agenda
s Set the scene - introduction
s Objective – the ideal world of settlement
s Strategy and roadmap to achieve optimization
s Strategy implementation
s Reflections on approach
s Reflections on cost and cloud
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3. Frankfurt, 21 June 2012
Set the scene - settlement
ILLUSTRATIVE
Retail and Private Banking
Pattern Communication
Capturing Interpretation Application Fulfilment
Recognition /Feedback
1. Client 3. Client 6. Discr. 8. Procure-
data profiling 5. Clients Portfolio ment
Demand financial Management
planning 10. 11. Client
− Processing reporting
Supply Governance 7. Non- 9. Limit
2. Market 4. Research process discretionary monitoring
data
Advisory
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4. Frankfurt, 21 June 2012
In an ideal world of settlement we would have
ILLUSTRATIVE
s 100% matching rate
s No contractual or organizational risk
s No data quality issues
s No investigations to be made
No reconciliation would be required,
but…
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5. Frankfurt, 21 June 2012
The reality is different
The key drivers for reconciliations are
s Managing the counter party risks
s Control of data quality & settlement risks
s Treasury management
s Manage liquidity
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6. Frankfurt, 21 June 2012
How do we achieve optimization?
Strategy
s Improve data quality for all business processes
s Move from asynchronous to middleware interfaces
s Reduce system’s complexity while keeping audit quality
s Reduce supplier/provider complexity
Roadmap to optimization
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7. Frankfurt, 21 June 2012
Roadmap to optimization
ILLUSTRATIVE
Optimization
Automatic Matching Transaction Lifecycle Integrated Reconciliation
level Management (TLM) & Exception Agents
Maximize automation
– minimize
monitor overall investigation work
transactions
use standard flows
matching
tools • Get central visibility
• Transform an efficient into
an effective reconciliation
• Collaborate better with • Collaborate better with
internal and external internal and external
• Improve matching rates • Destroy silo people/partners
reconciliation
time
Reduce cost for Manage complexity Focus on risks
reconciliation through transparency
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8. Frankfurt, 21 June 2012
Strategy implementation
Improve data quality for all business processes
s Improve reference quality for messaging
s Eliminate media gaps
s Define business process for automatic value date or amount
differences
s Improve quality of reversals and amendments of transactions
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9. Frankfurt, 21 June 2012
Strategy implementation
Move from asynchronous to middleware interfaces
s Neartime (nearly synchronous) vs. asynchronous or batch
s Create visibility on message flows
s Improve data quality of statements
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10. Frankfurt, 21 June 2012
Strategy implementation
Reduce system’s complexity while keeping audit quality
s Simplify application landscape
s Reduce number of interfaces
s Choose value added supplier
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11. Frankfurt, 21 June 2012
Strategy implementation
Reduce supplier/provider complexity
s Outsource messaging and reconciliation as PaaS or SaaS
s Outsource the entire reconciliation business process except the
manual exception handling and related investigations
s Create shared service center using a private or hybrid cloud for high
volumes of transactions (industrialization)
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12. Frankfurt, 21 June 2012
Reflections on approach
ILLUSTRATIVE
What do you aim for?
Highly
efficient
reconciliation
Sterci (Cloud)
e.g. SAP
Sterci
TLM
Corona
Manual
reconciliation
independent
No audit trail
audit trail
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13. Frankfurt, 21 June 2012
Reflections on approach
ILLUSTRATIVE
What is your focus?
Focus on
exception
management
Investment Banking
Credit operations
Private Banking
Retail banking
Focus on
reconciliation
Automatic
Manual
matching
matching
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14. Frankfurt, 21 June 2012
Reflections on cost
ILLUSTRATIVE
Reconciliation
cost per
transaction
low volume
medium volume
low volume in cloud
high volume
high volume in
private cloud
maturity level
Automatic matching Integrated matching Agent based matching &
exception management
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15. Frankfurt, 21 June 2012
Optimization - approach
− Efficiency vs. optimization
High volume − Move to shared service center approach or Cloud
− Integrate with order management to increase
integrity and visibility of STP
− Try to bundle volumes (within group) continuous
Middle volume − Move to Cloud improvement of
data quality and
− Move to Business Process Outsourcing
interfaces
− Keep reconciliation as simple as possible
Low volume − Move to Cloud
− Move entire operations to Cloud
Software for Corporate Leaders LLC © Richard F. Zbinden - Not to be used or reproduced without written permission
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16. Frankfurt, 21 June 2012
How to contact us
Richard F. Zbinden
Software for Corporate Leaders LLC
Grienbachstrasse 38
CH-6300 Zug
Switzerland
phone +41 (0)41 761 97 90, fax +41 (0)41 761 97 94
email: rzbinden@complex-issues.ch
Software for Corporate Leaders LLC © Richard F. Zbinden - Not to be used or reproduced without written permission
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17. Frankfurt, 21 June 2012
Backup slides
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18. Frankfurt, 21 June 2012
Requirements for usage in other business domains
s The recurring need to compare data integrity between two or
more sources
s The control of integrity
s The need for exception management
s The need for escalation
s Statistics
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19. Frankfurt, 21 June 2012
Potential areas of reconciliation
Retail and Private Banking
Pattern Communication
Capturing Interpretation Application Fulfilment
Recognition /Feedback
1. Client 3. Client 6. Discr. 8. Procure-
data profiling 5. Clients Portfolio ment
Demand financial Management
planning 10. 11. Client
− Processing reporting
Supply Governance 7. Non- 9. Limit
2. Market 4. Research process discretionary monitoring
data
Advisory
Software for Corporate Leaders LLC © Richard F. Zbinden - Not to be used or reproduced without written permission
19