Resource Type: Case Study

Our client has utilised the services of several data providers for its basic search and credit rating requirements. But three years ago, the company set out to overlay this information suite with financial health assessment tools that could deliver more sophisticated analysis and forward-looking insight for use by its UK risk team.     

Our platform has come into its own in examining larger clients and large debtor exposures. The H-Score® functionality gives the client the investigative capability it needs. And connected entities such as parent companies, subsidiaries, and other directorships are also easier to examine. The direct portal into Companies House data has been very helpful in negating having to dart between systems while keeping the thread of a specific enquiry running.

Our client uses our platform to monitor the financial health of its international network of dealers and distributors.

We created a tailor-made solution for our client, augmenting existing client data with the latest financials and developing customised scorecards designed to suit their business model and to reflect specific aspects of their portfolio segmentation.

Following a file matching process to a monthly automated data feed, we return the reports in a predefined template to ensure effective decision-making.

In addition, our client utilises Company Watch’s alerts tool to ensure they are reviewing dealers as close to account filing as possible.

We worked closely with the client to understand their key concerns and coupled this with our expertise on the pressure points which can cause certain types of companies to deteriorate rapidly, we carried out an identification of the suppliers within our databases (including group structures) and credit scored the suppliers using current financial data.

Based on a range (25) of economic scenarios that were discussed with the client, we then modelled a range of financial outcomes for these suppliers, using our abridged (abbreviated) company model
to impute P&L figures where needed.

The modelling outcome was >1M sets of modelled financials and associated credit scores. These were discussed and presented to the client in risk ‘buckets’. By flexing the economic assumptions we were also able to give an indication of which of them was most likely to have the biggest effect on the outcome: stress-testing the results demonstrated which assumptions were most critical to the portfolio.

“For a long time, I’ve used a service called Company Watch to help me keep on top of companies with weak balance sheets. Sometimes it’s obvious that a company is poorly financed but sometimes it’s not. Company Watch calculates an H-Score®, a twenty-first century version of the Z-Score, for each non-financial company it follows.

“To make it possible to predict problems in any company, it compares a large sample of the financial statements of businesses that got into financial difficulties in the past (the ‘failed group’) with those that did not. This enabled Company Watch to build mathematical models that can be applied to any company to determine the extent to which it reveals the characteristics of the failed group. Companies are scored on a financial health rating of 0 to 100 with 100 the strongest. Companies in the lower quartile have sufficient characteristics of failed companies to render them vulnerable. It is very unusual for companies with scores higher than 25 to experience financial distress.

“The models consist of seven key interactive measures, ratios that are treated mathematically and weighted before being combined to produce the single measure, the H-Score®. In support of the H-Score®, each of the seven measures is scored as well, to reveal and evaluate any company’s financial strengths and weaknesses over the past five years. Scores are recalculated every time a company produces financial results.

“The H-Score is one of the inputs I review every time I look at a company. Also, any company in my portfolio that is in the weakest quartile gets my special attention. A bit like technical analysis it’s not that I say I’ll never own a company with a poor chart or poor H-Score® but, if I do, I will want to do so with my eyes fully open and pay special attention to the company’s progress. If something starts to go wrong, these are the holdings that should be sold early, even if this means selling the holding at a loss. Highly geared companies are particularly exposed if business conditions change for the worse. Generally, I will take a smaller holding in these types of company than I would if the balance sheet was stronger. The ones in the lowest decile or so are the most risky of all. Also, I watch very carefully companies that historically had good scores, but which subsequently enter the lowest quartile. I also look out for otherwise strong companies with a steadily declining H-Score® and ones with a very volatile H-Score® history.

“Company Watch sends me a list each fortnight of companies at risk (in the lowest quartile), companies that have entered the at-risk zone and companies no longer at risk. This is one of my essential pieces of regular reading. As a further check, in more highly geared business, it’s worth looking at where the debt trades (if it does trade). I’ve sometimes seen businesses where equity investors are quite cheery about the company when debt investors are paying a big discount on the debt. I would rather take my steer from the debt investors (if the debt is not worth near par, the equity may be worth very little). It’s also worth looking at credit default spreads where these exist for similar reasons.

“Of course, most companies use debt and debt is not normally bad news. Companies that use debt sensibly can increase returns substantially for equity investors. Others have inefficient balance sheets today, and here shareholders should be asking for more debt. If I had my time again in running my funds and had avoided every share with a bottom quartile sector H-Score® I might have missed a few winners, but I believe I would have avoided most of my disasters.”

Extracts from: Anthony Bolton, Investing Against the Tide

Edinburgh: Pearson Education Limited, 2009 © Anthony Bolton, 2009

Our client is a market leader, supplying goods to a wide range of industries both in the UK and Ireland.

“Since working with Company Watch we have found both the sources of information and information quality to be an excellent fit to achieve our objectives.” The system has subsequently also been rolled out to the sales team, where it plays an important role as a prospect targeting tool, as well as allowing the team to qualify sales opportunities within a credit management context.

“Company Watch delivers the quality and insight we need to make highly informed business decisions and we have shared that capability widely across the business. The quality that Company Watch delivers is unwavering and so is our commitment to Company Watch.”

Our real estate fund manager client started working with us in 2011 following a thorough review of providers. The information requirement was both broad and deep including reviewing the covenants of a single property through to an entire shopping centre, as well as rating tenants and examining the financial performance of contractors.

We were appointed, not only because of the richness of the data available, but also because of how easy it is to access and analyse the information on the platform. It remains a vital component within the financial risk and analysis process at the company.

For insurance companies, our H-Score® tools provides an immediate snapshot of a company’s financial health and performance. This enables our client’s underwriting team to review companies and portfolios and have the capability of tracking performance against specific industry averages and market fluctuations.

We are instrumental in the way our client monitors counterparty risk for both existing insureds and prospect cases. Our financial analytics are integral to unique product offerings such as non-cancellable limit coverage.

Our client’s underwriting team delved deeply into the accounts of a contractor looking for Surety product solution to its bonding requirement. The team needed information that’s current and looks forensically into every aspect of the company’s P&L and balance sheet. The data also had to feed the need to be predictive, as Surety underwriters could be on risk for as long as five years.

Our platform’s data played a key role in the underwriting management information system that enabled full risk examination, for example aged debtors, cash position, short-term debt and long-term debt.

It also provided the experiment functionality to create highly sophisticated ‘what if’ interrogations.