"10 years after the collapse of Lehman Brothers, we are entering the maturity tail of the cycle characterised by increased competition in virtually all European markets and pressure on yields from purchased debt portfolios."
Managing the cycle has always been one of the most important tasks for managers of financial institutions. In favourable markets they use more of their balance sheets and take principal positions to take maximum advantage of underlying opportunities. In times of diminishing returns, they adopt by sweating the franchise and extracting more fee income.
Debt management companies need to adopt too. The financial crisis in 2008 wreaked havoc in the markets and offered a buoyant environment for non-performing debt purchasers. Especially in Europe, where the banking sector resembled a scene from the Walking Dead after 2008, the relatively small business of non-performing debt purchasing and management prospered to levels where the face value of non-performing debt changing hands surpassed €100bn per annum. 10 years after the collapse of Lehman Brothers, we are entering the maturity tail of the cycle characterised by increased competition in virtually all European markets and pressure on yields from purchased debt portfolios.
This stage of the cycle requires debt management companies in Europe to not only manage their balance sheets more efficiently but to also consider balancing out their revenue streams. The competitive environment brings risks in winning auctions on attractive yields and makes it more difficult to replenish purchased debt portfolios with steady margins. This, combined with substantial balance sheet leverage, translates into potential volatility in debt-purchase income and compression in valuation multiples.
In October 2017, the debt management sector was trading at approximately 11.4 times the following year’s estimated earnings. At present, the sector, represented by the same players, is trading at 8.2 times next year’s estimated earnings. While the argument above cannot be singled out as a reason for the change in valuations, investors seem to be more rigorous in challenging business models and pricing underlying risk and growth.
Diversification and collection efficiency are two topics that attract the sector’s attention.
Diversification Opportunities
"The outsourcing model can be just as effective as the underwriting model, especially in established markets where credit data is broadly available. Emphasis shifts from prices paid in portfolio purchases to efficiency in collection services."
Traditionally, third party collection services have been a big part of businesses such as Intrum Justitia and GFKL, which combined with Lindorff and Lowell, respectively. Both combinations pursued balanced revenue streams. In the last 12 months, Intrum and Lowell Group drew 57% and 27% of their revenues from third party collections, respectively.
DoBank was created by Fortress and opened up to public investors as a pure servicing entity, managing one of the largest investment portfolios in Europe. The company is not only expanding its position as a service provider in Italy but it is also pursuing cross-border consolidation as a pure-play servicer.
Arrow Global has been tactically consolidating different servicing capabilities in its geographical footprint and is turning the spotlight the growing contribution of this vertical. The company recently expanded disclosures to break down asset management profitability, underlining the importance of this segment to its investors. More European players should do the same.
Third party collection services provide an alternative corridor for growth with much less strain on capital structures. The outsourcing model can be just as effective as the underwriting model, especially in established markets where credit data is broadly available. Emphasis shifts from prices paid in portfolio purchases to efficiency in collection services.
Where debt purchase faces the challenge of continuous re-investment in competitive markets, collection services is a business with a natural long tail, given collection periods of 10-15 years with an average duration of 4-6 years. Assets rarely move from one service provider to another. It takes longer to create a franchise and attract assets to manage but resulting profits are sticky and stable.
The steady income from managing assets with longevity also attracts higher valuation multiples compared to those attached to debt purchase profits. DoBank is trading at 13.6 times 2018E earnings and 11.5 times 2019E earnings, which are near the PE multiples of European asset managers (13.7 times 2018E earnings and 13.2 times 2019E earnings.) In contrast, debt managers (including those with third party service revenues) trade at average multiples of 11.5 times 2018E earnings and 8.2 times 2019E earnings.
Establishing meaningful scale in third party collection services not only is a way to diversify revenues but may also attract higher valuation multiples for the players.
Where debt purchase transactions are lumpy and cross-border growth opportunities are limited, debt management companies may also look to diversifying revenues by purchasing performing loans or consolidating consumer finance businesses.
Credit models and other relevant consumer data is the core intellectual property driving debt management businesses. Moving into consumer lending would not only be a way of leveraging their intellectual property but also a way to better utilise their funding through more efficient capital allocation. Diversification that can bring funding synergies is something investors cannot replicate on desktop. Furthermore, such consolidations may bring additional scale, much needed by publicly listed companies trading at mid-market valuations. Boost in scale may lead to better analyst coverage and additional institutional investor interest.
Is AI the Next Game Changer?
"Automating the collection process is more effective and provides a friendly environment for debtors to assess their options, while it removes the pressure of emotional conversations between debtors and agents."
In less competitive markets, yields underlying debt purchases are large enough to accommodate collection costs, growth costs and still leave a healthy margin. As competition starts dictating yields, wiggle room in costs starts to evaporate. Pursuing new growth markets means facing higher collection costs until operations mature. Furthermore, investors are looking at ROE high-watermarks of mid to high teens and pushing leverage is not really an option. Nor is compromising on equity returns.
Spotlight on collection costs. Cost to collect in consumer credit changes between 15-30% of gross collections depending on portfolio dynamics as well as the underlying jurisdiction. Part of the cost structure includes legal costs while a big chunk is borrower interaction and settlements. Particularly the second part is in evolution and offers room for improvement, especially with the utilisation of alternative channels.
Automation of interactions is not a new concept and banks have been investing in automated channels to minimise the involvement of agents. In the same way, debt management companies have also been building digital interaction channels.
The federal regulator in the US issued in 2014 a strong guidance regarding banks’ selling of non-performing consumer credit in response to aggresive collection practices exercised by purchasers. This led to the rise of the outsourcing model and set in motion the development of automation in search for efficiency. New companies like Trueaccord, a San Francisco based fintech start-up, developed collection systems using AI powered virtual assistants. According to its CEO, TrueAccord collects 40% to 50% more than traditional collection agencies.
The shift towards outsourcing is also inevitable in Europe and emphasis is on channel-relevance and automation. Otto Group’s Collect.ai uses an AI based technology to for receivables management and offers omni-channel communication and payment methods. Experian’s eResolve offers an online platform where consumers can negotiate and pay their past-due accounts.
Automating the collection process is more effective and provides a friendly environment for debtors to assess their options, while it removes the pressure of emotional conversations between debtors and agents. What you end up with is an advance version of the Mechanical Turk, with the human element is used precisely and efficiently.
If decision-making can also be folded into automation, the process moves over to the world of artificial intelligence. While the term is often misused, it finds it ultimate home in consumer credit data. Unifying data and integrating credit models with behavioural analytics is the ultimate challenge.
Data integration and the establishment of a feedback loop leads to a self-learning system, which can predict behaviour and perceptiveness based on credit profile and optimise interaction towards the best possible outcome.
While debt purchase businesses face the challenges mentioned above, investment in automation may bring much needed efficiency into the system.
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