Pension Management Outline

Experiential Learning from BG Consulting

Experiential Learning from BG Consulting

Simulations are what you make of them.  Oxyor simulations are designed to portray real life situations and aspects of a specific segment of the financial industry.  They take place in a safe environment with integrated theory and knowledge transfer.  BG trainers are first and foremost talented, experienced trainers but it is key that they all also have considerable experience in the front line of banking and finance.

Oxyor Simulations + BG Trainers = The Best In Experiential Learning

Excel Visual Basic for Applications

Excel Visual Basic for Applications (VBA) can reduce data processing time by tens of hours each week and turn conventional spreadsheet analysis into interactive and insightful executive information.   Excel VBA training programmes from BG Consulting  enable delegates to automate conventional data collection procedures and run summary reports with the application of Excel VBA coding procedures.  Delegates learn how to develop interactive scenario analysis and provide an intuitive interaction portal that can be used for strategic business planning and what-if analysis.  Our Excel VBA courses will enable you to turn Excel into a sophisticated executive information system capable of providing interactivity and insight that surpasses that of much more costly financial planning software.  If the provision of your regular financial reporting in your organisation consumes a large proportion of your finance staff resource and you remain unimpressed by the huge pack of data tables each month, your finance team need to attend Excel VBA training arranged by BG Consulting.    

Peer to Peer Lending - How Should Banks Respond?

How Should Banks Respond?

P2P is probably most readily associated with the consumer-focused Zopa, which claims to have created the market almost ten years ago. However, the Chart shows that small businesses are also benefitting from this new technology:

P2P Lending: 2013

There is potential for P2P to change the way that businesses are financed. A key question for banks and other organisations serving small business is:

Is this an Opportunity or a Threat for Banks

The answer to this is, in part, dependent upon whether P2P is here to stay.

P2P has started to do something that banks either cannot or will not – filling the “financing gap”. Bankers have typically complained of the high “costs to serve” and lack of transparent financials associated with small businesses. Have P2P platforms cracked something that the banks have struggled to do for decades or even centuries?

Algorithms Linked to Social Networks

Are the P2P algorithms, with their linkages to social networks, really so much more robust than those developed by leading banks? Does this mean that they are better able to understand risk than the banks?

Traditionally, lending to small business has been relationship driven, which tends to be high cost in terms of both attracting suitable borrowers and in the credit analysis process. It is not difficult to imagine that there can be efficiencies in web-based customer acquisition, but this is available to online lenders without their being P2P. The P2P platforms could really have a sustainable advantage if their credit analysis is capable over the complete cycle of predicting probabilities of default (“PDs”), loss given default (“LGDs”) and the resultant Expected Losses (“ELs”). So, if P2P platforms remain better able to mine useful credit intelligence from social networks, the banks could face increasing competition.

Pricing Decisions

Lenders are probably not being altogether altruistic when they invest surplus funds across a P2P platform. The vast majority will, of course, be seeking to achieve a higher return than they could expect from a bank deposit. It is likely that all, or most, such lenders will appreciate that there is a significantly different risk profile in cutting out the middleman – i.e. a bank with deposit protection. Does the P2P lender: (i) have access to the risk adjusted return models which are standard in the banking industry, and (ii) have the ability to make informed investment decisions based upon these?

Funding Cost Advantage

It is true for the vast majority of P2P lenders that they do not suffer the formal requirement to allocate shareholder capital against their lending as is imposed upon the banks through the Basel regulations. While P2P lenders might consider their opportunity cost of capital to be low, this might be a little misleading relative to the funding advantages (leverage and often zero interest deposits) enjoyed by the banks. Banks have learned over many decades how to price for increasing tenor and this is something that might be new to P2P lenders.

Portfolio Diversification

One of the attractions of P2P lending appears to be that the transaction costs for lender are very low, meaning that it is quite easy to construct a portfolio of loan participations. The ability to diversify across several (or many) borrowers might be a comfort to lenders, but do they have the tools to assess whether they are achieving diversification benefits? How significant is the potential that their portfolios contain unrecognised concentration risks? In banking, there is a saying:

“Concentration kills”…

Investor Protection

Several P2P platforms state that they are able to offer varying levels of investor protection, and if effective this could be a good mitigant for the above objections. For example: Landbay says it offers “protection funds”; Lending Works says it has “insurance”, and Madiston LendLoan Invest advertises its “compensation scheme”. The devil is always in the detail, and it is important to have a concept as to how these mitigants operate and who stands behind them

Attractions to Borrowers from P2P

Just why are small businesses starting to use these platforms? Is it because the P2P process is quicker and less bureaucratic? Are they able to source cheaper, longer term funding from P2P compared to banks? Are P2P lenders financing borrowers who would be turned away by the banks? Or are the P2P platforms cherry-picking the banks’ best small business prospects? Can banks enjoy a better relationship with customers who source their financing from P2P lenders, enabling the banks to cross-sell non-credit products? The answers to these questions are likely to be central to the type of competitive response from the banks.

Some Key Challenges for P2P Business Models

Incentive Problems

This is essentially a broker model, wherein the provider of the P2P platform takes little or no financing risk. A root cause of asset bubble driven banking crises has often been a skewed reward structure wherein relationship managers have been incentivised to generate asset growth with little or no regard for the risks that they have piled onto their employers’ balance sheets.

If the P2P platforms have no risk of capital loss, could this mean that credit quality within the system might deteriorate and simply be passed around many P2P lenders rather than (as is currently the case) remaining in the hands of the originating bank?

Monitoring and the Identification of Early Warning Signals

Through the inclusion in their credit algorithms of behavioural factors (often drawn from social media), it is conceivable that the P2P platforms will do a better job of identifying developing problems than incumbent lenders (who have struggled with this since the beginning of time!).

However, it will be important to see how much attention the platforms will pay to advising their lenders of changes in the borrowers’ credit quality.

Without question, the earlier that problems are identified, the better the lender’s prospects of making a full recovery.

Problem Loans 

Who will take responsibility for negotiating restructurings when problems develop? This is a highly specialised, time-intensive and costly process. Loan workout and restructuring skills and cultures vary widely between existing lenders. How will P2P platforms perform?

Education of Lenders

Banks have invested huge sums in training their staff in credit analysis and associated topics. Will all (or even a reasonable percentage) of P2P lenders have the same or better understanding of these principles and techniques? And if the P2P platforms are to educate/ train potential lenders, is there not a significant conflict of interest?

There are, of course, myriad other issues for P2P platforms to manage, not least of which are potential fraud, anti-money laundering and KYC. However, within this article I have sought to identify some of the strategic questions and challenges with a view to providing bankers with a starting point for framing their strategic responses.

For assistance with developing your strategic response, training relevant staff or to provide feedback/comments on this article, please email me at:

adrian.grant@bgconsulting.com

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Financial Modelling: Model Design

Best Practice

Ultimately, the best practice is to invest time, thinking about a model before it is built, focusing on what it is needed for and what is the best way of structuring the model in order to achieve its objectives. The more time spent thinking about a model at the outset will save time later in the production process; remember that computers do not think, so we have to do the thinking for them. Once the objectives of the model have been thought about and the structure of the model set, the next most important rule to bear in mind when building a model is to keep it as simple as possible! Ask the following questions constantly when building any financial model:

Although a model will always reflect the way that the designer thinks, there are a few steps that can be taken to ensure that somebody else could use, and improve the understanding of, any model. Utilising these steps will also help to minimise errors:

Financial Forecasting & Modelling

Introduction

In order to value a company or understand its credit position, it is necessary to have a view about its future profitability, financial position and growth.

The assessment of future profitability, financial position and growth is based on assumptions about how fast a company will increase its sales, how much it will need to invest in order to be able to produce its goods, and how efficiently the company will be at turning sales into profits. 

Making assumptions is not an exact science: assumptions are reasonable or unreasonable, aggressive or conservative. On the other hand, producing an integrated set of financial statements based on agreed assumptions should only give one potential outcome: the answer is either right or wrong.

In building any financial forecast model, it is easy to become too engrossed in the details and lose focus on the aggregate result. It is often the case that once a model is built, it is better to improve a valuation by matching a decline in future ROCE (Return On Capital Employed) against a reduction in competitive advantage, rather than precisely modelling accounts receivable in 20 years’ time. There is value in thinking about how to go about forecasting and what level of detail is required in the model.

This manual covers how to build a fully integrated Excel model to forecast the financial performance of a company, based on reasonable assumptions and on the correct mechanics. It discusses how to achieve realistic forecasts and provides guidance in terms of model design, structure and formatting best practices.

Types of Valuation

Standalone Valuation

As discussed above, there are two main types of valuation used to value a company, either an absolute valuation tool which attempts to arrive at a nominal valuation, or a relative valuation tool, which uses the value of other companies in the market to determine the value of the company being valued. The two types of tool and approaches have been neatly summarised by the following quotes by two successful investors:

An absolute valuation approach produces a nominal valuation, i.e. the value in pounds, dollars or euros that the company’s shares should trade at if fairly valued. This type of valuation is often called an “intrinsic value”, because it is highly unlikely that the company’s shares do trade at this value. An absolute valuation approach assumes that the market is inefficient at valuing companies. 

A relative valuation approach produces a valuation based on how other similar companies are valued by the market and assumes that the market, in aggregate, is correctly valued but that inefficiencies in valuation exist across the market or individual sectors. Both absolute and relative valuation tools are generally used to value a company on what is called a standalone basis, i.e. the company being valued is being valued in isolation.

Market Practice and Combination Valuation

In practice, a combination of absolute and relative valuation tools would be used to value a business. Often an absolute valuation tool such as DCF would be used as the first pass at valuation and then a cross-check would be performed using relative valuation tools such as multiples to gauge how the market was valuing similar companies. Other absolute valuation methodologies would be Economic Value Added (EVA) or Adjusted Present Value (APV).
In addition to valuing companies on a standalone basis, in practice valuation tools are often used that assume an element of corporate activity will take place. This can take the form of a comparable transaction (comptrans) valuation, where recent corporate transactions are used as a benchmark to determine the value of the company being valued. The assumption made is that because other companies have been acquired at certain valuation levels that these transaction values are relevant to the value of the company being valued. Corporate activity can also be incorporated by way of a combination valuation, where the target company’s value in a transaction will incorporate elements of value that would only arise as the result of a transaction, such as the synergy benefits from combining two companies.
Other specialised valuation tools include Leveraged BuyOut analysis (LBO) where a valuation based on the restructuring of a company’s capital structure in the form of a private equity, venture capital or Management BuyOut (MBO) transaction is carried out.

Key learning points:

1. Standalone valuation approaches include absolute valuation and relative valuation. An absolute valuation approach assumes that the market is inefficient and a relative valuation approach assumes that, although the market in aggregate is efficient, inefficiencies exist across the market.
2. Other forms of valuation include comparable transaction valuation, combination valuation and leveraged buyout valuation.