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Assessing Counterparty Risk post-GFC – some lessons for #FinTech

Posted on September 29, 2015 by Content in Context

At the height of the GFC, banks, governments, regulators, investors and corporations were all struggling to assess the amount of credit risk that Lehman Brothers represented to global capital markets and financial systems. One of the key lessons learnt from the Lehman collapse was the need to take a very different approach to identifying, understanding and managing counterparty risk – a lesson which fintech startups would be well-advised to heed, but one which should also present new opportunities.

In Lehman’s case, the credit risk was not confined to the investment bank’s ability to meet its immediate and direct financial obligations. It extended to transactions, deals and businesses where Lehman and its myriad of subsidiaries in multiple jurisdictions provided a range of financial services – from liquidity support to asset management; from brokerage to clearing and settlement; from commodities trading to securities lending. The contagion risk represented by Lehman was therefore not just the value of debt and other obligations it issued in its own name, but also the exposures represented by the extensive network of transactions where Lehman was a counterparty – such as acting as guarantor, underwriter, credit insurer, collateral provider or reference entity.

Before the GFC

Counterparty risk was seen purely as a form of bilateral risk. It related to single transactions or exposures. It was mainly limited to hedging and derivative positions. It was confined to banks, brokers and OTC market participants. In particular, the use of credit default swaps (CDS) to insure against the risk of an obiligor (borrower or bond issuer) failing to meet its obligations in full and on time.

The problem is that there is no limit to the amount of credit “protection” policies that can be written against a single default, much like the value of stock futures and options contracts being written in the derivatives markets can outstrip the value of the underlying equities. This results in what is euphemistically called market “overhang”, where the total face value of derivative instruments trading in the market far exceeds the value of the underlying securities.

As a consequence of the GFC, global markets and regulators undertook a delicate process of “compression”, to unwind the outstanding CDS positions back to their core underlying obligations, thereby averting a further credit squeeze as liquidity is released back into the market.

Post-GFC

Counterparty risk is now multi-dimensional. Exposures are complex and inter-related. It can apply to any credit-related obligation (loans, stored value cards, trade finance, supply chains etc.). It is not just a problem for banks, brokers and intermediaries. Corporate treasurers and CFOs are having to develop counterparty risk policies and procedures (e.g., managing individual bank lines of credit or reconciling supplier/customer trading terms).

It has also drawn attention to other factors for determining counterparty credit risk, beyond the nature and amount of the financial exposure, including:

Bank counterparty risk – borrowers and depositors both need to be reassured that their banks can continue to operate if there is any sort of credit event or market disruption. (During the GFC, some customers distributed their deposits among several banks – to diversify their bank risk, and to bring individual deposits within the scope of government-backed deposit guarantees)
Shareholder risk – companies like to diversify their share registry, by having a broad investor base; but, if stock markets are volatile, some shareholders are more likely to sell off their shares (e.g., overseas investors and retail investors) which impacts the market cap value when share prices fall
Concentration risk – in the past, concentration risk was mostly viewed from a portfolio perspective, and with reference to single name or sector exposures. Now, concentration risk has to be managed across a combination of attributes (geographic, industry, supply chain etc.)

Implications for Counterparty Risk Management

Since the GFC, market participants need to have better access to more appropriate data, and the ability to interrogate and interpret the data, for “hidden” or indirect exposures. For example, if your company is exporting to, say Greece, and you are relying on your customers’ local banks to provide credit guarantees, how confidant are you that the overseas bank will be able to step in if your client defaults on the payment?

Counterparty data is not always configured to easily uncover potential or actual risks, because the data is held in silos (by transactions, products, clients etc.) and not organized holistically (e.g., a single view of a customer by accounts, products and transactions, and their related parties such as subsidiaries, parent companies or even their banks).

Business transformation projects designed to improve processes and reduce risk tend to be led by IT or Change Management teams, where data is often an afterthought. Even where there is a focus on data management, the data governance is not rigorous and lacks structure, standards, stewardship and QA.

Typical vendor solutions for managing counterparty risk tend to be disproportionately expensive or take an “all or nothing” approach (i.e., enterprise solutions that favour a one-size-fits-all solution). Opportunities to secure incremental improvements are overlooked in favour of “big bang” outcomes.

Finally, solutions may already exist in-house, but it requires better deployment of available data and systems to realize the benefits (e.g., by getting the CRM to “talk to” the loan portfolio).

Opportunities for Fintech

The key lesson for fintech in managing counterparty risk is that more data, and more transparent data, should make it easier to identify potential problems. Since many fintech startups are taking advantage of better access to, and improved availability of, customer and transactional data to develop their risk-calculation algorithms, this should help them flag issues such as possible credit events before they arise.

Fintech startups are less hamstrung by legacy systems (e.g., some banks still run COBOL on their core systems), and can develop more flexible solutions that are better suited to the way customers interact with their banks. As an example, the proportion of customers who only transact via mobile banking is rapidly growing, which places different demands on banking infrastructure. More customers are expected to conduct all their other financial business (insurance, investing, financial planning, wealth management, superannuation) via mobile solutions that give them a consolidated view of their finances within a single point of access.

However, while all the additional “big data” coming from e-commerce, mobile banking, payment apps and digital wallets represents a valuable resource, if not used wisely, it’s just another data lake that is hard to fathom. The transactional and customer data still needs to be structured, tagged and identified so that it can be interpreted and analysed effectively.

The role of Legal Entity Identifiers in Counterparty Risk

In the case of Lehman Brothers, the challenge in working out which subsidiary was responsible for a specific debt in a particular jurisdiction was mainly due to the lack of formal identification of each legal entity that was party to a transaction. Simply knowing the counterparty was “Lehman” was not precise or accurate enough.

As a result of the GFC, financial markets and regulators agreed on the need for a standard system of unique identifiers for each and every market participant, regardless of their market roles. Hence the assignment of Legal Entity Identifiers (LEI) to all entities that engage in financial transactions, especially cross-border.

To date, nearly 400,000 LEIs have been issued globally by the national and regional Local Operating Units (LOU – for Australia, this is APIR). There is still a long way to go to assign LEIs to every legal entity that conducts any sort of financial transaction, because the use of LEIs has not yet been universally mandated, and is only a requirement for certain financial reporting purposes (for example, in Australia, in theory the identifier would be extended to all self-managed superannuation funds because they buy and sell securities, and they are subject to regulation and reporting requirements by the ATO).

The irony is that while LEIs are not yet universal, financial institutions are having to conduct more intensive and more frequent KYC, AML and CTF checks – something that would no doubt be a lot easier and a lot cheaper by reference to a standard counterparty identifier such as the LEI. Hopefully, an enterprising fintech startup is on the case.

Next week: Sharing the love – tips from #startup founders

The art of #pitching – the long and the short of it… Pt.2

Posted on September 22, 2015 by Content in Context

Last week, I commented on a short-form pitching event hosted by General Assembly. This week, I report on Startup Victoria‘s latest pitch night, “Pitch in Melbourne”, which may become a more regular fixture on the startup circuit. It seems we can’t get enough of these events….

In contrast to “Out of the Garage”, “Pitch in Melbourne” was a more in-depth, long-form pitch event, with only three teams competing (for a prize of $50,000 in seed funding), and all of them are currently going through accelerator programs. Their presentations were about 10 minutes each, with ample time for Q&A with the audience and panel, ably assisted by MC Leni Mayo.

The underlying idea was to reveal some of the thinking that prospective angel investors apply when considering new proposals. Even with the opportunity to listen in on the judges’ deliberations (who were effectively choosing where to invest some of their own money), it was still a slightly artificial exercise, because in reality, few investments are made after just a 15-minute presentation.

The pitches were reasonably proficient, although the market sizing, opportunity assessments and financials were a bit thin. One startup appears to be making potentially serious money, another has validated their model with a commercial client, while the third is still working out a go-to-market strategy:

SweetHawk has featured in this blog before, and is building integrated voice solutions for e-commerce and m-commerce. During beta-testing, SweetHawk has helped a venue booking agency to deliver more business to its clients. As a result, the team believe it will have most success with high-value, complex and non-commoditised products and services, where talking to prospects means much, much higher conversion rates from enquiries to firm sales. The service pricing model looks like it needs more work, and more market segments would need to come on board to demonstrate the commercial application. Experience also tells us that big-ticket B2B items are less likely to be bought on-line, and rarely after only a single touch point. Plus, companies usually have strict policies around employees paying for enterprise purchases with their individual corporate credit cards, require purchase orders to be raised in advance, and often outsource their buying to third-party procurement services.

parkhound perhaps likes to think of itself as part of the sharing economy (“an AirBnB for car parking”), except that it’s trying to create long-term contracts, not overnight deals. It also faces strong competition, not only from other providers within Australia and overseas, but potentially from AirBnB itself as it develops a similar add-on service following its recent deal with ParkMonkey. There’s also the prospect of that other darling of the shared economy, Uber bringing its app technology to car parking as well. So far, parkhound has signed up a solid inventory of spaces, and is starting to acquire some more substantial corporate accounts. However, spaces in commercial buildings and residential developments normally require dedicated hardware and other technology solutions such as smart boom gates to allow non-residents and non-tenants to gain access to secure areas. One suggestion from the panel was to sign up more residential spaces close to train stations – although such a strategy risks “off-platform leakage”, by cutting parkhound out of the picture if householders choose to go direct to market (e.g., via Gumtree or similar). Finally, there is evidence that car ownership is in decline among some sections of the population, and the prospect of driverless cars could mean we will only need between 10%-30% of the current number of vehicles on the road.

nuraloop are building customised headphones that are attuned to our own ears, incorporating some proprietary technology called earSync (“a virtual Cochlear”) that is designed to enhance the user experience when listening to music. I’ve seen the team pitch before (with some success), but despite the medical, scientific and engineering pedigree of the team, it seems they are only interested in the product application for music. Sure, getting TGA status is complex without medical evidence, but other options in the area of OH&S might not be so onerous to pursue. However, a bigger concern for the judges was the fact that the founders are not clear whether they are developing a hardware product, or seeking to licence their IP to other manufacturers. The good news is that most of the audience indicated they would subscribe to the crowdfunding campaign, and nuraloop won the audience choice.

Although it wasn’t entirely clear which pitch won the $50,000 (if indeed any of them did – specific term sheet negotiations weren’t going to be discussed publicly), I think it would have been a close call between SweetHawk and parkhound. One judge even suggested the two of them should be collaborating – but he was possibly biased. Despite the different startup domains, the judges were assessing the validity of the business models, the level of novelty/disruption, the teams’ strengths and capabilities, the commercial attractiveness of the idea, and above all the ability to execute and scale.

Both these events demonstrated that pitching is not easy, that there is a balance to be achieved between a slick sales presentation and a detailed analysis of the product/market fit. It’s certainly not just about the “idea”, and teams will be challenged if they can’t substantiate their claims or don’t come across as authentic or convincing. Ultimately, there’s no such thing as a perfect pitch (it’s all very subjective), but it helps when preparing to become pitch perfect!

Next week: Counterparty risk post-GFC

The art of #pitching – the long and the short of it… Pt.1

Posted on September 15, 2015 by Content in Context

Pitch nights are popping up all over the place. So far this year, I have participated in two startup competitions where pitching was a core component, and attended at least half-a-dozen other pitch events. Some sessions were designed to help early-stage ideas find co-founders, some to showcase the results of accelerator programs, while others were full-on “show me the money” extravaganzas, where term sheets were put in front of the winning teams. The latest events represented two approaches to the format, organised by Startup Victoria (long form) and General Assembly (short form).

This week, the short-form – next week, the long-form.

General Assembly’s “Out of the Garage” Pitch Fest Party was not quite rapid fire, but the 15 teams only had 2 minutes each to present, faced some strict rules around format, and had no Q&A with the judges or the audience. The five winners each received a modest $1,000, plus some other perks to help them on their journey.

It’s impossible to do justice to the wide range of ideas that were pitched (and many of them were just ideas at this stage…), so here are my verbatim notes from the night, in the order of the pitches:

Animatly – DIY solution for making animated videos – “Canva for animated videos”
FolkFeast – good food more cheaply – “AirBnB for dining out”
RightClick – Intergenerational tech transfer – “young people teach old people how to use PC’s, tablets and smart phones”
Auug – Hardware device plus app that turns an iPhone into a motion-based MIDI controller and synth (as already featured in Apple ads)*
YearOutClub – “GoCompare for the gap year” – courses, content & accommodation
CareConnect – matching carers with clients, customised and personalised – Tech-driven. Big market: $13.5bn spent each year on care services
Good Packages – bio-degradable packaging
PetalBox – Single flower vending machines
VibeDate – “the best date you’ve never had” – curated dating experiences
NatureAtWork – re-connecting with nature, wellbeing and productivity
Wonderhood – market place for novel experiences
Project_O – “disrupting bottled water market” – art meets public water fountains
Joyality – Eco-psychology program for humans
Dunnit – “learn from someone who’s done it” – mentoring platform for creatives
LeanFilmmaking – agile process for creating video – technology is easy, finding audiences is hard… Idea to Audience: Fast – Accelerator program for story/audience fit

With limited exposure, it was difficult to know which pitches had real substance, but a couple are already in business, and a few have at least created a web profile. Several ideas sounded very similar to other new projects I’ve seen or heard of recently, and I would also recommend that all of the aspiring founders research their startup names before trying to register their companies. The winners were: Wonderhood, PetalBox, RightClick, Project_O and VibeDate.

Next week: Pt.2 – The Long Form

* Declaration of interest: I purchased one of the first units via their crowdfunding campaign, so I’m already a customer…

#FinTech – using data to disintermediate banks?

Posted on September 8, 2015 by Content in Context

At a recent #FinTechMelb meetup event, Aris Allegos, co-founder and CEO of Moula, talked about how the on-line SME lender had raised $30m in investor funding from Liberty Financial within 9 months of launch, as evidence that their concept worked. In addition, Moula has access to warehouse financing facilities to underwrite unsecured loans of up to $100k, and has strategic partnerships with Xero (cloud accounting software) and Tyro (payments platform).

Moula is yet one more example of how #FinTech startups are using a combination of “big data” (and proprietary algorithms) to disrupt and disintermediate traditional bank lending, both personal and business. Initially, Moula is drawing on e-commerce and social media data (sales volumes, account transactions, customer feedback, etc.). Combined with the borrower’s cashflow and accounting data, plus its own “secret sauce” credit analysis, Moula is able to process on-line loan applications within minutes, rather than the usual days or weeks that banks can take to approve SME loans – and the latter often require some form of security, such as property or other assets.

So far, in the peer-to-peer (P2P) market there are about half-a-dozen providers, across personal and business loans, offering secured and unsecured products, to either retail or sophisticated investors, via direct matching or pooled lending solutions. Along with Moula, the likes of SocietyOne, RateSetter, DirectMoney, Spotcap, ThinCats and the forthcoming MoneyPlace are all vying for a share of the roughly $90bn personal loan and $400bn commercial loan market, the bulk of which is serviced by Australia’s traditional banks. (Although no doubt the latter are waking up to this threat, with Westpac, for example, investing in SocietyOne.)

We should be careful to distinguish between the P2P market and the raft of so-called “payday” lenders, who lend direct to consumers, often at much higher interest rates than either bank loans or standard credit cards, and who have recently leveraged web and mobile technology to bring new brands and products to market. Amid broad allegations of predatory lending practices, exorbitant interest rates and specific cases of unconscionable conduct, payday lenders are facing something of a backlash as some banks decide to withdraw their funding support from such providers.

However, opportunities to disintermediate banks from their traditional areas of business is not confined to personal and business loans: point-to-point payment services, stored-value apps, point of sale platforms and foreign currency tools are just some of the disruptive and data-driven startup solutions to emerge. That’s not to say that the banks themselves are not joining in, either through strategic partnerships, direct investments or in-house innovation – as well as launching on-line brands, expanded mobile banking apps and new product distribution models.

But what about the data? In Australia, a recent report from Roy Morgan Research reveals that we are increasingly using solely our mobile devices to access banking services (albeit at a low overall engagement level). But expect this usage to really take off when ApplePay comes to the market. Various public bodies are also embracing the hackathon spirit to open up (limited) access to their data to see what new and innovative client solutions developers and designers can come up with. Added to this is the positive consumer credit reporting regime which means more data sources can be used for personal credit scoring, and to provide even more detailed profiles about customers.

As one seasoned banker told me recently as he outlined his vision for a new startup bank, one of the “five C’s of credit” is Character (the others being Capacity – ability to pay based on cashflow and interest coverage; Capital – how much the borrower is willing to contribute/risk; Collateral – what assets can be secured against the loan; and Conditions – the purpose of the loan, the market environment, and loan terms). “Character” is not simply “my word is my bond”, but takes into account reputation, integrity and relationships – and increasingly this data is easily discoverable via social media monitoring and search tools. It stills needs to be validated, but using cross-referencing and triangulation techniques, it’s not that difficult to build up a risk profile that is not wholly reliant on bank account data or payment records.

Imagine a scenario where your academic records, club memberships, professional qualifications, social media profiles and LinkedIn account could say more about you and your potential creditworthiness than how much money you have in your bank account, or how much you spend on your credit card.

Declaration of interest: The author currently consults to Roy Morgan Research. These comments are made in a personal capacity.

Next week: Rapid-fire pitching competitions hot up…..

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