Tag Archives: #fintech

#FinTech: The 8 things I want from mobile banking apps

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As we await the launch of ApplePay in Australia, and in light of the plethora of mobile banking tools, here is my wish list against which all such apps should be assessed:

  • TRUST – is my money safe?
  • CONVENIENCE – can I do multiple transactions from within the same app?
  • SECURITY – is my personal data secure?
  • RELIABILITY – will it always be there when I need to use it?
  • FLEXIBILITY – can I access and transact with all my accounts, brands and products from a single app?
  • COST – can I expect lower transaction, service and account fees if I use it?
  • SPEED – is it real-time?
  • EASE OF USE – is it intuitive?

Next week: Finding a career in #FinTech

Do we need a #FinTech safe harbour?

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As part of the recent FinTech Melbourne Meet Up, there was some discussion on the regulatory challenges startups face when trying to validate an early-stage concept. The notion of a safe harbour or “regulatory sandbox” has gained some momentum, with ASIC’s Innovation Hub, and a commentary by Deborah Ralston, of the Australian Centre for Financial Services, who is also inaugural Chair of ASIC’s Digital Finance Advisory Committee.

If we assume that the main purposes of financial regulation are: system stability, minimum professional standards, consumer confidence, investor protection, market transparency and risk mitigation, then I doubt anyone can deny the benefit of a formal and robust compliance regime. However, technology and innovation are combining to challenge and disrupt the inherent inefficiencies that can accrue within a static regulatory environment (especially one that is reactive, rather than pro-active), which is largely designed to monitor legacy frameworks and incumbant institutions.

While the ASIC initiative is not the same as obtaining an ATO private tax ruling, it does at least show that the regulator is keen to be more consultative in helping startups test new ideas. But the reality is the cost of initial compliance and licensing can be a barrier to a new venture, before the concept has even been market-tested. So perhaps there is an opportunity to ring-fence emergent FinTech ventures, so they can explore real-world applications, but limited by market scope, number of participants, transaction values and timeframes. (Such a model already exists for private equity offerings….)

As it stands, in the case of P2P lending platforms, a startup might find itself having to be licensed and regulated as a financial services provider, an approved consumer credit provider, an authorised depository institute and possibly a licensed financial planner as well. That’s a lot of compliance for a new business that might not even have a single customer.

From my own experience, what constitutes “financial advice” is subject to very wide interpretation. Several years ago, I was responsible for introducing a new financial product to the local market – a bond pricing information service. The service was aimed only at institutional investors (not retail customers), based on collated and published data supplied by existing market participants. Nor was it a real-time data feed; rather, it delivered intraday and end of day prices calculated on actual traded bonds. Yet the regulator determined this constituted “financial advice”, even though no trading recommendation or investment decision was inherent in the data. It was also designed to offer a more transparent and objective process for pricing portfolios of less liquid or rarely traded securities, where mark-to-market solutions are unavailable or inappropriate – thereby providing some clarity to market participants.

Meanwhile, the responses to shady advice and other malfeasance inflicted upon retail investors by “established” financial institutions and “traditional” financial planners usually take years to work their way through the legal and regulatory processes of investigation, mediation, settlement and prosecution. (And if anyone wants to understand what actually caused the GFC, well before the term FinTech had been coined, check out John Lanchester’s book “Whoops!”)

Next week: What I want from a mobile banking app.

A Tale of Two #FinTech Cities – Melbourne vs. Sydney….

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Inter-city rivalry between Melbourne and Sydney is nothing new. The fact that neither city is the national capital only adds to the frisson. The usual debates as to which is the better for sport, culture, beaches, food, weather, property prices, live music, public transport and coffee normally mean Melbourne edges out Sydney in most categories. (But then, I’m probably biased – however, having lived and worked in both, I think I am reasonably objective.)*

When it comes to startups, and FinTech in particular, the debate is beginning to hot up. At a recent FinTech Melbourne Meetup the topic was “is there room for both?”. The speakers, Toby Heap for Sydney, and Stuart Richardson for Melbourne, remained tactful and diplomatic, as it’s not really appropriate to talk about which is better – more a case of choosing “which is the right location for your own particular FinTech”. So, the debate avoided mere point-scoring, and tried to establish some commonalities, as well as provide some considered views on the benefits inherent within the key differences.

Both cities have a growing reputation for startup success, built on some core foundations: groups of angel investors and VC funds with an increasing FinTech focus; several accelerator programs, incubators and co-working spaces; and a community of founders and aspiring tech entrepreneurs.

From an industry perspective, two of the four Pillar Banks are headquartered in Sydney, and two in Melbourne. More insurers have their HQ’s in Sydney compared to Melbourne (apart from health insurance, where Melbourne hosts the largest market providers), while Tier 2 and regional banks (by their very nature) are more likely to be located outside either city (not including wholly owned brands of the Big 4).

As for pension funds and asset management, particularly in relation to Australia’s superannuation sector, Melbourne is clearly the bigger player, particularly for the largest industry funds (based on their historical links to the trade union movement). In addition, Melbourne is home to some substantial family offices, as well as specialist asset managers, including overseas firms. After all, Melbourne’s establishment wealth comes from the nineteenth century gold boom.

When it comes to markets, Sydney wins out by virtue of housing the main equities exchange, as well as being a hub for futures, fixed income and forex. Sydney also hosts more investment banks, including local branches of foreign players.

In some respects, the differences can be likened to the market roles and dynamics of London vs Edinburgh, New York vs Boston, Frankfurt vs Munich, or even Hong Kong vs Singapore, for example.

For me, however, the key distinction between Sydney and Melbourne can be summarised as: “Sydney trades, Melbourne invests”.

* Note: Content in Context is taking a well-deserved break. Starting this week, the next few posts will feature some brief blogs on different aspects of FinTech. Normal service will be resumed in early November

Next week: do we need a #FinTech safe harbour?

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

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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