Category Archives: Risk & Relationship Based Pricing

A series of posts describing the main principles of pricing for retail banking products

e-book on Risk and Relationship based Pricing Models and Strategy

This is a last posting on the pricing model and strategy.

I have transformed the pricing posts into an e-book, titled Risk and Relationship based Pricing. The e-book  is based on the posts of the blog, reorganising them, correcting many small and bigger mistakes, spellings and typos!

You can get this e-book (100% free) by sending me an email request on cw@bankstrat.com.

Please add your occupation, employer, and if you are interested in receiving offers for training or additional information on this subject. I may restrict the transfer of the e-book if the request is not legitimate.

Thank you for your continued support.

Clive

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Risk & Relationship based Pricing Part 5

This continues and completes the description of good risk and relationship based pricing principles.
Principle 6: Define cost allocation strategy and models
As a general principle all customers should pay the costs associated with the product they buy. The questions are:
1. What costs should be allocated?
2. With what level of granularity should these costs be allocated?
3. How are you estimating these costs?

In the ideal world the cost allocations should be done are the most granular level possible. This means, as an example, that the ATM costs should be allocated to each customers on the basis of the ATM usage by the customer and all ATM may have a different cost structure on the basis of location and other variables. This requires a very big and complex cost allocation system that can individualise all costs (and revenues) at client/ contract level. Teradata for example has such an application, but be warned it’s a big project to implement!
But is this good enough? Not if you just allocate past costs, as we are looking at future cash flows of revenues and costs! Those future costs will vary in time due to inflation, capacity, operational efficiency etc. This means you have to estimate future volatile costs based on historical allocations. Not impossible but definitely not easy.
What could be the consequences of allocating future costs as they are expected to occur, while revenues are dependent on the contract characteristics? Take a mortgage with fixed monthly instalments. The revenues of such a contract will be very high during the first years then very quickly drop to become small in the following years, while operating expenses for this contract will remain stable and even increase through inflation. The net profitability schedule will show higher profits followed by many years of losses! Actually this is the simple consequence of accrual accounting and should be adapted in management accounting.
Some banks want to allocate all costs down to the taxes associated with the product. That is actually easier to do, but is it correct? Should the customer pay the bank’s corporate income tax, or the Chairman and CEO’s airplane? Should the customer pay the cost of the Equity allocated to the products he buy’s.
In my opinion the answer is definitely no. The principle is that customers must pay the expected losses and the expected operational expenses (direct and indirect), but that the shareholders should pay unexpected risks and indirect costs, at least the indirect costs generated because of the nature of the corporate activity (being a bank) and thus including regulatory expenses, general management, audit and control costs… Yes these should be paid by the shareholders through reduced net profits (RoE) and dividends. An all-in cost invoiced to the customers would have them pay the inefficiencies of management and would make the banking products unaffordable.
Also core is the cost quantification model used. What cost accounting models should be applied? Average costing by product, by process or activity based costing…?
Decisions on the cost allocation strategy will fundamentally change product pricing and profitability. What is appropriate for your bank, your market, your global strategy? How is your bank analysing this/ Life Time Value of the contract, or if you prefer the Fair value of the contract after all costs allocations appears to me as the only financially correct way of giving a value to that contract/ client.

Principle 7: Define, quantify and manage current and future client profit and value contribution
It is evident that bank profitability and shareholder value requires appropriate pricing. But excess pricing can destruct value by killing growth and client satisfaction. To avoid that pricing must be “efficient” i.e. be fixed on the basis of risks and market/ client specific demand and price elasticity.
We believe this means that client pricing but consequently the client’s profitability analysis, must be granular and forward looking. Average profitability of products, multiplied by the contract size, which is added to the profitability also calculated on an average basis, will only give you an average historical profitability of little use to manage your client in the future.
Is your profitability analytics compatible with modern value metrics, such as the Customer Fair Value, which we can be summarised as the fair value of the client current product holding (multiplied by client behavioural variables) plus fair value of future product holdings (multiplied by the related client behavioural variables).

risk adjusted current and future client value

 
risk adjusted current and future client value

Such a model will highlight and individualise the behavioural sales/ marketing risks and allow the management of business uncertainties. LTV is metric to integrate and manage all client value drivers: profitability, growth, risks and time.
We will discuss customer value in détail in a future series on this blog.

Principle 8: Manage competitive pricing
How should the bank integrate pricing information from the market, from competition?
What should the bank do when it models a theoretical risk and relationship based price (for a product sold to a specific prospect) which differs from the market prices?

  • Reduce its price to meet competition?
  • Increase its price when it is lower than the market price?
  • Keep price unchanged?

A simple question but a very complex answer, requiring a multi-dimensional analysis!

  •  How to handle market inefficiencies and bank specific inefficiencies?
  • How do you integrate product life cycle and relationship life cycle?

These multidimensional analysis should allow you to understand pricing inefficiencies and market/ pricing opportunities, but don’t make the client pay for your inefficiencies and always manage pricing in a transparent and open way with the prospect client.
Remember abnormally high spreads can lead to immediate profits but negative values because of increased attrition. You need a long term value measure to manage your client over a long term horizon, and the at least the life time cycle of the product holdings!
Strategically you may want to sell a product at breakeven or at loss because you are buying market share or you have bundled that product with high profit/ value products. In all such cases you must calculate the loss and/or negative value generated for allocation as a cost to sales/ marketing.

Principle 9: Manage the complexity and risks of your quant models.
Bank management is complex because cash flows are volatile and behavioural. Managing that complexity requires deep understanding of the market, the client, and the product value drivers.
Each bank must adapt the complexities of its business models to its needs and markets. It should use quant models that are useful for its specific strategies and market constraints (often restricted due to weak data quality and availability).
From a practical perspective, the bank’s sales force does not need to understand all these complexities. You must package products in a way that can optimise the sales unit efficiencies.
Likewise clients do not need to understand all the complexities of the product. Managing risk and operational intermediation risks is what bank should do. They must package the products to make them attractive but without hiding any financial risks that you could be transferring to the product buyer. If you sell a variable rate mortgage inform the customer that there is risk in such a product for him (the bank has passed the financial risk to the customer because it will not or cannot manage the interest rate…). Finally be transparent in pricing, client will understand and appreciate this honest and professional attitude.
Ensure strong communication between your sales force and the clients, based on a simple list of core variables such as:

  • Price is dependent on risk and collateral,
  • Standard, off-the-shelf transactions are cheaper than tailor made products,
  • Pricing is a function of operational process, automated process (internet banking) will be cheaper than 1:1 branch operational support.

Principle 10: Adapt the organisation to the requirement of risk and relationship based pricing
A close integration of all risk management processes and policies with other parts of the process flows, will generate operational and management synergies. In other words banks should consolidate management analytics and resource allocations and break operational silos. This has often been said but not often realised! The evolution of data management and management analytics can achieve what enterprise culture has often shied away from!
Consolidation of management analytics and resource allocations will include Enterprise wide Risk Management (ERM) capabilities, with often new and specialised functional responsibilities (Risk Transfer Pricing, Economic Capital budgeting and allocation, Risk policy recommendations and strategy implementation…). On that subject please don’t look at ERM as an organisational issue (bring all risk functions under one umbrella headed by the CRO. ERM is much more that that!
Breaking operational silos is ensuring that the process flows are managed from client product request to product delivery in the most efficient and effective way, and is focused on client satisfaction and the bank’s performance criterias (KPIs) including operational capacity usage and cost efficiency, Economic Equity optimisation etc.
I recommend that such an integration project completes a thorough “impact analysis” on all aspects of the business model: Process, Organisation, Data, Applications and Technology, or PODAT analysis.

Principle 11: Integrate pricing process within an efficient process flow management system, from the origination of the client request to its fulfilment
Pricing is just one element in a chain of processes from origination to product delivery.
In the case of a loan these will include:

  1.  application analysis and qualification,
  2.  product matching to client requirements,
  3.  credit analysis – – scoring & rating,
  4. credit structuring & pricing,
  5. credit approval,
  6. documentation development and signature,
  7. verification of condition precedent,
  8. disbursement(s),
  9. contract management (interest payments, interest rate fixings…),
  10. collection.

Any delay or mismanagement of any of these activities (themselves usually divided in multiple operational, analytical and management process) will have negative impacts on the bank’s value drivers!
Control and automation of these activities and process are essential to sustain efficiency and strong business development.
The activities and process are data driven, rule driven and model driven. Without clear Policies and Procedures the bank cannot achieve operational efficiencies and respond to international standards of good management. The bank must manage the related operational risks and have strong audit trails on all activities.
Regulatory constraints and capital adequacy rules are dependant of these activities and must be fully integrated.

Principle 12: Integrate risk underwriting and pricing in an integrated sales and marketing strategy
Efficient process, good pricing models and strategies can result in very bad client management if behaviour analytics are weak and below standard.
We will define the behavioural analytical models as:

  • Credit scoring models that allow appropriate credit risk rating (for risk management purposes and/ or not for regulatory purposes);
  • Collection scoring for appropriate collections management;
  • Marketing scoring models that allow the development of appropriate client information (intelligence) such as sales propensities, attrition risks etc.
  • The client score card for credit risk and product ownership (business) risks is a core input in financial risk management (interest rate, liquidity) and capital management.

Risk appetite and risk allocation will be RAROC (or RORAC) dependant and global strategy must manage the Earning at Risk (EaR), due to all the risks underwritten by the bank.  An Adjusted Return on Risk Adjusted capital (ARORAC) is an interesting approach of integrating the bank’s solvency in the equation. We will define ARORAC as the RORAC minus the Risk Free Rate (RFR), divided by the banks’ market beta.

Principle 13: Optimise risk appetite, risk budgeting and allocation and pricing towards clear and precise performance criterias
The 2008 – 2012 great banking crisis has imposed stricter internal risk management constraints not only in capital adequacy but also and possibly more importantly in the bank risk policies, strategies, models and process of risk management.
Consequently this puts new challenges in the Financial Control function of the bank and in its management accounting policies and procedures.
In parallel financial accounting (IFRS) is implemented and includes different approaches to the risk management concepts defined under the Basel Accord and Best Risk Management Practices(BIS).
All the approaches are valid, but different hence they need to be reconciled!
Shareholder Capital is at a premium. It is rare, expensive and insufficient to cover all the needs of the market. Strict Economic and Regulatory Equity management is an absolute requirement. This translates into new solvency management requirements.
Banks develop new Key Performance Indicators (KPIs) to meet these challenges. They must be integrated into pricing to generate value manage value drivers.
This can only be achieved if pricing is relationship based and risk based.

Conclusion
This concludes the series on risk and relationship based pricing. I realise that this helicopter view of the “best of class” approach can seem excessively complex for many banks and markets. High competition, highly volatile markets, the increasing complexity of products sold and the increasing weight of regulatory constraints, will force all banks to enhance pricing models and strategies.
I hope my view of the subject will generate comments and discussions.
Please don’t hesitate to add yours on the blog.
Next series will cover customer value metrics.
I will then start a new series regarding a new approach in credit risk management using available but rarely used data. I’m talking of Event Based Credit Management, which I am developing with a good friend and partner, Mark Holtom. Mark is founder and general manager of eventricity an expert in Event Driven marketing. I strongly recommend you check him out on www.eventricity.biz

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Risk & Relationship based Pricing Part 4

I believe we have shown in the previous blog postings, that pricing can be complex as it integrates many management aspects. That does not mean the pricing strategy and model used by a bank needs to be complex and based on expensive pricing applications. The pricing model must be adapted to the bank’s business strategy and environment; it should also be based on core principles of good pricing.

In our previous blog we mentioned other concepts that we will review later, such as customer profitability and Life Time Value. We will do so in a separate series that should start early May. Stay tuned and get an email advice by following the blog.

Before we start the review of good pricing principles, I need to discuss a number of requests received from readers of our last post: Can I send them a copy of the models, formulas used in the pricing exercise in post #4 ?

It is difficult to give a complete answer to the request because there are many sub-models in the pricing model. The inputs are also dependant on many additional models used by different units of a bank. Let me give you a few examples to illustrate this.

  1. Cost of Funds. The CoF is based on matched Modified Duration & Convexity or VaR, depending on the market and capabilities of the bank. That also includes all implicit optionalities such as delayed drawdowns, pre-payments… In some instances this includes specific market calculated liquidity premiums; in others best estimations of those premiums using a more deterministic model.
  2. Credit risk is based on PD, EAD, LGD. Each of these is dependent on multiple different models, including different scoring and valuation models…
  3. Customer Value can be a simple estimation of profitability or a more complex Life Time Value (LTV) calculation.
  4. Economic Equity. There are many different approaches of calculating Economic Equity, which as you know goes beyond Basel II and/ or Basel III. They also have different quantification models…
  5. Risk diversification/ concentration uses classic portfolio theory approach. The difficulty is in defining the future/ projected variance and covariance. To estimate these you can use many different models (Bayesian approach or simply historical statistical models…)
  6. Cost allocation. Do you use ABC, PBC… or other models and which costs do you allocate (fixed and variable costs? direct and indirect costs? Cost of Equity?…)
  7. Etc.

The appropriate pricing model is bank specific, as it is dependent on the strategy, activities, markets and corporate vision. It can be based on very complex or very simple models but always needs a full understanding of the variables or value drivers. The bank must control of the calculation models (no black boxes). The calculations I used in this blog are highly simplified models that are just good to illustrate the issues I want to highlight.

We recommend you start with a “pricing policy and process assessment” of your bank’s current state, develop a future state vision (what you want to achieve in line with the bank’s strategy and banking model) and develop a project to bridge the gap between the current state and where you want to go.

My company can help you in such a project. Send me a message at cw@bankstrat.com for any additional information required.

Strategic principles of good pricing:

At this stage I count 13 core principles for good pricing. I’m sure we can add a few but these would be specific to an activity, market, bank, and would probably relate to different sales strategies. I want to focus on the generic principles relating to the pricing of financial products.

Principle 1:   Price integrates the volatility (risks) of projected future Cash Flows

In my first post on pricing, I indicated the difference between financial products and services versus other manufactured goods. Again the main difference is that profit margins are realised during the whole life of the product, by opposition to profits realised at the day of the sale of a manufactured good. This difference is essential because profit margins are dependant of future volatile cash flow. The volatility is generated by all the risks associated with each product sold.

Profitability cash flows of Manufactured Goods versus Financial Products

Profitability cash flows of Manufactured Goods versus Financial Products

What are the risks that need to be defined, quantified managed and expensed to the client in pricing? (1) Credit Risk, (2) Interest Rate Risk, (3) Liquidity Risk, (4) Foreign Exchange Risks, (5) Business Risks, (6) Operational Risks, (7) Regulatory (Compliance) Risk.

Principles of good risk management are based on the separation between expected and unexpected risks. They require differentiated treatments in pricing!

  1. Expected Risks are managed through (1) hedging by collateral or other risk mitigation technics and (2) provisioning strategies. In both cases the      “cost” of managing the risk is passed on to the client through adequate      pricing.
  2. Unexpected Risks are managed through equity. The equity adequacy regulations (BII & III) define the amount required to be invested by shareholders to cover the activities of the bank. The cost of managing those risks is born      by the shareholders.

The quantification and management of all these risks is complex and require fundamental adjustments in the bank’s process, models, competencies and strategies.

Risks are also multidimensional and must also be viewed on a contract basis (variance management) and on a portfolio basis (covariance optimisation). Covariance management is done within each risk portfolios and between different risk portfolios. We can develop different way of integrating covariance costs/ benefits in pricing?

These questions need to be discussed at bank level as different approaches are possible. The approach will be described in the bank’s Risk Policies and Procedures and in the bank’s Pricing Policy and Procedure.

Principle 2:  Individualise all risks, price and manage to optimise their variance/ covariance on a 1:1 basis

Banks are moving from standardised products (amount, maturity, payment frequencies…) towards 1:1 marketing and product adaptation to specific client requirements (if not tailor making). The characteristics of each financial contract are then specific and require 1:1 pricing.

Client behaviour analytics are showing major differentiations between client and even client segments. The future expected behaviour can be defined and analysed. It is a crucial element of the products’ future cash flows and the value of the client relationship. To achieve this, data granularity is important. Technology allows such approaches and must be leveraged.

Risk concentrations and diversifications will be managed at product, client, market and bank portfolio levels. Price and management of all risk classes imply the integration of risk covariance (Interest rate and credit risks; credit risk and liquidity risk…).

To allow the implementation of such a risk adjusted model, the bank must develop a complete set of contract level Risk Transfer Prices (RTPs) with the appropriate valuation models. This includes Fund Transfer Pricing, Credit Transfer Pricing, Liquidity Transfer Pricing… and Expense Allocation/ Transfer Pricing.

The development of such an integrated risk based model is transversal and vertical across the whole organisation. It requires a full impact analysis and feasibility analysis. There are recommended methodologies to define the impact of such a business model, starting with a clear definition of the Business Principles to be implemented, the Assumption underlying the project and the Constraint applicable to the strategy. This is not a trivial project.

Principle 3: Understand the client elasticity to pricing on a multidimensional factor basis.

Most marketing/ sales/ distribution departments measure performance on the basis of volume (new transactions, campaign hit rate and transformation rates…), with very little on 1:1 pricing. Mispricing will negatively impact product sales propensities, in ways that go beyond a simple a sales volume metric.

For example the bank can integrate price elasticity with client solvency. If not there is a high probability of selling the wrong product to the wrong client at the wrong price. Low (good) rating prospects will have zero purchase propensities to high priced credit products, but high risk rating prospects will have high purchase propensities of loan products whatever the price. Pricing on the basis of average risk ratings and rating cut-offs rather than individualised risk based pricing, will lead to a risk degradation of the credit portfolio and of its risk adjusted return!

 
sales propensities per risk rating and risk price

sales propensities per risk rating and risk price

Too many retail banks are still using standard product prices that they only adapt to the customer through a “negotiation/ commercial margin” that is assigned to the sales unit. This is NOT individualised or 1:1 pricing, it just allows weaker sales unit to sell on price, and the strong client to force pricing down.

Bad pricing is a source of attrition of your best clients, those that will create sustainable profits, LTV. This is an important business risk resulting in a steady erosion of the bank’s value (goodwill).

Principle 4:  Define, quantify and manage business risk

What is business risk?

From the bank’s perspective Business risk covers a very wide set of issues, but for our discussion we will limit it to the risk of not achieving the expected (budgeted) performances in client relationship growth and profitability. This may be due to a number of internal and external factors. Again we will restrict this to the business risk from a sales/ marketing perspective, in which case we can define it as the risk that the client and prospect do not meet the projected behavioural estimated targets planned by the bank. That the sales propensities were lower (or higher) than anticipated, that cross sales and up-sales do not meet plans, that attrition rates were higher (or lower) than expected… Consequently the bank does not achieve its planned growth and profitability, its return on marketing costs.

business risk management by targeting improved performance and reduced volatility of the targeted performance

business risk management by targeting improved performance and reduced volatility of the targeted performance

One way of looking at it (and model this) is to estimate an expected result (for example the client’s LTV) and the dispersion around that expectation, measured as the Standard Deviation (STD). Managing the business risk is then the science/ art of increasing the expected LTV from A to B, and to reduce the STD of the return from STD1 to STD2, by implementing the appropriate strategies in:

  • Product development
  • Distribution strategies
  • Marketing campaigns
  • Pricing strategies
  • Etc…

Note that this 100% different to classic satisfaction surveys or other methodologies often used to estimate client behavioural variables. Indeed client satisfaction surveys do not allow the bank to measure and manage its growth and profitability targets, as it does not quantify the factors generating growth and profitability. What you need are behavioural models that can discover those factors and explain the causalities of client actions and expected future behaviours.

Principle 5:   Adapt the pricing strategy to the banks market strategy and client value proposition

Before you can define your pricing strategy, the bank must decide what its market vision and strategy is, what value proposition it wants to propose to the market.

You may want to use the approach developed by Michael Treacy and Fred Wiersema (The discipline of Market Leaders) or any other that focuses on what and why clients are buying from one bank rather than another.

Treacy and Wiersema suggest that customers will seek 3 core values from its suppliers of goods and services: “client intimacy”, “operational excellence” or “product innovation”. They also state that companies that are clear leaders in one of these values and hold a strong at par position in the other two will be the market leaders and have above par performances. Finally, the analysis shows that the business models (process, organisation) and the technical requirements (data, application, technology) are different for the three strategies, hence no one can hope to be the best in the three value sought out by the clients. Note also that Customer Intimacy is not equivalent to Client Centricity! Client centricity is to focus on delivering a product/ service that maximises the client’s satisfaction which can be either operational efficiency or customer intimacy.

In regards to retail banking two of these approaches are clear options: Customer Intimacy (Developing a 1:1 relationship based on analytics and proprietary information) and Operational Excellence (Mass marketing of standard products delivered at the best price and without any operational glitches). Product Innovation is more difficult to apply to banking because of a number of factors which I will not expand on here and now.

Customer Intimacy versus Operational Excellence bank models

Customer Intimacy versus Operational Excellence bank models

Imagine two banks with two different value approaches, where Bank A wants to focus on customer intimacy, while Bank B is targeting operational excellence. They will need to organise and build two very different types of banks, with different organisations, process and skills based on specific technology and analytics. They will also develop fundamentally different pricing strategies.

I will soon continue the review of the remaining pricing principles. Meanwhile give me your comments and be advised by email of the following posts!

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Risk & Relationship based Pricing Part 3.2

So what was your recommendation to the bank for the quiz in my last blog?

  • Client A (20 year mortgage at 4.803%)?
  • Client B? (4 year consumer loan at 4.734%)?
  • 80% A, 20% B a mixed portfolio?
  • 20% A, 80% B, a mixed portfolio?

And the answer is… Well it is not an easy straight forward one. First let’s check if:

  • We have all the information needed to make an informed decision?
  • We are sure that we know and understand, the performance criterias used by the bank?
  • We know and understand the financial models used to calculate all the decision variables, the risk and relationship value drivers?

To make a good decision, we must:

  1. Focus on the value drivers of the different opportunities. But how to define and measure value?
  2. Analyse the risk adjusted financial performance of each opportunities. But which risk and how to measure them?
  3. Analyse the value of the relationships we will gain and the value of the one we will lose! But what is customer value and how should we measure it?
  4. Plus, plus, plus…

A very simple question, but a complex problem to model and a tougher management decision than it looks! The data used in the calculations of this simple example are simple indication of the real world conditions. The models use standard, simplified formulas. I will not go into the detail of the calculations (if you need to understand the methodologies proposed you will need to contact me on cw@bankstrat.com).
The financial performance analysis.
To start the analysis let’s decompose the total interest rate revenue for the four portfolios. The results of this decomposition is summarised in the following table.

Portfolio

Interest Rate Revenues

Gross Interest Margin

Interest Margin less   Liquidity premium

Risk adjusted Margin

Net Operating Margin

Client A

4.787%

0.89%

0.68%

0.47%

0.20%

Client B

4.777%

1.43%

1.28%

0.59%

0.15%

C = 80% A +   20% B

4.785%

1.00%

0.81%

0.50%

0.19%

D = 20% A +   80% B

4.785%

1.33%

1.17%

0.57%

0.16%

Notice the huge differences in the results depending on the level of the analysis and the total reversal of conclusions: Portfolio B starts as the best option with 1.43% gross interest margin, but drops to the worst position if the margin is credit and liquidity risk adjusted (the interest rate risk is hedged in the Gross Interest rate Margin) and adjusted for operating expenses!

Based on the models used, the cost of hedging risks and the allocation of fixed and variable direct operational expenses, the asset portfolio with the highest return is Portfolio A which is a surprise, as it is higher than diversified portfolios C and D. This of course is due to the fact that the diversification benefits are not integrated in the price, in other words they are not handed over to the clients but reserved to the shareholders.

The shareholders need to invest in the bank enough capital to cover the expected risks and unexpected risks (as defined in principles by the Basel Accord). That amount of equity should include the diversifications benefits or deficits. The Economic Equity calculations indicate that the minimum requirements (Basel II without the additional cushions of BIII) as expressed as a % of the total asset (loan portfolio), are of:

Portfolio A:         0.78%

Portfolio B:         1.35%

Portfolio C:         0.80%

Portfolio D:         1.17%

Surprisingly portfolio C requires more capital than portfolio A, it is this more risky than A, although it is a diversified portfolio. This is due to the relative levels of the expected losses (a function of the Probability of Default, Exposure at Default and Loss Given Default), the variance of Probability of Default and the covariance of the portfolio PD’s.

The RORAC (risk adjusted Return on Risk Adjusted Capital) is calculated of the Economic Equity based on expected and unexpected risks, i.e. using the loan loss provision estimations and the diversified value at risk of the portfolios. On that basis the bank should decide on investing in portfolio A as the risk adjusted return is the highest, although Portfolio C is also attractive thanks to the benefits of diversification:

Portfolio A:         25.65%

Portfolio B:         11.12%

Portfolio C:         23.66%

Portfolio D:         13.70%

In theory, and in practice, the bank needs to generate value for its shareholders, hence the risk adjusted return (RAROC) must be greater than the Cost of Equity as this and only this will produce economic added value for the shareholders.

I used some hypothesis to calculate the minimum return to cover the cost of equity or “hurdle rate”. These cover the solvency strategy of the bank (single A), the beta of the shares, the market premium… i.e. all the variables of a classic economic value model as per the Capital Asset Pricing Model (CAPM). The hurdle rate calculated is 18.63% and consequently the Economic Value Added contributions (EVA) of the 4 portfolios are:

Portfolio A:         + 7.02 %

Portfolio B:         –  7.51 %

Portfolio C:         + 5.04 %

Portfolio D:         –  4.93 %

Only two portfolios create shareholder value the other 2 destruct value potentially because loans B is mispriced! Can I improve those conclusions by looking at a Return on Risk as defined in the Sharp Ratio (excess return on the standard deviation of returns)? This show that the diversification benefits of portfolio C would favour that investment rather than portfolio A.

Portfolio A:         1.27

Portfolio B:         0,63

Portfolio C:         1,41

Portfolio D:         0,83

Anything above 1 indicates that expected excess returns exceed the risk associated with that return, and C with a ratio of 1.41 is a clear winner.

The diversification benefits will be influenced by multiple factors and dependant of the valuation models used.

Diversified Portfolio STD   Undiversified Portfolio STD    Diversification benefit

A:  0.15789%                                0.15789%                                      0.00000%

B:  0.23844%                               0.23844%                                     0.00000%

C:  0.13501%                               0.17400%                                      0.03898%

D:  0.19335%                              0.22233%                                     0.02898%

We have not optimised the portfolios on a variance, covariance basis (correlation of 0.60), nor have we optimised pricing en operational efficiency. These management strategies would be defined in a pricing strategy and model.

Is the financial analysis complete? There is a last aspect that should be analysed.

If we calculate the Present value of the future Net Operating Profit contribution of each portfolio, we will also integrate another important aspect of annual profitability, which is the fact that each contract will produce annual returns over its whole life. In other words RORAC is an annual profitability measure not a measure of value of the whole stream of revenues! The equity values of contract with a return of 1% per year maturing in one year, is different to one producing 1% every year for the next 10 years.

We can estimate the value of the contract profits flows as the Present Value of those cash flows discounted at the appropriate risk adjusted discount factor. Again note I’m not calculating the total value of the contracts but only of the value of the excess returns after cost of risks and operational costs allocations.

Taking some calculation shortcuts, the values are as indicated in the table below. We can now calculate the “Fair Value” of the excess net returns generated. Without surprise Portfolio C remains the best choice if you look at the relative excess value to per value of risk unit, between ( ).

Portfolio A:         € 2,549 (462%)

Portfolio B:         € 529      (  63%)

Portfolio C:         € 2,117  (449%)

Portfolio D:         € 899      (133%)

This indicated that the sustainable long term excess value of portfolio A outweighs the reduced risk of portfolio C.

Relationship Adjusted Value decomposition

The last missing factors to be integrated are the relationship variables: the value of the expected behavioural attitudes of clients with the existing product holdings (attritions, prepayments, drawdown…) but also probability/ propensity that these clients will “buy” other products because of the relationship built on the back of the initial contract A and/ or B (cross sale, up-sale…).

There are many approaches to estimate the value of this potential activity growth (positive or negative growth). The most logic being to estimate the “fair Value” of the expected contracts sold, adjusted for their sales propensities, attrition risks and financial risks.

Combining both values will give us the true Life Time Value of the client or Client Fair Value.

From a financial perspective we are calculating the financial value of the bank’s goodwill created by the growth generated by using its business capacity (distribution network, operational back offices…). Hence we can try to reconcile the market capitalisation value of the bank by adding the fair value of the goodwill with the accounting fair net asset value.

Is this important? I believe that if you don’t measure something you will not manage it. By making the effort of measuring the drivers of value contribution you will define client relationship variables to be managed and priced. Examples of value drivers and business risks that can be quantified and managed include: cost of attrition risk, return on marketing campaigns, and contribution of next best product… plus of course “price the relationship value”!

It is not uncommon to see (even large and advanced banks) budget marketing strategies based on incomplete and sometimes misleading information. One was planning campaigns to reduce attrition of the least profitable clients will doing nothing to retain the more profitable ones, only because they were using average profitability data to segment their client base. Using Life Time Value over 85 % of the client would have been assigned a different profitability segment!

Conclusions

The consequence of mispricing and of approximate profit and value contribution are not trivial.

The mathematics does not need to be rocket science, but a robust analytical model adapted to the business model of the bank and its sales and marketing strategy should be implemented.

In the following blogs I will review the core principles of good pricing strategies.

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April 6, 2013 · 4:56 pm

Risk & Relationship based Pricing Part 3.1 – A simple quiz.

Before we dig into our pricing principles, I’d like to propose a very simple pricing exercise.Imagine you are the bank’s new business officer. You have to recommend one and only one loan. Which one will it be? The bank is short of equity following Basel III, so cannot take both but would be ok with a certain portion of both, say 80% A and 20% B or vice versa.

Client A
Loan type Annual fixed instalment
Credit Rating 2
Loan Amount € 150,000
Maturity(years) 20
All-in Rate 4.79%

Client B
Loan type Annual equal reimbursement
Credit Rating 3
Loan Amount € 150,000
Maturity(years) 4
All-in Rate 4.78%

Other elements you are given before you can make any decision are:
1. The prospect borrowers have been scored and rated as 2 and 3 (on a rating scale of 1 to 10, with 1 being the best).
2. The current Yield Curve for risk free interest rates, from 1 year to 20 years is as follows:

YC pa in %
1 year 3.35%
2 years 3.45%
3 years 3.75%
4 years 3.85%
5 years 4.00%
7 years 3.95%
10 years 3.90%
15 years 3.75%
20 years 3.50%

3. The bank is under huge stress to maximise profits because it needs to attract new capital and compensate the huge costs it has been faced with following the latest large compliance investments and liquidity crisis.
So, which one will you recommend for financing by the bank, Client A, Client B or a mix of both?
Send me a word (cw@bamkstrat.com) or give your opinion through the LinledIn.com poll!

I’ll give you the answer in a few days.

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April 3, 2013 · 9:25 am

Risk & Relationship based Pricing Part 2

Bank Pricing Strategy 2

The opportunities and issues to organise a pricing strategy and develop pricing models that can enhance value based management.

I mention value based management as the ultimate objective of good banking strategy. This needs a short explanation. Value based management refers to the management of future bank profitability, not on the budgeted profits of the year. What we want to maximise is the value of the firm calculated as the present value of projected profits streams resulting from existing financial contracts on the books of the bank (assets, liabilities and off balance sheet) plus the present value of profits derived from future sales of financial contracts. The later good be described as the goodwill of the bank i.e. the premium over net book value that shareholders are willing to pay to acquire the shares of the firm.

By itself value based management is important for all companies, but it takes even more importance for financial institutions because the profits of all the financial contracts sold to the customers are dependent on future volatility, as we discussed in the first blog of this series. In this case management will need to discover and manage the value driver.

To achieve a value based management capability all activities must align to that concept.

  • Financial accounting does so partially through the accounting fair value model (it is only a partial alignment as the banking book is still value on an accrual basis).
  • Risk management is the most sensitive to this approach and good risk management principles all focus on future cash flows and their sensitivity to market volatility. This includes the management of economic capital through capital budgeting and allocation as per the Basel recommendations.
  • Sales and Marketing has developed a set of statistical and probabilistic tools to predict future client behaviours, but that capability is often in an independent silo and not integrated into other management domains.
  • Management accounting has evolved rapidly, but is still mainly focused on current profitability. Product and client profitability is in nearly all cases still a simple calculation that does not integrate future risk sensitivities.

It is evident that moving towards integrated value based management requires substantial reengineering of current processes and management information, with substantial organisational and IT consequences. The appropriate solution will depend on the banks strategic vision and strategies; hence the organisational and technical solution is not a standard “one size fits all” solution. In regards to the pricing aspects of this note that:

  • Different pricing strategies and models will apply to different business models, hence the problem and the solution are different by bank, but the approach is strategic and must be designed and managed top down.
  • There are no “off-the-shelf” technical solution/ application for a quick fix, because pricing is integrated in many other process and business support systems. Best of breed pricing will rely on the existence of robust risk analytics, risk transfer pricing capabilities, appropriate cost allocation systems, capital management capabilities…
  • Many of the management skills and capabilities required to implement a value based pricing strategy were developed post crisis and within the new regulatory environment (think liquidity risk…).
  • The project will imply revisiting Policies and Procedures, Process Flows, Competencies and skills, Organisational structures.
  • The technical solution to improve these business capabilities is data centric and rule based. It also requires systems integration between all the management domains of the bank.
  • Managing enterprise culture and change is essential as the new banking model that emerges from these approaches will require adaptations of skills and competencies and changes operational and management process.

Pricing is only one element of a global sales strategy.

We can summarise the main areas of competition in banking as being function of pricing, convenience and confidence:

  • The Price Function: The cornerstone of competitive positioning, but is all a question of price? And what is price? Does collateral requirements constitute a pricing variable and how?
  • The Convenience Function: Convenience has multiple facets. It can include: distribution channels and reach, the number & quality of products offered, the quality of documentation etc… Some of these issues are becoming increasingly more important, think of mobile banking versus internet and branch banking.
  • The Confidence Function: More than ever this is important, trust in the banking industry is at its lowest ever. Reputational risk is high. Bank solvency management is a priority. The European banking crisis is a constant reminder that this must be managed in anticipation of the risk not when it is basically too late.

One or the other way all these factors will influence product pricing, through cost allocations, solvency premium etc. This of course takes us to a fundamental question: if the theoretically correct price as calculated by the banks’ pricing model exceeds the competitors price, should the bank adapt its price to that of the market, or should they decline to do the sale? It sounds like a trivial question with an obvious answer, while in fact there is not a single answer and to make the correct decision we need to understand all the variables included in the contract price. This can only be done with the appropriate drill down and drill through capability of the price components, which is a technical problem requiring high data granularity and good analytical capabilities.

Strategic importance of Pricing

Many banks will say that they are not market leaders so can’t influence prices and they must follow market prices because they are supposed to be efficient. This position is of course un-defendable as pricing differences are often due to

  • internal inefficiencies which the bank must recognise and correct,
  • differences of marketing strategies,
  • differences in the behaviour characteristics of each bank’s client/ prospect base.

Another way of looking at this problem is to analyse the consequences of pricing. Pricing will influence many crucial and strategic management domains:

  • Client acquisition and retention;
  • Product innovation and management;
  • Product risk adjusted profitability and value contribution;
  • Client profitability and value contribution;
  • Risk Adjusted Return on Capital (RAROC) and Economic Value Added (EVA);
  • Operational efficiency (cost to income management);

The question I ask banks is simple: How do you measure the impact of your pricing decisions on all these variables? This capability is essential if you want to manage efficiently each of the domains.

Principles of Good Pricing for Financial Contracts

With all this in mind I have developed a list of 13 pricing principles that I believe are important in a pricing strategy and thus should be integrated in the pricing model of the bank.

  • Principle 1: Price the volatility (risks) of projected future Cash Flows;
  • Principle 2: Individualise all risks then price and manage them to optimise their variance and integrate whenever possible their covariance;
  • Principle 3: Integrate price elasticity to client solvency (their risk rating), not only to client segments characteristics;
  • Principle 4: Define, quantify and manage business risk;
  • Principle 5: Define cost allocation strategy and models;
  • Principle 6: Define, quantify and manage current and future client profit and value contribution (Life Time Value or Customer Fair Value);
  • Principle 7: Adapt the pricing strategy to the banks market strategy and the value proposition the client is seeking from your bank;
  • Principle 8: Manage competitive pricing;
  • Principle 9: Manage the complexity of management models;
  • Principle 10: Adapt the organisation to the requirement of risk and relationship based pricing;
  • Principle 11: Integrate pricing process with an efficient process flow from the origination of the client request to its fulfilment;
  • Principle 12: Integrate risk underwriting and pricing in a seamless strategy;
  • Principle 13: Optimise risk appetite, risk budgeting and allocation within the pricing model and define related clear and precise performance criterias.

Conclusion

Pricing strategy and pricing models are important developments; they are strategic and touch most management domains of the bank. The solution must be adapted to the vision, strategy and organisation of each bank but is based on a robust, flexible, data and rule centric technical architecture.

The implementation of such a capability will allow management to substantially enhance its control of the bank’s value based performance.

In the following weeks we will review the core principles of efficient pricing models.

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Risk & Relationship based Pricing Part 1

Bank Pricing Strategy

A forward looking complex management challenge for most big or small banks on all continents.

Jonathan Witter, Capital One’s (COF) president of retail and direct banking, predicts that over time, “we will see the advent of different pricing models, and we will see the advent of different feature models” (extracts from an article in AmericanBanker of March 18, 2013). McKinsey reported that less than 5% of the Fortune 500 companies have a dedicated pricing function.

If you agree with these statements, and I cannot find any reason to disagree, you have to ask yourself:

  • What do the other 95% of the Fortune 500 do?
  • What is the state of business for smaller companies?
  • Are banks better off or not?
  • Is this important and why?

My experience on all continents is that banks are probably worst of because of the nature of the banking products and services. Think of the differences in pricing a commercial good, a widget, sold to the sale of a financial contract.

Industrial/ commercial goods

The widgets are priced on the basis of known historical Cost of Goods Sold (COGS) and Sales Costs and margins adapted to the sales strategy and lifecycle of the product. The sales margins and profitability are easy to calculate and manage. Sales & price strategies focuses on marketing efficiency

Financial contracts

Financial contracts are sold on the basis of future operational costs and risks. Even if these future costs and risks can be estimated, they are uncertain because they are projected. Bankers must manage these uncertainties. The sale is completed only when the product cash flow cycle is completed, that can be in 1 month, 12 months… or 30 years! Throughout the cycle margins will vary. How do you integrate that uncertainty in the bank’s sales strategy and pricing strategy and models, and how do you manage that uncertainty?

To start answering the implied management questions, you should define and quantify these uncertainties and measure their volatility.

Operational cost uncertainties. In financial contracts the margins are contractually fixed (even if some products refer to reference rates or indices to fix the all-in rate as for variable or floating rate products). But the costs related to that product will vary through inflation, operational efficiency etc.

Financial and business risks, uncertainties. We can commonly agree that all financial products contain (1) Credit Risk or solvency Risk, (2) Interest Rate Risk, (3) Liquidity Risk, (4) Foreign Exchange Risks, (5) Business Risks, (6) Operational Risks, (7) Regulatory (Compliance) Risk, plus possibly some more!

All these operational and risk need to be defined, quantified and managed. The cost of managing the uncertainties, hedging the risks must in theory be expensed to the client, and the residual margin will constitute the “sustainable risk and relationship adjusted profit” of that transaction. Note that a measure of the sustainability would be the Life Time Value of the product

The introduction of value management by opposition to profit management is essential, because it is a forward looking measure of profit contribution defined around the all the future volatilities of the product related cash flows. Understanding these value drivers/ destructors and integrating them in the bank’s pricing model is the only way to take control of the commercial and sales strategy of the bank.

Conclusions

Pricing products is not trivial and it is complex.

All banks measure product and client profitability. But what model is used? With what data: average financial data or granular, historical financial data or projected data? Are customer projected behaviour integrated?

All banks price products, by definition. But how efficient, precise, flexible, useful are they?  Are they related to profit or value targets?

These are just a few of the issues possible.

I have prepared a brief slide presentation (available on SlideShare.com) in which I mention 13 good management principles to integrate in a pricing strategy and model. I want to expand a little on the solutions available and the strategic importance of this subject before I review the 13 principles over the following weeks/ months.

With some luck you will give me your comments, criticisms, suggestions as we go. I can then integrate all the ideas into a set of final recommendations.

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