The document discusses credit risk management for Chinese banks. It outlines several challenges facing banks in 2008, including improving processes to avoid bad debt, managing data and loan origination/collection processes, and balancing compliance and business performance. It also discusses the need to integrate management information and improve staff awareness of risk management. The document proposes building a credit risk management architecture that includes establishing governance over credit data and building a credit risk data mart. It emphasizes the importance of pricing loans correctly to capture both risk and the value of customer relationship management.
Cognitivo - Tackling the enterprise data quality challengeAlan Hsiao
Competing effectively in the digital age means being data-driven to make the right long term and short term decisions. However the quality of your decisions will be proportional to the quality of your facts. Data quality is the critical stable foundation for your organisation to transition to a data-driven and AI enabled organisation.
Business Intelligence System and instrumental level multi dimensional database Rolta
The PDF gives a brief introduction of business intelligence system and instrumental level multi dimensional database. As most associations still experience an absence of Business Intelligence (BI) in their basic leadership forms while executing endeavor frameworks, for example, Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and Supply Chain Management (SCM). Thusly, a model and strategies to assess and evaluate the insight level of big business frameworks can enhance choice backing.
Cognitivo - Tackling the enterprise data quality challengeAlan Hsiao
Competing effectively in the digital age means being data-driven to make the right long term and short term decisions. However the quality of your decisions will be proportional to the quality of your facts. Data quality is the critical stable foundation for your organisation to transition to a data-driven and AI enabled organisation.
Business Intelligence System and instrumental level multi dimensional database Rolta
The PDF gives a brief introduction of business intelligence system and instrumental level multi dimensional database. As most associations still experience an absence of Business Intelligence (BI) in their basic leadership forms while executing endeavor frameworks, for example, Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and Supply Chain Management (SCM). Thusly, a model and strategies to assess and evaluate the insight level of big business frameworks can enhance choice backing.
How Ally Financial Achieved Regulatory Compliance with the Data Management Ma...DATAVERSITY
A Data Management Maturity Model Case Study
Ally Financial Inc., previously known as GMAC Inc., is a bank holding company headquartered in Detroit, Michigan. Ally has more than 15 million customers worldwide, serving over 16,000 auto dealers in the US. In 2009 Ally Bank was launched – at present it has over 784,000 customers, a satisfaction score of over 90%, and has been named the “Best Online Bank” by Money magazine for the last four years.
Ally was an early adopter of the DMM, conducting a broad-based evaluation of its data management practices, and creating a strategy and sequence plan for improvements based on the results. Ally’s implementation of an integrated, organization-wide data management program including data governance, a robust data quality program, and managed data standards, resulted in a “Satisfactory” rating on its latest regulatory audit.
In this webinar, you will learn:
How Ally employed the DMM to evaluate its data management practices
Who was involved / lessons learned
How Ally prioritized and sequenced data management improvement initiatives
How the data management program has been enhanced and expanded
Business impacts and benefits realized
Major initiatives completed and underway
How Ally is leveraging DMM 1.0 to proactively prepare for BCBS 239 compliance.
EWS is an AI-based predictive analytics solution that collects comprehensive borrower information from multiple sources (internal and external to a bank) and analyses it for early identification of incipient stress, based on global compliance standards. EWS helps banks to reduce NPAs (non-performing assets) and improve profitability.
I created this document to allow resources in the financial institutional sector to benefit from someone who is experienced in supporting BCBS projects from a PMO perspective. In summary it provides the reader with a deeper understanding of BCBS and what's required to be successfully compliant. It also provides information in layman's (rather then jargon) and gives a general insight into what BCBS is about, and how compliance requirements need to align to the 14 principles.
FINANCIAL & CORPORATE COLLATERAL > portfolio // Linda C. ModicaLinda Modica
This short visual presentation contains the design work of Linda C. Modica, a NYC-Metro area art director & graphic designer. Selected published works for GSMI, IMN (Information Management Network) and Black Swan Consulting Group.
Temaswiss' Integrated Key Risk Controls (IKRC) best-practice design for Commercial Banking KYC and AML Transactions Monitoring.
- Commoditised Consulting & FSI Advisory packages.
- Tailored to your data & process realities.
- Budget- & Time-bound.
How Ally Financial Achieved Regulatory Compliance with the Data Management Ma...DATAVERSITY
A Data Management Maturity Model Case Study
Ally Financial Inc., previously known as GMAC Inc., is a bank holding company headquartered in Detroit, Michigan. Ally has more than 15 million customers worldwide, serving over 16,000 auto dealers in the US. In 2009 Ally Bank was launched – at present it has over 784,000 customers, a satisfaction score of over 90%, and has been named the “Best Online Bank” by Money magazine for the last four years.
Ally was an early adopter of the DMM, conducting a broad-based evaluation of its data management practices, and creating a strategy and sequence plan for improvements based on the results. Ally’s implementation of an integrated, organization-wide data management program including data governance, a robust data quality program, and managed data standards, resulted in a “Satisfactory” rating on its latest regulatory audit.
In this webinar, you will learn:
How Ally employed the DMM to evaluate its data management practices
Who was involved / lessons learned
How Ally prioritized and sequenced data management improvement initiatives
How the data management program has been enhanced and expanded
Business impacts and benefits realized
Major initiatives completed and underway
How Ally is leveraging DMM 1.0 to proactively prepare for BCBS 239 compliance.
EWS is an AI-based predictive analytics solution that collects comprehensive borrower information from multiple sources (internal and external to a bank) and analyses it for early identification of incipient stress, based on global compliance standards. EWS helps banks to reduce NPAs (non-performing assets) and improve profitability.
I created this document to allow resources in the financial institutional sector to benefit from someone who is experienced in supporting BCBS projects from a PMO perspective. In summary it provides the reader with a deeper understanding of BCBS and what's required to be successfully compliant. It also provides information in layman's (rather then jargon) and gives a general insight into what BCBS is about, and how compliance requirements need to align to the 14 principles.
FINANCIAL & CORPORATE COLLATERAL > portfolio // Linda C. ModicaLinda Modica
This short visual presentation contains the design work of Linda C. Modica, a NYC-Metro area art director & graphic designer. Selected published works for GSMI, IMN (Information Management Network) and Black Swan Consulting Group.
Temaswiss' Integrated Key Risk Controls (IKRC) best-practice design for Commercial Banking KYC and AML Transactions Monitoring.
- Commoditised Consulting & FSI Advisory packages.
- Tailored to your data & process realities.
- Budget- & Time-bound.
Currently pi network is not tradable on binance or any other exchange because we are still in the enclosed mainnet.
Right now the only way to sell pi coins is by trading with a verified merchant.
What is a pi merchant?
A pi merchant is someone verified by pi network team and allowed to barter pi coins for goods and services.
Since pi network is not doing any pre-sale The only way exchanges like binance/huobi or crypto whales can get pi is by buying from miners. And a merchant stands in between the exchanges and the miners.
I will leave the telegram contact of my personal pi merchant. I and my friends has traded more than 6000pi coins successfully
Tele-gram
@Pi_vendor_247
BYD SWOT Analysis and In-Depth Insights 2024.pptxmikemetalprod
Indepth analysis of the BYD 2024
BYD (Build Your Dreams) is a Chinese automaker and battery manufacturer that has snowballed over the past two decades to become a significant player in electric vehicles and global clean energy technology.
This SWOT analysis examines BYD's strengths, weaknesses, opportunities, and threats as it competes in the fast-changing automotive and energy storage industries.
Founded in 1995 and headquartered in Shenzhen, BYD started as a battery company before expanding into automobiles in the early 2000s.
Initially manufacturing gasoline-powered vehicles, BYD focused on plug-in hybrid and fully electric vehicles, leveraging its expertise in battery technology.
Today, BYD is the world’s largest electric vehicle manufacturer, delivering over 1.2 million electric cars globally. The company also produces electric buses, trucks, forklifts, and rail transit.
On the energy side, BYD is a major supplier of rechargeable batteries for cell phones, laptops, electric vehicles, and energy storage systems.
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
How to get verified on Coinbase Account?_.docxBuy bitget
t's important to note that buying verified Coinbase accounts is not recommended and may violate Coinbase's terms of service. Instead of searching to "buy verified Coinbase accounts," follow the proper steps to verify your own account to ensure compliance and security.
Even tho Pi network is not listed on any exchange yet.
Buying/Selling or investing in pi network coins is highly possible through the help of vendors. You can buy from vendors[ buy directly from the pi network miners and resell it]. I will leave the telegram contact of my personal vendor.
@Pi_vendor_247
how to sell pi coins effectively (from 50 - 100k pi)DOT TECH
Anywhere in the world, including Africa, America, and Europe, you can sell Pi Network Coins online and receive cash through online payment options.
Pi has not yet been launched on any exchange because we are currently using the confined Mainnet. The planned launch date for Pi is June 28, 2026.
Reselling to investors who want to hold until the mainnet launch in 2026 is currently the sole way to sell.
Consequently, right now. All you need to do is select the right pi network provider.
Who is a pi merchant?
An individual who buys coins from miners on the pi network and resells them to investors hoping to hang onto them until the mainnet is launched is known as a pi merchant.
debuts.
I'll provide you the Telegram username
@Pi_vendor_247
Financial Assets: Debit vs Equity Securities.pptxWrito-Finance
financial assets represent claim for future benefit or cash. Financial assets are formed by establishing contracts between participants. These financial assets are used for collection of huge amounts of money for business purposes.
Two major Types: Debt Securities and Equity Securities.
Debt Securities are Also known as fixed-income securities or instruments. The type of assets is formed by establishing contracts between investor and issuer of the asset.
• The first type of Debit securities is BONDS. Bonds are issued by corporations and government (both local and national government).
• The second important type of Debit security is NOTES. Apart from similarities associated with notes and bonds, notes have shorter term maturity.
• The 3rd important type of Debit security is TRESURY BILLS. These securities have short-term ranging from three months, six months, and one year. Issuer of such securities are governments.
• Above discussed debit securities are mostly issued by governments and corporations. CERTIFICATE OF DEPOSITS CDs are issued by Banks and Financial Institutions. Risk factor associated with CDs gets reduced when issued by reputable institutions or Banks.
Following are the risk attached with debt securities: Credit risk, interest rate risk and currency risk
There are no fixed maturity dates in such securities, and asset’s value is determined by company’s performance. There are two major types of equity securities: common stock and preferred stock.
Common Stock: These are simple equity securities and bear no complexities which the preferred stock bears. Holders of such securities or instrument have the voting rights when it comes to select the company’s board of director or the business decisions to be made.
Preferred Stock: Preferred stocks are sometime referred to as hybrid securities, because it contains elements of both debit security and equity security. Preferred stock confers ownership rights to security holder that is why it is equity instrument
<a href="https://www.writofinance.com/equity-securities-features-types-risk/" >Equity securities </a> as a whole is used for capital funding for companies. Companies have multiple expenses to cover. Potential growth of company is required in competitive market. So, these securities are used for capital generation, and then uses it for company’s growth.
Concluding remarks
Both are employed in business. Businesses are often established through debit securities, then what is the need for equity securities. Companies have to cover multiple expenses and expansion of business. They can also use equity instruments for repayment of debits. So, there are multiple uses for securities. As an investor, you need tools for analysis. Investment decisions are made by carefully analyzing the market. For better analysis of the stock market, investors often employ financial analysis of companies.
how to sell pi coins at high rate quickly.DOT TECH
Where can I sell my pi coins at a high rate.
Pi is not launched yet on any exchange. But one can easily sell his or her pi coins to investors who want to hold pi till mainnet launch.
This means crypto whales want to hold pi. And you can get a good rate for selling pi to them. I will leave the telegram contact of my personal pi vendor below.
A vendor is someone who buys from a miner and resell it to a holder or crypto whale.
Here is the telegram contact of my vendor:
@Pi_vendor_247
Introduction to Indian Financial System ()Avanish Goel
The financial system of a country is an important tool for economic development of the country, as it helps in creation of wealth by linking savings with investments.
It facilitates the flow of funds form the households (savers) to business firms (investors) to aid in wealth creation and development of both the parties
The secret way to sell pi coins effortlessly.DOT TECH
Well as we all know pi isn't launched yet. But you can still sell your pi coins effortlessly because some whales in China are interested in holding massive pi coins. And they are willing to pay good money for it. If you are interested in selling I will leave a contact for you. Just telegram this number below. I sold about 3000 pi coins to him and he paid me immediately.
Telegram: @Pi_vendor_247
1. Managing Credit Risk for Competitive Advantage in China
Richard Bisset, Executive Project manager,
Risk and Compliance, IBM Greater China Group.
Shanghai, Friday 29th February,2008
2. 2
2008 challenges for Chinese banks
2008年中国的银行的关键因素
Improve and enhance standards, systems and processes to avoid bad debt.
Manage data origination, information distribution and reporting
Manage loan origination, NPL management & collection processes
Find a balance between compliance and business performance
Find the equilibrium between centralization and control of branches.
Need to integrate management information and create value added knowledge.
Need to improve level of awareness and understanding of bank staff to improve
internal controls and governance
3. 3
Table of Contents目录
Credit Risk Management, Data and Economic Capital
Managing the information
The Credit Factory
The Pricing of Credit: The link between economic capital and CRM
Lifecycle Risk Management
Risk Management Issues
Human Capital Management – Risk Management Benefits
Conclusions
4. 4
Risk Management is the Bridge between Data and Bank Objectives with
Shareholder Value as the Target .
风险管理是用以连接数据与银行目标,即对股东的投资回报的桥梁
Risk
Mgmt
Data
Analytics
Governance
Objectives
Tools
Data & IT
Management
Processes
Moving from origination function to a risk/portfolio management function methodology
Moving from collecting interest and principal payments to a portfolio total return measurement approach
Deliver
Shareholder
Value
Business
Front
Office/Transaction
Commercial
Loans, Leases, LoC
Consumer
Auto, Residential,
Cards, HEL
Asset Mgmt
Mutual Funds,
Custodian, Financial
Planning
Processing
Solution
Debit, credit, private
labels, etc
Trading
Corp, ABS, FX,
Derivatives, etc
Others
Treasury services,
etc
Risk
Life
Cycle
View
Origination &
Acquisition
•Deal prospecting
•risk assessment
•Pricing & funding
•Credit approval
•Credit booking
Risk Mgmt &
reporting
•Payment remittance
•Provision
•Past due (30,60, 90d)
•Risk migration – NPL,
charge-off
•Performance – ROA,
ROE, P/E, Market Cap
Disposition &
Recovery
• Distressed debt
recovery/charge-off
Risk Mgmt/Basel
Risk mitigation
(hedging, securitization,
syndication)
)
(
)
(
1
1
1 /
)
)
(
(
t
t SDP
SDP
t
t SDP
Z
5. 5
•Credit Risk
default risk
credit deterioration
•Market Risk
Interest rate risk
Liquidity risk
ALM
•Operational Risk
•Legal Risk
•Reputation Risk
•Credit Risk
PD/LGD/EAD/M
•Market Risk
VaR, volatility, NII,
Operational Risk
AMA, SA, BIA
•Legal Risk
•Reputation Risk
•Hedging
Credit derivatives
(CDO/CDS)
Interest rate derivatives
•Securitization
MBS/CMO/ABS/CLO
•Syndication
senior/junior/equity
•Asset Disposition and
Restructuring
•RAROC
(Risk Adjusted Return
on Capital)
•EPS
(Earnings per Share)
•SVA
(Shareholder Value
Added)
•EVA
(Enterprise Value Added)
•External
Financial Regulators
Basel II, Sarbanes-Oxley
Shareholders
Customers
•Internal
Portfolio
LOB
Senior Management
Board
Risk Management Polices & Procedures
Risk Management Processes (Monitoring, Execution & Implementation)
ALLL (Allowance of Loan and Lease Loss)
Reserves
Capital Allocation
Economic Capital
Banks need to develop an End to End Integrated Risk Management System
Risk
Identification
Reporting
Performance
Measurement
Portfolio
Management
Risk
Measurement
6. 6
Table of Contents
The Risk Management, Data and Economic Capital
Managing the information
The Credit Factory
The Pricing of Credit: The link between economic capital and CRM
Lifecycle Risk Management.
Risk Management Issues
Human Capital Management – Risk Management Benefits
Conclusions
7. 7
Data Management: a Key Challenge for Basel II Compliance
Da ta m gt.
Proje c t m gt.
Im pl of s up Re v ie w proc e s s e s
Adhe re nc e to dis c los ure s
Suffic ie nt re s ourc e s
M gt buy -in
Othe r
0% 20% 40% 60% 80% 100%
Source: IBM Institute for Business Value analysis
Banks and Basel II: How Prepared Are They?, October 2002
Based on interviews with 32 Financial institutions worldwide
Percent Responding
Challenges:
Identifying the data
Locating that data in operational systems
Understanding the structure of the data
Extracting and transforming data
Cleansing the data
Choosing a database management system
Fast reliable access to data
Storing risk calculation and analytical
results
Production of all regulatory reports
On-line analytical processing capabilities
Data mining Source: IBM Institute for Business Value analysis
Based on interviews with 32 Financial institutions
worldwide
8. 8
Redundant and inconsistent data in various
systems that consolidate data for different
purposes
Multiple interfaces to source systems are
one of the main reasons for huge change
efforts
Reporting tools, methodologies/functions
and data warehousing aren‘t separated
properly and are often redundant
Older source systems frequently generate
additional complexity
Inland
PBC & CB
F/C DrKW
Ausland
Töchter
KDI
KDU/KRD
FIF930 SAK/CRP
KWV
KDA
KDV WEG
KDO/KDR HGD
ELBA FC RWI
WPD WERS
MABILA /
BORIS
OLB
AMI
AIDA
ADB DKW Reuschel
Manuelle
Geschäfte
Calypso
PROFIT
DreLUX
COM
FORWARD
FID/FIN MIDAS
DBLA
Globus
CORDOBA SEBIOS
KDD
PAD
ANLOS / ACBS
MARCX/BF
BF
INV
TEA KDW
Reports
MWD CDS MKB
CAD CRIS DCL/RWS
Funktionen
LOB X
Finance LOB Y
Risk Management
INV
Reports, strategies and positions
Functions
Source Systems
The major challenge is to overcome the lack of integration currently leading to poor
data quality & high costs for Credit Risk, Finance & CRM Management
Inconsistencies in overlapping reports on
business side
9. For credit risk, Banks need to build the Management Architecture
Credit Risk Data Mart
Key Area Improvement Opportunity
Set up proper governance structure to actively manage credit data,
identify credit data ownership, assign roles and responsibilities
Initiate credit data standard definition, data requirement planning, data
quality management, data security management
Development of data management tools and methodologies to enhance
data quality and analysis of the risk output, as well as to streamline the
collection, consolidation and extraction of counterparty and credit data
from the Bank’s existing systems
1 Improvements on Credit Data Governance
Establishment of data warehousing based around an open architecture
and supports the key functional areas related to the credit process,
such as risk analysis, relationship management, profitability, collateral
and asset and liability management.
2 Establishment of Credit Risk Data Mart
10. 10
This in One Possibility for Credit Risk Management Architecture
Credit Risk / Portfolio Analysis (CRS)
Core Banking System (Credit Related Processing)
EAI Technology Infrastructure
Loans Origination
(Loans Application, Credit Approval,
Document Verification & Credit
Signing)
Loans Servicing
(Loans Drawdown, Repayment
Processing & Account Closing)
Risk
Concentration
Portfolio
Summary
Credit Rating
Shift
Large Exposure
Management
Counter-party
Risk Analysis
Country Risk
Analysis
Industry Sector
Risk Analysis
Loss
Forecasting
VaR Based Analysis
Sensitivity Analysis Stress Test Analysis “What-if” Simulation
Portfolio
Monitoring
Portfolio
Analysis
Remedial Processing
(Fraud Detection, Collection, Loans Restructuring,
Past-Due, NPL & Write-off Processing,
Collateral Acquisitions & Mgt, Assets Recovery
Credit Control
(Customer Credit Review, Loans Review, Collateral Management, Customer Limit Management, Credit Management Process Auditing
& Credit Operation Reporting
Payment & Collection
Records
Loans Accounts
Loans Applications
Customer
Information File
Loans
Default
History
Payment &
Collection
History
Loans Appln
&
Scoring
History
Customer/
Portfolio
Characteristics
Credit Risk Management Data Mart
DBW
Credit Workflow Platform
Approval Limit
Control
Loan
Origination
Rule-based
Credit
Approval
Credit Process
Status
Tracking
Pipeline
Management
Performance
Reporting
Document
Management
Core Credit Risk Engine
Exposure, EL, UL
Risk Modelling (incl. PD &
LGD modeing) and Scoring
Credit Adjusted Valuation
Limits Engine Decision Engine
Risk-based Pricing
RAROC, Strategy
Simulation
Marginal Risk
Rating / Scoring
Limit Setting
Limit Monitoring
Limit Utilization
Approvals
Corporate Financial Analysis
Spreading Analysis
Financial Ratio Analysis
Historical Financial Maintenance
Future Cash Flow Forecasting
CRS Core Applications
Reporting Solution
(Reporting & Ad-Hoc Queries)
Data Mining Solution
(Data Mining, Model Validation & Testing)
11. 11
Redundant data have been eliminated and
consolidation of data is easier. Changes are
only needed to match changing markets
Interfaces between source systems and
functions have been unscrambled and are
one of the main results of the change efforts
Reporting tools, methodologies/functions
and data warehousing have been separated
properly and are much more accurate
Source systems have been rationalised and
the reporting architecture is simpler
KDI
KDU/KRD
FIF930 SAK/CRP
KDA ELBA FC RWI AIDA
ADB DKW Reuschel PROFIT
DreLUX
COM CORDOBA SEBIOS
KDD
PAD
MARCX/BF
Reports
MWD CDS MKB
CAD CRIS DCL/RWS
Reports, strategies and positions
Functions
Source Systems
With the correct architecture, the picture becomes much simpler and easier to control.
Data quality is much higher and costs for Credit Risk, Finance & CRM Management
have been greatly reduced 由于正确的架构,结构图将变的更为简单并且易于控制。数据质量
大大提高,同时风险管理的费用也显著降低
Inconsistent and overlapping reports on
business side have been eliminated
12. 12
Table of Contents目录
The Risk Management, Data and Economic Capital
Managing the information
The Credit Factory and Portfolio Management
The Pricing of Credit: The link between economic capital and CRM
Lifecycle Risk Management.
Risk Management Issues
Human Capital Management – Risk Management Benefits
Conclusions
13. 13
Transaction Processing
The Credit Factory: The constituent elements in managing the asset and
liability portfolio of the bank
信用工厂:管理银行资产负债组合的组成要素
Secondary market
management
Syndication
Credit Derivatives
Structured deals
CDOs
Origination
Active Portfolio
Management
Secondary market products
Portfolio
Credit
Customers
Branches
ALM
Secondary
market
Primary
market
Trade Processing Financial Control Product Control
Account Management
Behavior Scoring
Attrition Scoring
Response Scoring
Credit Risk Management
Application Scoring
Recovery Management
Collection Scoring
14. 14
Portfolio Business Objectives
资产组合的商业目标
Revenue Enhancement
Increased Profits from Up Sell / Cross
Sell Opportunities
Increased Profits from Strategic Line
Management Programs
Increased Profits from Targeted
Repricing Strategies
Maximize Likelihood of Repeat
Business
Improve Customer Service
Procedure Enhancement
Manage Workload/Make Efficient Use
of Staff
Lower Delinquency/Write-Offs
Control Operational Expenses
Reduce Required Loss Reserves
Lower High Risk Balances
Loss Control
Manage Workload
Make Efficient Use of Staff
Lower Delinquency
Lower Write-Offs
Control Operational Expenses
Reduce Required Loss Reserves
Lower High Risk Balances
Improve Profitability
Increase Profitable Revenue
Reduce Delinquency and Loss
Decrease Collection Expenses
15. 15
Credit Portfolio Management Process
信贷资产管理流程
Credit
Default History
Payment &
Collection History
Credit Application &
Scoring History
Customer/ Portfolio
Characteristics
Credit Risk Management Data Mart
Risk
Concentration
Portfolio
Summary
Credit
Rating
Shift
Large
Exposure
Mgmt
Counter-
party Risk
Analysis
Country
Risk
Analysis
Industry
Sector Risk
Analysis
Loss
Forecasting
Portfolio Monitoring
Portfolio Analysis (CRS)
VAR Based Analysis
Sensitivity Analysis Stress Test Analysis “What-if” Simulation
Portfolio Analysis
Industry Risk Scoring
Portfolio & Risk Management Strategy
Strategy
Matrix
Identify Current
Cycle Phase
Performance
Profile Modeling
Equivalent
Strategy
Comparison
Suitable Strategy
Selection
Implementation &
Management
16. 16
Table of Contents目录
The Risk Management, Data and Economic Capital
Managing the information
The Credit Factory
The Pricing of Credit: The link between economic capital and CRM
Lifecycle Risk Management.
Risk Management Issues
Human Capital Management – Risk Management Benefits
Conclusions
17. 17
Cost of funds资金
成本
Pure cost of funds
that the branch
would lend
Credit Premium
信用溢价
Accurate
assessment of
expected loss from
credit default
Mark-up加价
The margin that
makes the loan
profitable for the
branch
Cost of Operations运营成本
Total cost of activities conducted at the bank
(at branch and head-office levels)
Correct Pricing of loans is a Necessity….it captures both risk and value
of CRM
贷款的准确定价至关重要
How can branches use these tools to grow their revenue and profitability分行如何运
用这些工具来增加其收益和利润
How can central units better manage risk exposure arising from systemic factors总
行如何更好的管理来自系统性因素的风险敞口
CRM
客户关系管理
CREDIT
RISK信用风险
ALM
资产负债管理 Interest rate offered on a loan贷款利率出价
18. 18
The final component that brings the profit to the bank; the margin that a bank can
charge on a loan is driven by a number of factors, the skill of the banker is determining
how they can leverage these factors to their advantage
为银行带来利润的决定性因素决定了贷款利差,银行需要将这些因素转化为优势
No.
Key Factors Driving Margin 利润
驱动的主要因素
Description 描述 + ve -ve
Competitiveness 竞争力
1 客户细分 customer characteristics
The finer the understanding of peculiarities within group of
customers, the better a company can manage its risk exposure
2 产品差异化 product differentiation How is my product different from those offered by other banks
3 其它银行分行的竞争 product competition
How many banks are offering exact and substitute products in the
same market to the same customers
4 潜在的进入壁垒 barriers to entry How difficult is it for a competitor to enter the market
5 产品可获性 cross regional competition
Cross regional competition – when corporate differ to head-office
to get loans or non-bank competitors
6 人民银行控制 central bank controls
Margins on loans and deposits are only allowed within a narrow
band based on the central bank reference rate
Risk 风险
1 信用评级 PD What is the risk of default for the borrower
2 抵押交易 LGD What is the amount of collateral against the loan
3 有效的抵押品管理 process management Efficiency of the collateral management & evaluation processes
4 更少的经济资本 (对于预期损失) EC The amount of capital that has to be applied to unexpected loss
5
与全面的银行资产负债表的关联
concentration
How many loans in the portfolio are in the same region & industry
Customer relationship 客户关系
1 关系管理 depth of relationship
How deep is our knowledge of the customer and deep is the
relationship
19. 19
Table of Contents目录
The Risk Management, Data and Economic Capital
Managing the information
The Credit Factory
The Pricing of Credit: The link between economic capital and CRM
Lifecycle Risk Management.
Risk Management Issues
Human Capital Management – Risk Management Benefits
Conclusions
21. 21
From Basel to CRM : Data plus Analytics
从Basel到CRM:数据加分析
CRM platform automates customer
portfolio workflow and provides
access to customer information to
support the sales or service
dialogue
The content and format of customer
treatment and the business logic that
determines when how and what is
delivered to each customer in order to
optimise customer value
Using customer data and the rules
embedded in the customer strategies,
make customer decisions that
optimise value - before they are
needed
Customer data, data warehousing,
analytics tools and techniques,
customer value algorithms, credit
portfolio and customer scorecards
22. 22
Talking to the grey
mass
Understand
customer
value
Segment
by value
and need
Frame
strategies
for treating
customers
Decide actions
customer by
customer
Success=f (customer contact, data analytics, value strategy,
decision-making)
Product
holdings
High
Attrition
score
E-channel
preference
Yes No
Yes
Offer e-
chat room
Offer advice
service
No
Not High
Application back-out Leave page Cash withdrawal
23. 23
Customer Relationship Management客户关系管理
Credit Policies
Credit Guidelines
Credit Risk Management
Risk Appetite
Regulations
Audit and Compliance
CRM SYSTEM
Credit Bureau (Retail)
PBoC Loan Database
Demographics
Competition
Economic Factors
Political Environment
Internal Data External Data
Business Constraints Market Environment
Customer & Market data
Attrition rates
Retention Rates
Acquisition costs
Product Mix
Cross-selling strategy:
Up sell / Down sell
Pricing strategy:
Give the optimum price to the
customer to maximize profit
Credit Line management:
Increase / Decrease credit limit
according to different customer
performance
Collection strategy:
To avoid future loss on defaulting
customers
ETC…………
Anti-attrition program:
Increase customer retention rate by
better offers, fee waiving, etc
24. 24
Interlinkage between Data and Risk Strategy
数据和风险战略的关系
Risk & Portfolio Management Strategy
Customer
Relationship
Management
Risk Engine
Historical Loss Data
Credit Risk Rating Model
Generate individual PD,
LGD, EAD,M, Credit Grade
and Expected Loss
Collateral Management
From an IRB and MtM
approach
Bank’s Credit Risk Repository
Pricing Engine
RAROC
Information on cost of
funds and administration,
profitability, interest rate
risk)
Bank’s Data Warehouse
Portfolio Data
Loan
Mortgages
Cash-flow data
Collateral Data
Securities
Real Estate
Credit Derivatives, etc
Market Data
Interest Rates
Credit Spreads
FOREX Rates
Customer Information
Customer Profile.
External ratings
PD, etc
Core Banking
Administration
Disbursement
Regulatory
disclosure
Public
disclosure
Portfolio
Credit Risk
Management
Generate
portfolio
PD, EAD,
LGD,
Correlations
and cVaR
Capital and
reserves
allocation
and limits
setting
Stress-
testing
25. 25
Table of Contents目录
The Risk Management, Data and Economic Capital
Managing the information
The Credit Factory
The Pricing of Credit: The link between economic capital and CRM
Lifecycle Risk Management.
Risk Management Issues
Human Capital Management – Risk Management Benefits
Conclusions
26. 26
Risk Management Issues
• Heightened requirements around privacy, security, and various types of risk are requiring
financial institutions to take a more proactive, enterprise-wide approach to managing internal
governance and compliance issues.
• They need to leverage compliance and risk management in a way that creates new value for the
business through greater transparency, better internal controls, better compliance and increased
trust.
• Greater transparency is critical, not only because regulators and customers are demanding it, but
also because of the emergence of collaborative business models and partnerships.
• Risk management and regulatory compliance require fast, accurate and complete data, but they
also require that management and staff understand the financial institution, the regulatory
environment and, most importantly, their own roles and obligations within the organization
• The key for financial institutions is to improve governance and compliance enterprise-wide by
widening their focus from implementing software solutions that solve specific problems or
comply with regulatory and legal requirements to include facilitating a bank-wide system of staff
development and training which will ultimately help the bank grow revenue and profits, and
manage the business more effectively.
• Going forward, the most critical developmental need in banks in China will be human capital
development
27. 27
Risk Management Issues
• Appropriate Expertise
There is little value in having a world class system in place without the expertise to oversee it. The business
of finance has become increasingly complex and this complexity requires a thorough understanding of the
bank’s systems and procedures – particularly in the area of risk management
• The Human Element
The one element that overrides all others in the successful implementation of internal good governance is the
integrity of staff. It is the most important component of any internal governance program and yet it is easiest
to underestimate and the hardest to control.
• Recruitment
Recruitment of quality staff, that have strong values and integrity, and investment in training those staff to
understand the importance and relevance of core values in their daily business is the glue that binds all other
elements of a successful process together. The media is full of reports of rogue traders (most recently at
Societe Generale), or sharp practice within organizations that have occurred through either a lack of
understanding of the bank’s systems and procedures or a lack of personal integrity in an employee or group of
employees.
• Training and Development
Training in ethics and the consequences of the personal actions of employees is an important part of modern
corporate governance. But it is not just ethics and compliance. Compliance only goes so far, the staff have to
understand the mechanics of banking to give ethics any basis in fact. It has been found that the single most
critical aspect to mitigating risk lies beyond merely installing and closely monitoring world class systems. It
is in the management of human resources – from very stringent and thorough hiring processes, to ongoing
staff training and development
28. 28
Risk Management Issues
• Innovation
Banking in China is going through enormous changes and the people in the bank need to be able to change
with it. They need to be able to think outside the box and look for new ways to improve the way the bank
conducts business. Proper HR management can enable staff to embrace change, rather than fear it.
• Direction, Focus, Mission
It is very often the case that staff are unaware of what the Bank wants to achieve. The information flows
are inadequate to ensure that the Bank and its staff are moving in the right direction. Proper HR
management can ensure that the correct message and therefore the correct procedures and systems are used
to the best advantage of the bank
• Operational Efficiency
A better understanding of the job and the staff’s position and purpose in the bank can greatly enhance
operational efficiency, leading to fewer mistakes and lower losses. Proper HR management can provide the
tools and the skills to ensure that this happens
• Quality Customer Service
Staff that understand their role provide better customer service and therefore better customer satisfaction.
This is key to being able to compete effectively in the market place. Proper HR management can help staff
understand just how important the customer is and how to help him.
• Governance and Compliance
Proper HR management can instill in staff an appreciation of the bank, its environment, its role in society
and the staff member’s obligations (and those of the bank) to that society.
29. 29
Table of Contents目录
The Risk Management, Data and Economic Capital
Managing the information
The Credit Factory
The Pricing of Credit: The link between economic capital and CRM
Lifecycle Risk Management.
Risk Management Issues
Human Capital Management – Risk Management Benefits
Conclusions
30. 30
Human Capital Management - Risk Management Benefits
• Staff Development
Staff are motivated by many things, but a key ingredient is a sense of self-worth. Training should be a
reward which shows the staff how valuable he is to the organization. Proper HR management can equip
staff with the capacity to move up through the ranks in the bank.
• Results and Bottom-Line Orientation
Without the right framework in place, it is easy for lending staff to lose sight of their primary professional
function – to make profits for the bank. Proper HR management can assist lending staff to understand this
and understand the consequence of their actions in terms of bottom-line performance.
• Leadership
Every bank wants to groom the leaders of the future. Proper HR management can provide them with the
tools to achieve this.
• Teamwork
Staff in the credit areas should understand that they do not work alone, but are part of a small team of
professionals which in turn is part of a larger team. Proper HR management can instill the value of
teamwork leading to greater operational efficiency and an esprit de corps
• Loan Quality
The easiest way for a bank to lose money is in credit. A lack of understanding of a customer’s business or
the business environment can lead to serious losses and high levels of NPLs. Proper HR management can
help lenders understand the dynamics of lending and the impact bad lending decisions can have.
31. 31
Human Capital Management - Risk Management Benefits
• Staff Retention and Loyalty
Staff turnover is often the result, not only of conditions of employment such as salaries, but also of people
feeling under-appreciated. It can also have a pernicious effect on morale amongst other staff. Proper HR
management can overcome this and reduce turnover levels and increase loyalty.
• Lower level of Non-Performing Loans
China’s track record on NPLs has been lamentable and whilst the reasons are many (policy lending,
preservation of employment at SOEs) the only way to avoid a repeat of past mistakes is through training on
lending.
• Understanding of the methodology behind the Software
Under the new Basel Accord, statistical methodologies are used to calculate risk, capital requirements etc.
It is easy for lending officers to lose the ability to undertake their own analysis of customers. Proper HR
management can ensure that lending staff have the ability to make value judgments about counter-parties.
• Performance
Personal performance is key to job satisfaction and can be adversely impacted when staff do not understand
what they are doing. Proper HR management can reduce errors, increase efficiency and provide more and
better opportunities to staff for self- development and promotion.
• Profitability
The overriding objective of proper HR management is to enhance the profitability of the Bank.
32. 32
Table of Contents目录
The Risk Management, Data and Economic Capital
Managing the information
The Credit Factory
The Pricing of Credit: The link between economic capital and CRM
Lifecycle Risk Management.
Risk Management Issues
Human Capital Management – Risk Management Benefits
Conclusions
33. 33
Conclusions结论
With the right investment in data sourcing and packaging, a Bank’s capital
requirements can be better managed and the risk measured and controlled.
It is important to get the data sourcing and management right first. Reporting
and information flows will follow.
Based on internal and external information sources, the trick is to get pricing
right and correctly target the customer
In a world of securitization and credit derivatives, the effective management of
assets and liabilities, and the correct balancing of the bank’s portfolio depends on
risk identification through strong database information.
The integration of the foregoing points into Credit Risk, Customer Relationship
Management and Portfolio Management is essential, but without due care and
attention paid to the human capital issues, the effect of any such integration will be
limited and the effort to increase shareholder value will only have limited success.
34. 34
Richard Bisset’s Resume
Richard Bisset is a graduate of Leeds University with a bachelor degree in Chinese and German. Having
spent 25 years at HSBC, he joined IBM at the beginning of September 2007 as Executive Project
Manager and is now working with Global Business Services, advising on credit risk management,
compliance and governance.
During his time with HSBC he worked in many places in the Far East, but by far the most time was spent
in Greater China, either in Shanghai or in Hong Kong. A veteran of many roles, the last 12 years of his
career with HSBC was in the credit area, including 4 years as Head of Credit Risk Management for
HSBC's operations in Japan. In this role he was responsible for both the corporate bank and the securities
company, managing a diversified portfolio comprising private banking, corporate banking, financial
institutions, project finance and sovereign borrowers.
His career with HSBC culminated in secondments first to Bank of Shanghai (HSBC 8%) in 2004 and the to
Bank of Communications (HSBC 19.9%) in 2005. In these roles, he was responsible for advising on Credit
Risk Management, handling delinquent loans and implementing best practices in credit risk management.
This included creating credit policy, writing credit manuals and training credit staff.
Since late 2007, he has been managing IBM’s downstream project at Bank of Nanjing, whilst at the same
time providing input for proposals being made to other Chinese banks.