Gypsy Banking: Future of Finance

Are “Gypsy Banks” the future of Australian finance?

For 5 minutes, let’s forget about our banking oligopoly and look at another Australian industry which could also be considered oligopolistic.

The Beer Industry

With CUB and Lion Nathan dominating the beer industry, we can be certain that it isn’t as competitive as it should be. However, consumer trends have pushed back against the mainstream and enabled microbrewing to blossom. A small part of this trend is called Gypsy Brewing.

Brewer_top

What is “Gypsy Brewing”?

Gypsy Brewing is when a small group of people hire out the facilities of a larger brewer to make their own batch of beer, usually because the larger brewer is not running at capacity. This could be due to:

  1. Demand for the beer made by a specific piece of machinery is down.
  2. Maximum utilisation is impossible with seasonality, so pockets of downtime periodically emerge.

The Gypsy Brewers get access to infrastructure they could not afford at such an early stage, test their recipes, manufacturing skills and sales and distribution of the new brews. People drink their beer and the beer industry evolves, with happy taste buds in the consumer, major breweries with a new revenue stream, and smaller brewers getting access to equipment they can’t yet afford.

And this isn’t limited to beer. A friend of mine at Pacific Ice Creams was testing his IP protected process for making UHT Ice Cream, using a major ice cream manufacturer’s facilities. With this he also got access to their expertise for ensuring the food passes consumption laws and regulations.

Why can’t we create Gypsy Banks?

So why is this limited to beer and food when a financial services equivalent would provide a huge amount of value? If this approach works to improve customer choice and deliver to different niches in beer and food, the same can surely be done for banking.

Our current banks could then be described in another way: Infrastructure Banks. They have the licensing and most importantly deposit financing (the two biggest barriers to a new entrant), but they are not operating at capacity.

We know the banks are not good at manufacturing new financial products, and in recent years have been more focused on product rationalisation. Their Legal, Risk, Operations and Compliance teams have seasonality, so staff won’t always be at full capacity. Other staff in the bank, may not be completely engaged, but giving them new and varied work may help keep them satisfied. And finally, as market conditions change, the banks will be looking for new revenue streams outside the core business.

So what would a Gypsy Bank look like?

This needs to be about manufacturing new products and services, which is not where banks are going with their innovation teams (who are focused on improving digital infrastructure and the customer experience). That excess seasonality in product compliance needs to be linked up with Gypsy Banks (FinTech) who have a product vision and want to sell it themselves. The existing banks should focus on providing their infrastructure at a price, be it 10, 15, 20 or even 30% return on capital. This needs to be efficient and transparent. 

So a FinTech needs to be in a position to say to a bank, “I have a product with a recipe (costs, risks, structure etc.)”. Then work with an Infrastructure Bank to agree a timeframe for product development, ideally around the downtime in Legal, Risk and Compliance (this shouldn’t be a marketing or business unit decision).

The Infrastructure Bank then needs to:

  1. Be able to agree to commercial terms for product development/prototype and medium-term manufacturing
  2. Look at contingency options if the Gypsy Bank proves a hit: is this an acquisition, is this a joint venture, are their extra services to offer (for example FX, hedging, complementary products).

Does this work overseas?

We are seeing this evolve in many forms. Tide is an example of a white-label small business bank run by Barclays. Other white-label products are further options but they are usually paid for upfront by the would-be Gypsy provider. Technically, they are not new businesses and in many cases are add-ons, such as mortgage broker group’s white-label home loans that have no distinguishing features to existing products.

The goal is to improve financial products and services so they provide the best possible outcome for consumers, including lower risk. People want or need different flavours.

brew_variety

Why banks should support this kind of structure and the competition it will bring?

This one is simple: local Australian FinTech are not a threat. FinTech globally are not a major threat. The major threat for our banks is coming from Google, Apple and Amazon from the US and the unknown quantity emerging from China by the likes of Tencent and Alibaba. After all, CUB and Lion Nathan aren’t worried about the threat of smaller craft brewers. They’re worried about other global giants or non-beer options coming to Australia to eat their lunch.

If we can then create a competitive market in Gypsy Banks and Infrastructure Banks, Australian consumers might be able to sample financial services that don’t leave a bitter taste in their mouth. And our banks will have access to a wider range of tools to compete with new entrants locally and offer to overseas markets.

I’ll drink to that.

Read More

Building Tracker Loans

Thought piece from last week’s Bank Inquiry.

Brian Hartzer, CEO Westpac:

“When your cost of funds spike dramatically and yet you’re unable to reprice your loan book, that’s a serious for problem for the bank.

We could put that product out there but the premium involved in managing all the risks inherent in doing that … make that product really unattractive for a customer.”

Is this really true? Does a bank face an existential risk from offering Tracker Loans? How much more would they cost and what strategy would you use to deliver them.

Screen Shot 2016-10-10 at 12.24.32

Firstly, banks have the full right to offer whatever loans they wish. It is their risk management and ultimately banks offer 2 services: maturity transformation and risk transformation.

What we want to know, however, is why don’t banks offer Tracker Products right now, how could they do it and how much would they cost but still make similar returns.

Step 1: Defining a Tracker

A Tracker Mortgage is different to a variable rate loan in that the Tracker is legally linked to a premium above a reference rate, be it Libor, base rates, cash rates or in the Australian context, BBSW. A variable loan is usually defined as a discount to a bank defined standard variable rate (with discounts up to 1.75%).

For example, with the Australian cash rate at 1.5%, a Tracker could have a premium of say 2.5% above the cash rate and currently have an interest rate of 4.0%. As the RBA moves the cash rate, the borrower will pay the bank a higher interest but it will always be 2.5% above the cash rate.

Step 2: Understanding the Risks

The main risk with a Tracker is that a bank cannot manage the loan re-pricing, meaning it must make up front decisions on the Tracker’s premium above the reference rate. This is difficult as a bank needs to manage maturity transformation – balancing deposits, debt funding and securitisation programs. As those costs change, a bank usually changes the variable rate.

The variable rate works really well if a bank prices the variable aggressively – attempting to pass on wholesale cost savings to borrowers and then recoup them as costs increase. This is the cheapest way to offer home owners value at the lowest possible rate.

The problem builds when rather than passing on all the rate savings, banks pocket too much of the wholesale cost savings, either for profit or to cover costs. However, borrowers should also have some partial blame here – if they were willing to switch to those passing more on then the behaviour would subside. But human nature is difficult and the cost of switching isn’t zero. The result is that borrowers are potentially willing to pay a premium to make sure banks can’t take too much of the change in wholesale pricing.

Trust Banks: Go Variable. Don’t Trust Banks: Go Tracker.

The clear risk with a Tracker is that cost of funding increases more than 1% and a bank has to swallow that entire cost if the bank’s lenders (such as deposit holders) refuse to absorb higher costs (banks could manipulate the deposit rate). This leads to a profitable loan turning into a loss making one the bank cannot rectify unless it can reduce its funding cost.

Step 3: Tactics

Firstly, a bank can offer a Tracker product without too much risk as long as that loan is only a small portion of its loan book.

If tracker loans were 10% of the mortgage loan book, the risk of that loan being loss making still exists but it won’t be a systemic risk for the bank. It would mean the loan book becomes less profitable if funding costs widen. The bank could also have a Tracker period for the first 2 or 3 years only, as happens in the UK.

Key point though: as a response, a bank would need to charge a premium for the Tracker mortgage as its own risks do increase and a bank’s main function is risk management.

It can decide on the loan interest rate by using probability-based pricing via an economic capital framework. What are the chances of the rise in wholesale funding and the likely cost? Assuming this has a 50% probability and a 1% per annum cost: 0.5% additional charge could be levied on the consumer.

An alternative is using wholesale funding, like many banks do. However, RMBS funding costs are currently higher than deposit and other funding sources. CBA priced a Medallion RMBS early this year at about 0.5% higher than a blended cost of funding and that is a Tier 1 issuer.

Either way, this suggests the tracker would be 0.5% higher in interest rate than the median discounted variable rate. Note: this is a very basic assessment and ignores regulatory capital constraints.

Step 4: Interim Risk

A bank would also need to consider interim risk if it were holding a tracker mortgage on balance sheet. Interesting here, a bank coming to market with a Tracker is likely to have some demand and reduced sales costs: it would be, for a period of time, the only lender offering the product.

Alternative options also exist. If mortgage brokers are being paid upfront 1.5% per mortgage on average, a similar quantum to the potential loss on a tracker is paid out upfront by a bank to a 3rd party for 52% of all loans (mortgage broker share of sales). Admittedly, mortgages brokers are effective at the distribution of home loans.

If, instead, a bank decides to sell exclusively online, then it may be able to offer a Tracker at a closer rate to the variable product whilst still maintaining the current profitability.

Step 5: Mass Adoption

As Tracker loan volumes increase, the wholesale mechanisms behind them may also change and improve. Investors themselves may prefer the guaranteed headroom on loan interest rates rather than a bank’s ability to reduce them to meet their own needs. This may lead to an uptake and system-wide improvement in Tracker mortgages.

Step 6: First Mover

So who will be first mover?

For us, it is important to determine how much demand there is right now for a Tracker Loan at 4.00% to 4.25%. If there is strong demand and a bank is struggling to make a good return on equity at the moment, this product could be launched pretty quickly and have an immediate increase to ROE (as higher funding costs are not present at the moment).

We look to the smaller lenders to move first here, particularly ones looking to increase their digital distribution and reduce their cost of sales. The main problem they face is the wholesale solution. However they can easily finance an exploration phase via direct online options and the associated cost savings.

Other Options?

For banks looking for more creative options, there is potential scope in using FinTechs to bridge the gap, particularly if they have improved the process of selling online. This also introduces the scope for venture capital to fund the interim risk: will venture capital invest in Start-ups on the basis of transferring borrowers to the digital universe via improved mortgage products at prices that are attractive for the customer.

Our opinion: A Tracker Mortgage at 4.0% (cash rate + 2.5%) is possible right now and high demand would exist for it.

 Note: Thanks to the AFR.

Read More

Ensuring Long-Term Mortgage Affordability Via Optionality & Liability Management

Our widely quoted statistic is that 85% of Australian home loans are variable rate, with just 15% having any sort of fixed rate (mostly 2 & 3 years) and virtually no product offering beyond 5 year fixed. This is in huge contrast to the US and UK Mortgage markets, where 90% and 78% are fixed respectively. 90% of the US mortgage market is fixed for 15 or 30 years.

Market structure, including the regulations that govern banking, insurance and retirement systems are influencing factors in the US and UK. In Australia’s case, the dominance of a variable rate product allows banks to maintain strong pricing mechanisms over their home loan portfolios, which in effect ensures a strong level of profitability and stable banking system from their perspective.

However, this isn’t necessarily the best result for customers or the most profitable option for banks. More importantly, borrowers are left without the flexibility or certainty to manage their financial liabilities and exposure to interest rate risk – services banks should be offering. These products need to exist and our primary research suggests 25% of the entire mortgage market will move to these products within 3 years of launch.

Is Variable any different to short-term borrowing?

Borrowing short-term comes in various forms but having an interest rate that floats and can re-price is a risky consideration for the borrower. Consider this: if interest rates increase by 1%, how exposed would a variable rate borrower be? For a $500k loan that is an extra $5k per annum in payments, which is absorbing an extra 10% from the median gross household income ($80k) once you consider tax.

This is one reason why banks are required to measure serviceability on loans with a 2 or 3% increase in the variable rate. But do borrowers really pay attention to this and does the wider financial system understand what risk this will lead to? Can better customer solutions be developed?

We should assume 1% increase over the next decade will happen:

Nobody truly knows where interest rates will go but forward rates and the yield curve can give an indication. Extrapolating this, we can expect a cash rate of 2% within 7 years and 2.5% within 10-years.

Screen Shot 2016-10-03 at 11.57.22

For borrowers, we might see lower rates but how much lower can they go? They certainly will never go zero. In terms of how high they can go, increases of 0.25% per annum wouldn’t be unheard of. At this rate, by year 7, a variable home loan rate could be as high as 5.25% – a rate seen less than 3 years ago.

I have mapped out the various future home loan interest rate paths on the chart.

Screen Shot 2016-10-03 at 11.33.34

All borrowers will also have an unaffordable line – the extent to which they can no longer service their debt. I have put this at 1% above variable rates to show that what is affordable today may not be affordable by year 2023, leading to a spike in defaults to the segments that become overexposed (the RBA would have to allocate pain to somebody if they need to raise rates).

Fixing at 4.49% now for 10-years with the option to leave anytime:

Consider this option – fixing for 10 years but with the ability to leave anytime.

As a borrower, you take out the risk of higher rates straight away. You also can bring in the ability to take advantage if a rate drop occurs: optionality gives a borrower the basis for fixing at a rate they can definitely currently afford and plan towards but the option to take advantage if rates do decline.

This optionality then reduces the variability borrowers face: they will have a maximum of 4.49% interest rate but may be able to fix it to an even lower amount (I assume 3.50% appears n 2019). Further, if the affordability line moves upwards, they can take higher risk and return to a variable rate with full confidence they are no longer the segment that would feel the RBA pain if interest rates need to rapidly increase.

Screen Shot 2016-10-03 at 11.32.52

This is a potential optimal answer and a financial product driven solution for borrowers. Even though it looks complex, the borrower use is simple: fix a rate but maintain the flexibility to move to a lower rate as it becomes available. No wonder why these types of products are popular overseas.

The US financial system has figured this out. Now is the time for the Australian financial system to figure it out too.

 

 

Read More

How Fixed Rate Mortgages Transform Affordability

A previous blog discussed overall housing affordability in Australia. Using a simplified version of serviceability we determined that the median house was only affordable by the top 10 percent (90th percentile) of household incomes (under a set of conservative assumptions). This has been the status quo for a while, with lower interest rates being counteracted by higher house prices.

Screen Shot 2016-09-06 at 13.40.54

Of course, this affordability isn’t broadly true even if it feels like it. We note that many households will resort to interest only mortgages, which reduce the payment burden but do increase the risk overall. Other mechanisms also exist so that a wider portion of the population can still buy the median house.

However, the trend – where the income band increased from top 30% in 1998 to just the top 10% by 2014 is worrying. The trend exists under all circumstances even if the exact percentile brackets are different. The extra risk via interest only and the overall interest risk taken by borrowers in variable rate products is a large systemic risk Australia and the RBA needs to contend with.

Revisiting the model

If we take a 3.75% variable rate and apply it to our last data point, we observe that the top 15% can now afford the average home as the mortgage is more serviceable due to the lower interest payment (note: the house price data is not up to date). Housing gets more affordable based on our conservative affordability assumptions. One would expect an increase in house prices to close up this shift.

Taking the analysis further: what happens to house prices and affordability when our 10-year mortgage is launched?

Further assumptions:

  1. The current expected interest rate for our 10-year is at 4.5% and this is allowed to be applied for the life of the loan.
  2. We are able to deliver our mortgage going backwards using similar observed metrics plus other wholesale pricing observations (we cannot disclose this here, sorry).
  3. Serviceability can then be determined using the interest rate for the fixed rate and not via a 3% upwards stress.

Fixed is lower risk for the borrower

The subtle difference in the serviceability assessment means what the borrower is able to take on as debt is higher for fixed rate (vs. variable) as the borrower has less overall interest rate risk. Alternatively, a borrower can take on the same amount of debt but with lower risk versus a variable loan. Using our assumed mortgage rates, we obtain the following results:

  1. A Principal and Interest Variable Rate Mortgage at 3.75% using the above methodology suggests the median house is affordable to the top 15% of the population (85th percentile).  Note: the house pricing data is on a lag.
  2. For the Fixed Rate home loan, even though it has a higher fixed rate, the affordability is to a wider audience. The top 20% of earners (80th Percentile household income) can afford the median house and historically an additional 5% to 10% of the total population would be able to buy the median house.

Screen Shot 2016-09-06 at 13.39.20

Now a few key pieces to add

  1. Fixed rate debt can be taken on with more confidence knowing the rate cannot increase. Most importantly here, borrowers can have greater confidence in their repayment certainty. The cost is a higher interest rates compared to variable loans.
  2. Lower systemic risk: fixed rate home loans have lower systemic risk as interest rate increases will not impact home owners and damage retail consumption – it will impact the wholesale funding portion of the financial system. In other words, a fixed loan with repayment optionality shifts all of the interest rate risk from the borrower into the financial system.
  3. Housing hasn’t been affordable for a while, however it is more affordable to Fixed Rate borrowers on a consistent basis, meaning a wider set of customers for a similar quantum of risk. It just depends on the method and product the lending is delivered.

Look forward to comments and discussion.

Read More

6a010534b1db25970b0147e0ae51b2970b-800wi

Musings of a FinTech – Actionable Insights from Social Media

Being able to effectively mine data produced via social media is very topical, with the emergence of companies such as Thinknum providing metrics from social media and other sources to provide new insights into company performance.

However, there is a wider question here of what data can actually be harnessed to provide genuine insight and tangible value to both companies and/or individuals – the classic problem of extracting the signal from the noise.

Thinknum provides company metrics such as Twitter/Facebook followers, employees on LinkedIn and web site traffic which arguably could be useful indicators of a company’s health for investors. A recent FT article provides a good run down of some of the current crop of investor-offerings in this space.

 

In the area of housing, a recently published piece of research from Harvard, Facebook, NYU and the Bureau for Economic Research provides one such insight using data from Facebook. Entitled “Social Networks and Housing Markets”, it looks at how social media influences an individuals perception of the attractiveness of property investment.

The key takeaway from the paper is “Individuals whose friends experienced a 5 percentage points larger house price increase over the previous 24 months (i) are 3.1 percentage points more likely to transition from renting to owning over a two-year period, (ii) buy a 1.7 percent larger house, and (iii) pay 3.3 percent more for a given house. Similarly, when homeowners’ friends experience less positive house price changes, these homeowners are more likely to become renters, and more likely to sell their property at a lower price.”

It’s interesting to see how they combined the data sources for it – the model used Facebook user data along with market research data from Acxiom at its core to build rich demographic data.

One of the key uses of the Facebook friend data was the location of where an individual’s friends reside – specifically those that are within or outside of the Los Angeles county commuting zone (they surveyed homeowners all resided in LA county). This enabled the researchers to distinguish between local friend influences and biases, versus those further afield – the assumption being that house price movements experienced by friends outside the commuting zone would have been effected via social media channels (sec 1.4 p10).

This was supplemented with the relevant housing data, and a 4 question multiple-choice survey for testing the various hypotheses:

 

  1. How informed are you about house prices in your zip code?

[x] Not at all informed [x] Somewhat informed [x] Well informed [x] Very well informed

 

  1. How informed are you about house prices where your friends live?

[x] Not at all informed [x] Somewhat informed [x] Well informed [x] Very well informed

 

  1. How often do you talk to your friends about whether buying a house is a good investment?

[x] Never [x] Rarely [x] Sometimes [x] Often

 

  1. If someone had a large sum of money that they wanted to invest, would you say that relative to other possible financial investments, buying property in your zip code today is:

[x] A very good investment [x] A somewhat good investment [x] Neither good nor bad as an investment [x] A somewhat bad investment [x] A very bad investment

 

The ordering of the questions in 35% of the surveys was changed to avoid the framing effect with people’s responses, which was an interesting point to note (although they didn’t find participants were influenced by ordering of questions in this instance).

This survey & demographic data was then utilised alongside housing transaction data, and they created a number of regression models which supported the conclusions of the paper.

 

Given all of the talk about social media & mining this data, it’s a useful paper to be aware of and illustrates not only a potential use case for harnessing the power of social media to generate insights, but also how complex a task it is to do so.

Bearing in mind that the individuals in the survey were limited to those residing in LA county, and the measured impact of social media appears to influence individuals by up to ~3% which is pretty small in the grand scheme of things*, trying to apply a similar model to something similar like how social networks influence an individuals mortgage preference would be no small task!

 

*We are very excited overall that new data can not only lead to new ways of analysing risk but potentially be a strong leading indicator, allowing more time to rebalance portfolio risk. However making a judgment call on new data presents higher modelling risk.

 

Read More

Musings of a FinTech: Same, Same but not all that Different

I was recently asked to take part in a focus group with one of the Big 4 banks who shall remain unnamed. They had flown a (presumably) very expensive consulting group out from San Francisco to help them to define their “purpose”. Whilst having a clearly defined purpose is a great idea, I couldn’t help but think that it was just another example of the big banks doing everything they can to differentiate themselves from their competitors except the thing that would truly allow them to.

What I’m talking about of course is product innovation.

Banks are trying to innovate on everything, bar the thing that matters most – their products. I mean think about it, without products we wouldn’t even need the banks. Their core service is to provide us with great financial products that allow us to make the most of our money and help us achieve our dreams. Be it buying a home, building wealth or starting a business (now it sounds like I’m the one defining their purpose).

Don’t get me wrong, banks are doing a lot of work to change themselves through innovation in their retail arm with new branch designs and services, improved customer service through social media etc. or better digital offerings with great apps and technology. All of this stuff is necessary and hugely important but the elephant in the room is that we still have a set of financial products that seem almost identical across the major banks.

Same, Same

In a recent Q&A at the FinTech Melbourne Meetup, new ANZ CEO Shayne Elliot stated that his bank would be looking to invest in and partner with startups to help improve their customer experience. We totally agree with his sentiment but once again the focus isn’t on their products. Funnily enough in the same session he also said “We make most of our money selling mortgages”, yet no mention was made of the fact that their product is barely differentiable with the other 3 majors and FinTechs could help them to build out a truly unique product proposition.

At Huffle, we believe that product innovation can, and should, come from sources external to banks. Here are 3 key reasons why:

  1. Bureaucracy and speed-to-market: Over the years, banks have built up a number of processes and programs which make getting things to market quickly virtually impossible. No such barriers exist for a small tech company which has recently been established.
  1. Ability to run a Minimum Viable Product (MVP) under a different brand: Making big changes to existing products does present a risk to banks, having smaller innovative brands to test these with limits the exposure to reputational damage and allows unique propositions to be tested and refined before being adopted en masse.
  1. Fresh, outside-the-box thinking: Whilst there are probably a million good ideas floating around in a large bank, often people who have been working there follow a similar pattern of thinking. Startups that bring people together from a broad range of backgrounds have the ability to attack a problem creatively, from an angle which might not have been thought of before.

I would love to know your thoughts;

  • Do you think the banks products are up to scratch?
  • What kind of product innovation would you like to see them offer?

Read More

Originate-to-Distribute in Finance: Part 2 (FinTech Lending)

In Part 1 of this post, I described where we currently are regarding originate-to-distribute risks. Australia has a heavy sales culture across financial services, run by manual processes that the industry admits “mostly does a fulfilment process”. In the long run, FinTechs need to prove they can do more than distribution.

In recent years we have seen wider adoption in the US and Europe for online lending. Peer-to-peer models are particularly powerful, as they don’t require bank balance sheets or regulatory capital and many cost savings can be passed back to lenders or borrowers.

The main risk we see in FinTech lending is that the fledgling industry is trying to replace a mostly reliable format with a model that may overlook risk management processes. Do remember that banks, as much as they try to redress themselves as technology companies, have a core function in risk transformation.

Lending FinTech still needs to consider risk transformation

Risk transformation is an interesting thing. Some FinTechs believe that the sharing economy can probably perform the task itself and this is the purest part of peer-to-peer lending. If consumers can capture the efficiency savings, or at least the reward previously captured by banks, then it serves a purpose. However, I doubt that individuals have the capability to perform all the required risk management functions, particularly the measurement of unexpected losses in recessions.

For FinTechs who have aspirations to stand taller than the past models, they need to develop strong risk assessment at a minimum but also address the potential for fraud or manipulation over time. There are several other mechanisms you can put in place to manage those risks but they will need adoption by incumbents too as existing constraints impact what is achievable.

Will we see a wider distribution model

The question is where do FinTechs go? Without large balance sheets they will either have to be ever more reliant on a retail distribution model (peer-to-peer) or look for alternative wholesale funding models and rely on being a sales entity.

Securitisation immediately springs to mind but I would suggest this will fail if start-ups don’t’ have deep expertise in this area. A type of government guarantee, similar to a deposit guarantee, would also work but needs the FinTechs to demonstrate their ability to manage risk and a standardised framework to be built by a regulator.

What could FinTech risk management look like

Better risk management tools do and can exist but may need system-wide re-design – but start-ups are free of some legacy constraints. Answers point towards new risk management frameworks and how they directly compete against distribute-to-originate risks that sales-only business models face. This might be in construction of the FinTech or by the relationships built with incumbents, and knowledge of regulations would fall upon FinTechs (we doubt incumbents would push this on behalf on fledgling start-ups unless they wanted to pivot to a FinTech centric utility bank).

A key component will be avoiding swathes of sales heavy teams extracting upfront value, even if venture capital investors demand this to de-risk as quickly as possible or to avoid later capital raising and dilution. Luckily tech driven approaches who achieve low customer acquisition cost have the capacity to offer this, as long as the customer can recognise the additional work being done in the background (and government guarantees or third party approvals are effective ways to communicate this).

What Huffle is doing?

We have created an entire risk management framework that covers the above and forms part of why we can bring more attractive home loans to the market. Partially driven by a credit supply chain re-design but also what processes we do:

  1. Actively managing credit risk and interest rate risk on a daily basis, driven by new data sets and in-house models based upon our prior professional experience
  2. Being capital additive to the banking system

However, if we truly want to enable these changes, we need to let go of our legacy models that have the originate-to-distribute risks embedded within them. Overall, we’ll have a stronger financial system that will be more resilient through business cycles.

Read More

Originate-to-Distribute in Finance: Part 1 (What we have now)

Before we delve into variables and risks within FinTech and lending, we need to start with a simple view of what banks are.

Banks are a financial intermediary between sources of money, such as companies creating value and individual depositing their salaries and savings, and companies or people needing money, such as a loan.

The core basis of our financial system is that banks originate-to-hold to both sides of their equation (borrowers and lenders). A company borrowing from a bank owes the bank money, which is a clearly separate risk from a pensioner with their cash sitting in a savings account, for example. That pensioner receives interest payments that are unrelated to the risks the banks makes elsewhere.

Deposit holders (The Pensioner) then get government protection if the bank fails. If the bank fails, this will be due to incredibly severe losses in their lending books (insolvency) or a deep mismatch in the timing of loans (this is to do with liquidity). Banks are well regulated to cover these risks.

This model works well on a few fronts, most notably if the lenders (The Pensioner) and borrowers want 2 different things. This creates the requirement for banks to manage risks and perform maturity transformation. A bank’s core function is risk transformation.

Originate-to-distribute

The above model is a well-tested model and has functioned for many years. Bank regulators set capital to cover risks that has mostly worked but is also expected to fail at some points in time and this is where regulators, central banks or governments need to intervene.

Originate-to-distribute systems are slightly different and were originally about removing risk from the banking system: allowing banks to sell on some of their risk to investors who want that specific risk or require a higher return. This then frees up banks to make sequentially more loans rather than being full of legacy loans.

Problems pop up straight away

We have a few clear problems here. Firstly, this enables more lending. This is good if it allows more companies to exist or allows more people to borrow to achieve life goals. However, the expansion of lending pushes up asset prices. Further, the selling of loans by the bank puts a slight question as to what they care about: volume quickly surpasses quality.

This model works well if the risks are well-managed and consistent, however we have seen how this breaks down when fraud or manipulation is introduced. The originate-to-distribute increases the potential for fraud and manipulation as selling becomes a primary function for more of the credit supply chain.

Under the microscope

Now we must realise a few things: if we start to look at bank processes in a more granular way, originate-to-distribute appears in several formats in most financial intermediation systems. Sales functions themselves are originate-to-distribute, particularly if those functions are rewarded in a predominantly upfront manner or have little risk on the table.

The construction of the Australian mortgage industry brings up more examples of originate-to-distribute.

Firstly, most Australian banks under the standard variable home loan place several of the loan risks back with the borrower – notably bank credit spread risk and interest rate risk. Secondly, mortgage brokers are a large component of the mortgage industry.

Borrowers keeping the risk

The obscure part here is that if you take a loan from a bank as a borrower, the bank keeps the default risk but the borrower faces a number of other risks. The borrower keeps the interest rate risk and credit spread risk. What this means is Australian banks have manufactured a way to maintain margins and allow them to originate loans in a limited risk environment: they can simply increase interest rates to cover their margins.

Mortgage brokers are a direct originate-to-distribute model as a sales function. If they don’t’ originate loans, they don’t get paid.

Why we don’t like this

Returning back to the originate-to-distribute, as the sales function or bank is less inclined to hold risk themselves, they really only care about volume knowing that they can re-price loans at a later date. This isn’t a claim that it is occurring, rather than an observation that this has a potential weakness for fraud or manipulation. Variable rate loans and the attached credit supply chain have become lazy: risk transformation has reduced as borrowers keep more of the risk.

Now we have set out the problems in the current system, we can start to look at how they relate to risk management for FinTech and why a superior system is expected to emerge. Tune in for Part 2.

Read More

Musings of a FinTech: Why “if it ain’t broke, don’t fix it” isn’t always true

In 1977 Bert Lance coined the oft-used phrase “if it ain’t broke, don’t fix it” – but you only have to look at the disruption that’s happened due to technology over the past decade to know this isn’t true anymore.

Extensively covered examples, like Uber and the taxi industry, Airbnb and hotels or even case studies from closer to home such as Xero and accountancy, have shown that left field thinking and broad access to technology have changed the game. It’s no longer good enough to rest on the laurels of existing business models, just because they bring consistent returns and customers appear to be content. Chances are there is a better way to do things which someone is working on quietly in their bedroom or a co-working space somewhere.

If it aint broke fix it

At Huffle Home Loans, this is what we are looking to bring to the home loan space. For years, banks in Australia have delivered record profits driven off the back of a mortgage industry where the products have stayed stagnant and the public’s appetite for property as the most popular investment option has kept demand high. To the banks, and most consumers, the system isn’t broken… So why fix it?

We think there is a better way, and it’s all about fixing it!

Huffle has built a new home loan model, which allows us to take on some of the risk that a customer would normally absorb (through their interest rate). This in turn, enables our partner bank to offer a lower interest rate, fixed over a long period of time. The loan also come with added features like; no penalties for paying out early, and flexibility over breaking out of the loan after a period of time (before the full term).

The biggest hurdle is getting the banks on board. As mentioned, they have a proven model that continues to drive increasing profits with the added bonus of high barriers and government protection preventing new entrants. But what about you – the customer? Are the current mortgages in the market what you really want and need? Or can they be delivered in ways that better serve you?

That’s why we need your voice and support to join together and help bring our products to life. We’ve built the model. We have the team in place. The last 2 things we need are a bank to supply the loans, and most importantly, the customers telling the banks that it may not be broke – but we can surely FIX it.

Sign up at huffle.com.au to keep informed about our launch and lend your voice to our movement.

Read More