## Fwd: LO 2.3: Com pare and contrast the age-weighted, the volatility-weighted, the

LO 2.3: Com pare and contrast the age-weighted, the volatility-weighted, the

correlation-weighted, and the filtered historical sim ulation approaches.

The previous weighted historical simulation, discussed in Topic 1, assumed that both
current and past (arbitrary) n observations up to a specified cutoff point are used when
computing the current period VaR. Older observations beyond the cutoff date are assumed
to have a zero weight and the relevant n observations have equal weight of (1 / n). While
simple in construction, there are obvious problems with this method. Namely, why is the
wth observation as important as all other observations, but the (n + 1) th observation is so
unimportant that it carries no weight? Current VaR may have “ghost effects” of previous
events that remain in the computation until they disappear (after n periods). Furthermore,
this method assumes that each observation is independent and identically distributed. This
is a very strong assumption, which is likely violated by data with clear seasonality (i.e.,
seasonal volatility). This topic identifies four improvements to the traditional historical
simulation method.

Age-weighted Historical Sim ulation

The obvious adjustment to the equal-weigh ted assumption used in historical simulation is
to weight recent observations more and distant observations less. One method proposed by
Boudoukh, Richardson, and Whitelaw is as follows.1 Assume w(l) is the probability weight
for the observation that is one day old. Then w(2) can be defined as \w (l), w(3) can be
defined as X2w(l), and so on. The decay parameter, X, can take on values 0 < X < 1 where
values close to 1 indicate slow decay. Since all of the weights must sum to 1, we conclude
that w(l) = (1 — X) / (1 — Xn). More generally, the weight for an observation that is i days
old is equal to:

x 1- 1 (1 – X)

1 – X n

The implication of the age-weighted simulation is to reduce the impact of ghost effects and
older events that may not reoccur. Note that this more general weighting scheme suggests
that historical simulation is a special case where X = 1 (i.e., no decay) over the estimation
window.

Professor's Note: This approach is also known as the hybrid approach.

1. Boudoukh, J., M. Richardson, and R. Whitelaw. 1998. “The best of both worlds: a hybrid

approach to calculating value at risk.” Risk 11: 64-67.

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Topic 2
Cross Reference to GARP Assigned Reading – Dowd, Chapter 4

Volatility-weighted Historical Sim ulation

.Another approach is to weight the individual observations by volatility rather than
proximity to the current date. This was introduced by Hull and White to incorporate
changing volatility in risk estimation.2 The intuition is that if recent volatility has increased,
then using historical data will underestimate the current risk level. Similarly, if current
volatility is markedly reduced, the impact of older data with higher periods of volatility will
overstate the current risk level.

This process is captured in the expression below for estimating VaR on day T. The
expression is achieved by adjusting each daily return, r j on day t upward or downward
based on the then-current volatility forecast, ct • (estimated from a GARCH or EWMA
model) relative to the current volatility forecast on day T.

where:
rt j = actual return for asset i on day t
<Tt i = volatility forecast for asset i on day t (made at the end of day t — 1)

= current forecast of volatility for asset i

Thus, the volatility-adjusted return, rt -t , is replaced with a larger (smaller) expression if
current volatility exceeds (is below) historical volatility on day i. Now, VaR, ES, and any
other coherent risk measure can be calculated in the usual way after substituting historical

There are several advantages of the volatility-weighted method. First, it explicitly
incorporates volatility into the estimation procedure in contrast to other historical methods.
Second, the near-term VaR estimates are likely to be more sensible in light of current
market conditions. Third, the volatility-adjusted returns allow for VaR estimates that are
higher than estimates with the historical data set.

Correlation-weighted Historical Sim ulation

As the name suggests, this methodology incorporates updated correlations between asset
pairs. This procedure is more complicated than the volatility-weighting approach, but it
follows the same basic principles. Since the corresponding LO does not require calculations,
the exact matrix algebra would only complicate our discussion. Intuitively, the historical
correlation (or equivalently variance-covariance) matrix needs to be adjusted to the new
information environment. This is accomplished, loosely speaking, by “multiplying” the
historic returns by the revised correlation matrix to yield updated correlation-adjusted
returns.

2. Hull, J., and A. White. 1998. “Incorporating volatility updating into the historical simulation

method for value-at-risk.” Journal of Risk 1: 5-19.

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Topic 2
Cross Reference to GARP Assigned Reading – Dowd, Chapter 4

Let us look at the variance-covariance matrix more closely. In particular, we are concerned
with diagonal elements and the off-diagonal elements. The off-diagonal elements represent
the current covariance between asset pairs. On the other hand, the diagonal elements
represent the updated variances (covariance of the asset return with itself) of the individual
assets.

f

/
0" • •
1,1
(T • •
{ b1

\
0" • •
1,J
CT • •
b))

Variance(Xj)

C o v (X ;, Xj )'

C ov(X j, X j ) Variance(Xj)
' /

Notice that updated variances were utilized in the previous approach as well. Thus,
correlation-weighted simulation is an even richer analytical tool than volatility-weighted
simulation because it allows for updated variances (volatilities) as well as covariances
(correlations).

Filtered Historical Sim ulation

The filtered historical simulation is the most comprehensive, and hence most complicated,
of the non-parametric estimators. The process combines the historical simulation model
with conditional volatility models (like GARCH or asymmetric GARCH). Thus, the
method contains both the attractions of the traditional historical simulation approach with
the sophistication of models that incorporate changing volatility. In simplified terms, the
model is flexible enough to capture conditional volatility and volatility clustering as well as a
surprise factor that could have an asymmetric effect on volatility.

The model will forecast volatility for each day in the sample period and the volatility will
be standardized by dividing by realized returns. Bootstrapping is used to simulate returns
which incorporate the current volatility level. Finally, the VaR is identified from the
simulated distribution. The methodology can be extended over longer holding periods or
for multi-asset portfolios.

In sum, the filtered historical simulation method uses bootstrapping and combines the
traditional historical simulation approach with rich volatility modeling. The results are then
sensitive to changing market conditions and can predict losses outside the historical range.
>From a computational standpoint, this method is very reasonable even for large portfolios,
and empirical evidence supports its predictive ability.

A d v a n t a g e s a n d D i s a d v a n t a g e s o f N o n -Pa r a m e t r i c M e t h o d s

## LO 79.3: Describe the framework for analyzing culture in the context of financial

LO 79.3: Describe the framework for analyzing culture in the context of financial practices and institutions.
An alternative to the efficient markets hypothesis (EMH) is the adaptive markets hypothesis (AMH) (Lo, 2004, 2013).13,14 In the AMH, individuals compete for scarce resources. These individuals adapt to both their past and current environments. Like people sort themselves based on values into political parties, they also sort themselves into professions. For example, those who value fairness might choose jobs where they can fight for fairness (e.g., teachers of under privileged children or sports referees). In contrast, those
11. Luigi Guiso, Paula Sapienza, and Luigi Zingales, Does Culture Affect Economic Outcomes?
Journal o f Economic Perspectives 20, no. 2 (Spring 2006): 2348.
12. Ryan Goodstein et al., Contagion Effects in Strategic Mortgage Defaults (GMU Working
Paper in Economics no. 13-07, January 2013), ssrn.com/abstract=2229054.
13. Andrew W. Lo, The Adaptive Markets Hypothesis: Market Efficiency From an Evolutionary
Perspective, Journal o f Portfolio M anagem ent 30, no. 5 (2004): 15-29.
14. Andrew W. Lo, The Origin of Bounded Rationality and Intelligence, Proceedings o f the
American Philosophical Society 157, no. 3 (September 2013): 269-80.
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who do not believe in fairness above all, may choose high pressure sales jobs or choose to teach in expensive boarding schools.
Context is also important to behavior. For example, in a study by Cohn, Fehr, and Marechal (2014)15, the impact of context on financial culture, based on the honesty of participants from a large international bank, was gauged based on a coin-tossing experiment. The 128 participants were split into two groups. Half of the subjects were asked seven questions about their jobs at the bank prior to the exercise, while the other half were asked seven non- banking questions. The authors induced the participants to apply the cultural standards of the banking industry by asking them about banking prior to the experiment. Those who were asked banking questions were significantly more dishonest during the exercise than the group that was asked non-bank questions. The non-bank question group displayed a level of honesty equal to those working in other industries (i.e., nonfinancial). However, individual values can allow one to resist a bad norm.
A study by Dyck, Morse, and Zingales (2013)16 finds, using class action lawsuit data from 1996 to 2004, that fraud increased as the stock market increased in the first five or six years then declined after the dot.com bubble burst in 20012002. Ponzi schemes also increased during bull markets between 1988 and 2012, decreased after 20012002, and then increased again leading up to the 20072009 financial crisis (Deason, Rajgopal, and Waymire 2013).17 The authors note that Ponzi schemes are more difficult to sustain in bear markets. Also, regulation and enforcement budgets often increase after bubbles burst (i.e., the dot.com and the housing market bubbles). The authors find that Ponzi schemes are more likely when there is an affinity link (i.e., a strong connection) between the offender and the victim, such as they are members of the same religion or are part of the same ethnic group, indicating that shared culture can be used for ill. Both studies indicate that culture is often a product of the environment (e.g., good versus bad economic times, perceived moral character and changing character of leaders such as CEOs, movie stars, politicians, and so on).
There are several examples of corporate culture and the role it has played in company failures in the financial industry. They include: Long-Term Capital Management (LTCM). LTCM had a strong corporate culture that
was well-respected across the financial industry. Founders John Meriwether (a former head of bond trading at Salomon Brothers) and Robert Merton and Myron Scholes, future Nobel Prize in Economics winners, founded a company based on mathematical models that the industry perceived as ultra-safe and invincible, leading to extremely favorable credit terms and little to no margin requirements. In fact, the failure of LTCM may even be seen as the failure of the firms creditors corporate cultures, overconfident in their abilities to assess the risks of the firms to which they loaned money.
15. Alain Cohn, Ernst Fehr, and Michel Andre Marechal, Business Culture and Dishonesty in the
Banking Industry, Nature 516, no. 7529 (December 2014): 86-89.
16. Alexander Dyck, Adair Morse, and Luigi Zingales, How Pervasive Is Corporate Fraud?
(working paper, August 2013).
17. Stephen Deason et al., Who Gets Swindled in Ponzi Schemes? (unpublished paper, Goizeta
Business School, Emory University, Atlanta, GA, 2015).
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American International Group (AIG). AIGs culture centered on its original chairman,
Maurice Hank Greenberg. Compensation plans rewarded loyalty to the firm. Much of AIGs success was attributed to excellent insurance underwriting. That underwriting was monitored across divisions by Greenberg himself. When, in 2005, the board replaced Greenberg due to headline risk that Greenberg may have played a role in financial irregularities, the new chair, Martin Sullivan, assumed the vigorous risk management culture would remain without Greenbergs watchful eye. Without Greenberg, however, the companys actions grew more aggressive and risky [selling billions of dollars of credit default swaps (CDS)], ultimately leading to a government bailout in 2008. In fact, AIGs strong risk management culture may have led to its failure in the sense that firm leaders believed that strong risk management and high growth in a traditionally lower risk and lower growth industry like insurance, would translate into higher risk activities such as selling CDSs. As a result of its confidence in its own risk management practices, billions of dollars of toxic assets were allowed to appear on AIGs balance sheet.
Lehman Brothers. The culture at Lehman Brothers was such that flaws were not only

Sadly, regulatory culture is not immune to these cultural failings. For example, the Securities and Exchange Commission (SEC) had received several warnings about Bernie Madoff s Ponzi scheme but failed to act. The SEC had a hierarchical corporate structure that impeded the flow of information from one division to another. This fact meant that SEC offices that were getting complaints about Madoff, did not talk to each other and did not even know that they were each investigating Madoff (i.e., the Northeast Regional Office and the Office of Compliance Inspections and Examinations). Low morale, a distrust of management, and a compartmentalized, hierarchical, and risk averse culture that feared public scandal contributed to the shocking slowness with which the SEC caught on to Madoffs scheme. The SEC has since tried to remedy some of the failings in its corporate culture.
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## LO 79.2: Examine the role of culture in the context of financial risk management.

LO 79.2: Examine the role of culture in the context of financial risk management.
Firms, including financial firms, often hire go-getters, more aggressive people with higher levels of risk tolerance. The thought is that they have the personality and competitive nature to move a firm forward. This personality type is drawn to riskier activities, what sociologist Stephen Lyng refers to as edgework (Lyng 1990).9 Sports enthusiasts who skydive and do other dangerous activities get a certain pleasure from being one of the few who can, relative to the average person, navigate these dangerous waters. These individuals voluntarily take risks, without necessarily expecting a reward for that risk.
Sociologist Charles W. Smith recently used this idea of edgework to compare financial market traders to sea kayakers (Smith 2005).9 10 While people drawn to higher-risk activities view themselves as exceedingly independent, they actually, according to Lyng, feel solidarity with fellow edgeworkers and at odds with the broader culture. In finance, this can manifest as a split between the trading desk (and perhaps upper management) and the rest of the firm. While executives may encourage risk aversion, they often seek out risk in their own lives, resulting in a do as I say, not as I do situation.
Contrast risk management in the insurance industry versus the banking industry. Revenue in the insurance industry is in large part determined by regulation. Insurance companies have an incentive to manage risks and protect against the downside. Bank earnings are more variable and are tied to bank size and the use of leverage. This means historically that insurance companies are more conservative than banks.
In the financial culture, protestors, regulators, and other dissenting opinions are often ignored. Criticisms are diminished, discounted, and dismissed. But market participants,
9. Stephen Lyng, Edgework: A Social Psychological Analysis of Voluntary Risk Taking, The
American Journal o f Sociology 95, no. 4 (January 1990): 851-86.
10. Charles W. Smith,Financial Edgework: Trading in Market Currents, in Edgework: The
Sociology of Risk Taking, ed. Stephen Lyng (London: Routledge, 2005).
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whether investors, entrepreneurs, bankers, regulators, or executives, are all part of and shaped by the culture. After a crisis, such as that of 20072009, regulation is good, greed is bad. But when economic times are good, greed is good and regulation is unnecessary, and the cycle continues.
Provided an incentive to be good, individuals will be good, according to economists. Economic self-interest is a learned behavior. A Wall Street manager, driven by a bonus culture, will excel at some parts of the job (those that result in the reward, the bonus) and be less successful at those not rewarded, such as following the ethical guidelines of the firm. If the incentives change and reward ethical behavior, the same manager may behave differently. Behavior can be predicted based on a knowledge of incentives and economic self-interest. Spoken in the extreme, bad behavior results from incentive problems, and can be corrected once an appropriately designed system of rewards and punishments is constructed. Economists always look to incentives when investigating bad behaviors.
An example is the strategic defaults on mortgage loans during the financial crisis. As housing prices fell and borrowers were underwater (i.e., homes were worth less than their loans) on their mortgages, it made sense (i.e., there was an economic incentive) to default, whether one could afford to pay or not. However, what role did culture play in strategic defaults? A study by Guiso, Sapienza, and Zingales (2013)11 found that survey respondents were 31% more likely to strategically default if they knew someone else who had done so. The finding was confirmed by a study (Goodstein et al. 2013)11 12 13 14 that showed delinquency rates were influenced by zip code, controlling for income. The more delinquencies in the zip code, the greater the strategic defaults.
Incentives and culture are inextricably linked. It is not possible to single out one or the other as the culprit for bad behavior.
An a l y z in g a n d Im pr o v in g C u l t u r e

## LO 79.1: Explain how different factors can influence the culture of a corporation

LO 79.1: Explain how different factors can influence the culture of a corporation in both positive and negative ways.
In the movie Wall Street (1987)1, Gordon Gekko, played by Michael Douglas, says:
The point is, ladies and gentleman, that greed, for lack of a better word, is good. Greed is right, greed works. Greed clarifies, cuts through, and captures the essence of the evolutionary spirit. Greed, in all its forms, greed for life, for money, for love, knowledge, has marked the upward surge of mankind. And greed, you mark my words, will not only save Teldar Paper, but that other malfunctioning corporation called the USA.
This monologue, based on a commencement address made by Ivan Boesky (who was convicted of insider trading 18 months later) at U.C. Berkeley in 1986, has become part of popular culture. It inspired legions of people to enter the field of finance, despite the fact that Gekko was the villain in the film and his plot was foiled by his young protege. But the
1. Wall Street, directed by Oliver Stone (20th Century Fox, 1987).
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Gekko effect, and the culture of greed that goes along with it, lives on in corporations and institutions. Corporate culture can instill values in employees that make financial crimes and misdemeanors more likely.
C o r po r a t e C u l t u r e f r o m t h e To p D o w n
O Reilly and Chatman (1966)2 define corporate culture as a system of shared values that define what is important and the norms that define appropriate attitudes and behaviors for organizational members. Schein (2004)3 focuses more on the learned assumptions of people in a group that help new group members think and feel in relation to the groups problems. The values of an organization, and its culture, ultimately define the group. One can think of culture more as biological, than economic, in the sense that it propagates itself. Culture also spreads, like an epidemic. Culture is spread through: Group leaders (the root source of the cultural epidemic). Group composition (the population through which the epidemic spreads). The group environment (which forms the groups response to the epidemic). Leadership, or the authority that comes from the top of an organization, shapes culture as much or more than financial incentives. Charismatic leaders, like Gekko, garner authority via a strong, forceful personality. Traditional leaders garner authority through established customs. Authority figures establish proper behaviors, both negative and positive, of those below them through social sanctions (e.g., praise or reprimand, approval or disapproval). In some cases, like the military, people subordinate themselves to the will of others out of the belief that it will assist in the achievement of the goals of the group.
One question that arises, and can be answered to some degree with academic research, is how large must the financial incentive be to entice someone to behave badly? The answer, based on research, appears to be that there must be something else in the culture, beyond financial incentive, to entice bad behavior. Two famous examples from social sciences research support this conclusion. They are:
In a study by Milgram (1963)4 26 out of 40 subjects delivered what they believed was In a study by Milgram (1963)4 26 out of 40 subjects delivered what they believed was a high voltage, potentially lethal, electric shock to victims, at the suggestion of the experimenter. All of the subjects expressed doubt and concern, three appeared to have seizures and a result of the stress induced by the situation, but they all administered the shock anyway. The financial reward was $4.00 plus carfare, which equates to approximately$50.00 today. Thus, financial incentive cannot explain the behavior.
2. Charles A. O Reilly and Jennifer A. Chatman, Culture as Social Control: Corporations, Cults, and Commitment, in Research in O rganizational Behavior, vol. 18, ed. Barry M. Staw and L.L. Cummings (Greenwich, CT: JAI Press, 1996), 157-200.
3. Edgar H. Schein, O rganizational Culture and Leadership (San Francisco, CA: Jossey-Bass, 2004). 4. Stanley Milgram, Behavioral Study of Obedience, The Journal o f Abnorm al and Social
Psychology 67, no. 4 (October 1963): 371-78.
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A Stanford psychology professor, Phillip Zimbardo, created a prisoners and guards
study in 1971 (Haney, Banks and Zimbardo 1973a, b)5,6. Participants were randomly assigned the roles of prisoners or guards. Zimbardo played the role of prison superintendent. Guards began treating prisoners inhumanely almost immediately. Verbal abuse, manipulated bathroom privileges and sleeping conditions, and nudity used to humiliate prisoners were all used by the guards. The experiment was terminated after six days at the urging of Zimbardo s wife, who was interviewing subjects. The study participants were paid $13.00 per day, which equates to approximately$90.00 today, again not likely a financial incentive big enough to explain the guards behavior.
One of the lessons learned from these and other studies is that financial incentives alone are not enough to explain bad behavior. In the Milgram study the subjects, despite physical and mental distress of their own, acted on the commands of the authority figure. In the Zimbardo study, subjects acted with enthusiasm, fulfilling the roles they believed were expected of them by the authority, prison superintendent (and professor) Zimbardo. In both cases the financial incentive was minimal. There is a type of moral hazard that emerges, even if (or perhaps because of) the authority has a good track record. People are taught that when experts speak, they are correct. So if, like in the cases of the Milgram and Zimbardo studies, the authority figure seems okay with the behavior, people may act, as Shiller (2005)5 6 7 puts it, from peoples past learning about the reliability of authorities.
However, just as corporate leaders may encourage bad behavior and promote goals which are immoral, unethical, and in some cases even irrational, they also can encourage employees to be more productive, increasing the competiveness of the firm.
Corporate Culture from the Bottom-Up
The people within a system (i.e., the composition) also influence the culture. Firms hire people and, during the process, filter out other qualified people. This filtering process can impact culture. For example, beginning in the 1980s, investment banks started deliberately targeting graduates from elite schools such as Harvard and Princeton. These hires brought their social values with them and as bankers retired, these values became the norm at Wall Street firms, according to a study by Ho (2009).8 The high Wall Street compensation levels were perceived as appropriate for members of the elite tolerating the personal risk of job insecurity and the potential to be let go in these investment banks.
Company managers recruit people who they believe will be useful to the organization. While choosing from a diverse pool of applicants, companies often choose people who reinforce the corporate culture that already exists. These people then succeed in the culture and a feedback loop occurs, reinforcing the companys existing culture. In the best of circumstances this leads to a strengthening of culture and stronger performance. However, companies can also benefit from a diversity of thought that results from different
5. Craig Haney, Curtis Banks, and Philip Zimbardo, Interpersonal Dynamics in a Simulated
Prison, International Journal o f Criminology and Penology 1 (1973): 69-97.
6. Craig Haney, Curtis Banks, and Philip Zimbardo, A Study of Prisoners and Guards in a
Simulated Prison, N aval Research Reviews 9 (1973): 1-17.
7. Robert J. Shiller, Irrational Exuberance, 2nd ed. (Princeton, NJ: Princeton University Press,
8. Karen Ho, Liquidated: A n Ethnography o f Wall Street (Durham, NC: Duke University Press,
2005).
2009).
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backgrounds, ethnicities, and so on. This can help a company avoid group think. There is an important place in modern corporations, especially in uncertain economic times, for whistle blowers, devils advocates, innovators, and for those whose thoughts and ideas run contrary to the norm (i.e., the existing corporate culture).
Culture and the Environment
Regulation, the economic climate, the competitive environment, and many other factors also affect culture. For example, consider driving fatalities in the United States. Despite significantly more drivers, more miles driven, and the same propensity for risk taking, fatalities have decreased in the last 40 years. That is due to environmental factors. Cars have become safer (material culture), the police enforce speed limits (regulatory culture), and there is a stigma associated with driving while under the influence of alcohol (social culture).
C o r po r a t e C u l t u r e a n d Fin a n c ia l Ris k M a n a g e m e n t

## LO 78.3: Examine the implications for financial stability in the event that FinTech

LO 78.3: Examine the implications for financial stability in the event that FinTech credit grows to account for a significant share of overall credit.
Benefits
The growth of FinTech credit could result in greater financial inclusion. There are two key underlying points here: (1) investing in FinTech loans could diversify an investment portfolio, and (2) borrowers such as self-employed individuals or small businesses, who have historically been restricted in the amount of financing obtained from traditional banks, may now have access to sufficient capital to grow their businesses.
With all credit services being transacted electronically rather than with paper and the traditional branch banking, FinTech could bring out lower transaction costs that will benefit borrowers in the form of lower financing costs and benefit lenders in the form of higher risk-adjusted returns.
Additionally, because the use of FinTech could result in lower transaction costs and greater convenience for customers, it may incentivize traditional banks to compete more directly by innovating (i.e., establish or acquire FinTech platforms) and/or operating more efficiently (i.e., discontinuing outdated IT systems and adopting newer online IT systems). Another possibility is for banks to cooperate with FinTech platforms by establishing partnership agreements to potentially improve risk analysis or target certain underserviced areas in the market (i.e., self-employed individuals), for example.
FinTech credit may offer newer and a greater variety of lending options (beyond those of traditional banking), some of which may be more appropriate and tailored to the needs of certain borrowers.
The emergence of FinTech as a major player would reduce the level of credit situated in the banking sector. It would serve as a backup source of credit in the economy. For example, if there are negative effects that are specific only to the banking sector (i.e., unsystematic risks) that significantly reduce its ability to lend during an economic crisis, then FinTech could potentially come to the rescue.
Assuming that FinTech platforms and traditional banks remain relatively separate in their operations, it should shield the FinTech industry from risks specific to banks. However, some banks are starting to provide operational, loan origination, and referral services to FinTech platforms, which increases their dependence on banks and may make the FinTech industry more vulnerable to the same risks as banks.
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Unlike traditional banks, the FinTech industry is not exposed to maturity mismatch with its lending so it may serve as a source of credit should the economy otherwise be subject to a major liquidity shock. FinTech platforms tend to lend almost exclusively in the domestic market so compared to banks, they will be far less impacted by international shocks.
Like traditional loans, FinTech credit loans may be securitized, which allows for active trading of the resulting securities and funding to borrowers from a wider range of investors.
Risks
With more competition in the lending market with the growth of FinTech, it may significantly cut traditional banks revenue and profits, which would lower their access to capital. It may force them to take on more risk to maintain market share or compensate for losses, which could be demonstrated by weaker overall lending standards (in well-developed credit markets), for example.
Banks may be taking on incremental operational and reputational risk by working with FinTech platforms, using electronic credit models, and outsourcing IT to third-parties. The operational risk is already there for many banks but would be exacerbated as a result of FinTech. Some banks may be involved in loan origination for FinTech platforms and then involved in subsequent FinTech loan sales to investors, all of which would be largely unregulated. Should borrowers or investors suffer significant losses due to those transactions, the banks could suffer from reputation risk for being viewed as operating outside of proper credit regulation.
The growth of FinTech may also promote procyclical credit provisions. It would manifest itself in more credit being available (i.e., weaker lending standards) when it is needed less in an economic upturn, but less credit being available when it is needed more in a downturn.
Should there be a reduction in FinTech lending, there is the issue of replacing the credit within the FinTech sector or through traditional banks. Regarding the FinTech sector, FinTech credit tends to be very concentrated within domestic markets so it would likely be challenging to find replacement credit on a timely basis. Regarding traditional banks, borrowers that are likely to access FinTech are often those who would not normally be able to obtain sufficient credit through traditional banks (i.e., small business owners or self- employed individuals) so it is not likely that they will be able to find replacement credit outside of FinTech.
The nature of FinTech credit would make it more difficult for regulators to properly monitor activities given the likely lack of reporting requirements and supervision. Because FinTechs activities may largely be unregulated, government policy actions related to strengthening the credit industry during an economic downturn, for example, may be ineffective. FinTech lenders would not be able to take advantage of public safety measures such as emergency liquidity (from the central bank) that would be available to traditional banks.
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With securitization, the dependency between FinTech and the rest of the financial markets increases, thereby reducing FinTechs protection from risks faced in the general financial markets (and vice versa). In addition, the repackaging of FinTech loans could make the financial markets even less transparent from both an investing and a regulatory perspective.
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Ke y Co n c e pt s
LO 78.1 The FinTech industry may develop due to the following supply reasons:
FinTech lenders are likely to go further beyond conventional lenders in their use of technology, ultimately resulting in stronger client service.
The use of an online business model for FinTech platforms typically has small upfront
costs. FinTech lenders may be able to operate in very much the same way as conventional lenders, yet avoid their large fixed costs as well as the regulatory constraints. FinTech lenders may benefit from some market opportunities left untapped by traditional lenders and potential tax and regulatory incentives.

The FinTech industry may develop due to the following demand reasons: Greater use of online services by many younger customers and those in certain emerging
markets.
Loss of trust in traditional lenders in the aftermath of their failures to provide credit to

borrowers during the financial crisis. FinTech loans may be appealing to investors who view FinTech lending as investing in an alternative asset class that may provide higher returns and lower risk. Possible impediments to development of the FinTech industry include: Traditional banks have been in the online banking world for many years and some
customers may not be willing to switch to an unknown digital lender.
Considerable uncertainty exists as to whether emerging FinTech lenders would survive
an economic downturn.
Regulatory requirements could severely limit the growth of FinTech in jurisdictions
where the licensing requirements are overly onerous or where interest rate limits apply.
LO 78.2 Traditional P2P lending platforms establish an online presence whereby borrowers and lenders may interact directly with each other.
The potential borrower makes an initial loan application on the online platform by providing the required information, which is reviewed and approved by the platform. From there, only the approved applications will go into the pool from which potential lenders may select the loan(s) they want. At that point, the loan contracts are established directly between the borrower and lender. From the borrower and/or lender, the platform operator takes fees such as for loan setup or loan repayments.
In general, borrowers establish the maximum rate for loans and lenders establish the minimum rate. The platform operator uses the information together with the loan amounts to match borrowers and lenders.
The majority of platforms allow for partial or full pre-payment of loans on a penalty-free basis.
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Should a borrower be potentially delinquent on a loan; at the point of delinquency, the platform may start charging additional fees to the lender. Some platforms have methods to deal with credit losses, which could be in the form of insurance or guarantee/provision funds that provide partial or full coverage of the loan portfolio.
Should lenders wish to exit their loan investments, some jurisdictions allow those creditors to do so by paying fees to the platform and on the condition that other lenders will take over those loans.
The notary model involves a partnership agreement between a fronting bank and the lending platform because the former actually originates the loans. The loans are then sold or assigned by the fronting bank directly to interested lenders or through a platform subsidiary (securitization) to institutional investors.
With the guaranteed return model, the lending platform guarantees the principal and/or interest on the loans.
The balance sheet model involves the lending platform operating much the same way as a non-bank lender; it requires capital (i.e., debt, equity, securitization) to originate loans but it also retains the loan receivables as assets.
Invoice trading platforms providing recourse factoring have become popular because they include perks such as automatic invoice processing, less delay between invoice processing and cash payment, and a lower level of business activity required.
Microfinancial benefits include: Lower financing costs for borrowers, in theory, through the extensive use of
computerization and automation. Although there seems to be a wide dispersion of interest rates.
Higher returns for lenders, in theory, because quantifying the benefit is difficult. User convenience due to the computerized environment and the very streamlined
process that may lead to extremely timely loan offers.
Assisting existing borrowers by offering additional financing when needed (i.e., invoice trading platforms), addressing the needs of forgotten borrowers such as self-employed individuals and small business owners, and reaching out to new borrowers in emerging market economies.
Microfinancial risks include: A few platforms take on leverage risk in that they use internal resources to fund loans or provide return guarantees. Some platforms are now providing investors with the ability to withdraw amounts early; there is the risk that investors may expect liquidity even though it is clearly stated that it is not guaranteed.
Operational risks such as cyber risks given the extensive use of electronic data, service

disruption risks relating to an external provider of data storage, and fraud risk (i.e., money laundering, Ponzi schemes). Potentially lower credit risk assessment quality. Many FinTech platforms likely do not have detailed borrower information such as income, assets, and liabilities, and some FinTech platforms use exclusively hard data sources and do not consider soft credit risk factors.
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Inappropriate business model incentives that may cause more loans to be granted or more high-risk loans to be granted to maximize fees earned.
Difficulty in attracting new investors for consumer loans if investor confidence in the
platforms is low due to reasons such as low returns, higher default rates, and inability to withdraw investments early.
Low barriers to entry reduce the opportunities for any individual platform to be

profitable. In addition, there is always the threat of traditional banks beginning to aggressively compete with the online platforms. Platforms have generally incurred consistent losses each year, which calls into question whether they can continue to operate in the long-term. The result may be that platforms will have to alter their operations by originating and funding their own loans, providing loan guarantees, or using leverage, for example. In such cases, the platforms may become inherently more risky.
LO 78.3 With the potential growth of FinTech credit, some of the benefits include:
Lowering transaction costs.
Introducing greater financial inclusion.
Incentivizing traditional banks to compete more directly by innovating and/or operating more efficiently. Providing newer and a greater variety of lending options.
Reducing the level of credit concentrated in the banking sector.
Serving as a source of credit should the economy be subject to a major liquidity shock. They are also minimally impacted by international shocks.
At the same time, some of the risks include: The increased competition may significantly cut traditional banks revenue and profits,
which may force them to take on more risk to compensate and ultimately lead to weaker lending standards.
Banks may be taking on incremental operational and reputational risk by working with FinTech platforms, using electronic credit models, and outsourcing IT to third-parties.
The growth of FinTech may also promote procyclical credit provisions.
Should there be a reduction in FinTech lending, because FinTech credit tends to be very concentrated within domestic markets, it would likely be challenging to find replacement credit on a timely basis.
The nature of FinTech credit would make it more difficult for regulators to properly
monitor activities. The lack of regulation means that government policy actions related to strengthening the credit industry during an economic downturn would not be effective or public safety measures such as emergency liquidity would not be available.
With securitization, the dependency between FinTech and the rest of the financial
markets increases, thereby reducing FinTechs protection from risks faced in the general financial markets (and vice versa).
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Co n c e pt Ch e c k e r s
1.
2.
3.
4.
3.
For FinTech platforms, the extent to which the underlying financial activity may be standardized is most likely limited by which of the following factors? A. Legal framework. B. High upfront costs. C. Customer reluctance. D. Potential competition from banks.
Which of the following FinTech credit platforms is characterized by matching borrowers with lenders with the loan being originated by a partnering bank? A. Notary model. B. Balance sheet model. C. Guaranteed return model. D. Traditional P2P lending model.
In which country is the notary model least likely to be utilized by FinTech lending platforms? A. Korea. B. Canada. C. Germany. D. United States.
Compared to traditional banks, FinTech credit platforms are likely more vulnerable to which of the following risks? A. Fraud risk. B. Cyber risk. C. Liquidity risk. D. Third-party service provider risk.
For an economy with a well-developed credit market, which of the following points is a benefit resulting from the growth of FinTech credit platforms? A. Greater access to credit. B. Procyclical credit provision. C. Diversify sources of funding. D. Greater concentration of credit in one sector.
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Co n c e pt Ch e c k e r An s w e r s
1. A Examples of standardized activities include digital identification and standardized electronic contracts. The extent of standardization within a jurisdiction is primarily limited by the legal framework.
FinTech platforms typically have low upfront costs. The nature of FinTech and its digital innovations is more likely to result in customer acceptance of standardization. Potential competition from banks is not a relevant factor in determining the extent of standardization.
2. A The notary model is similar to the traditional P2P lending model in that it matches
borrowers with lenders but it requires a fronting bank to originate the loan.
3. B The notary model is the most commonly used model in Germany and Korea and it is also
common in the United States.
4. B Given that FinTech credit platforms generally rely more on new electronic processes
compared to traditional banks, the electronic processes are generally more vulnerable to cyber risk.
Fraud risk, liquidity risk, and third-party service provider risks are common to both FinTech credit platforms and traditional banks. The exposure to such risks depends on the nature of activities undertaken by each.
5. C
In diversifying the sources of funding, more alternative funding options are made available to borrowers. Some of those options may be more tailored to borrowers specific needs.
In a well-developed credit market, greater access to capital may lead to a potential decrease in lending standards. Procyclical credit provision is a risk resulting from the growth of FinTech; it manifests itself in excess credit provided in a market upturn and a deficiency in credit (when it is needed most) in a market downturn. The growth of FinTech credit platforms allows a lower concentration of credit in the banking sector, which could be beneficial if the banking sector is subject to unsystematic risk.
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The following is a review of the Current Issues in Financial Markets principles designed to address the learning objectives set forth by GARP. This topic is also covered in:
Th e G o r d o n G e k k o Ef f e c t : Th e Ro l e o f Cu l t u r e i n t h e Fi n a n c i a l In d u s t r y
Topic 79
Ex a m Fo c u s
In this topic, we describe corporate culture and the role it plays in financial malfeasance and misdeeds, drawing on an analogy to the movie Wall Street and the Gordon Gekko character played by Michael Douglas. This topic is descriptive, explaining both the role culture has played in the downfalls of several firms, as well as measures society (and regulators) should take to identify and change corporate cultures. It is not as simple as corporate culture alone though, as the environment also influences human behavior. Both corporate culture and the environment can lead to excessive risk taking and, at the extreme, fraudulent behavior. For the exam, know how culture is influenced not only from top managers, but also from the types of workers who are hired (i.e., top down versus bottom up). Also, understand how culture can lead to excessive risk taking. In addition, be able to describe the way culture influenced outcomes for firms such as Lehman Brothers and AIG. The financial crisis of 20072009 shined a light on corporate culture as firms such as Lehman Brothers failed, due in part to a corporate culture that would not acknowledge failings either to outsiders or to those inside the firm who might have objected.
In f l u e n c in g C o r po r a t e C u l t u r e

## LO 78.2: Analyze the functioning of FinTech credit markets and activities, and

LO 78.2: Analyze the functioning of FinTech credit markets and activities, and assess the potential microfinancial benefits and risks of these activities.
P2P lending platforms establish an online presence whereby borrowers and lenders may interact directly with each other as shown in Figure 1.
Figure 1: Traditional P2P Lending Model
Source: Graph 2: Stylized Traditional P2P Lending Model. Reprinted from FinTech Credit: Market Structure, Business Models and Financial Stability Implications, BISCommittee on Global Financial Systems, May 2017, 11. The potential borrower makes an initial loan application on the online platform by providing the required information, which is reviewed and approved by the platform. From there, only the approved applications will go into the pool from which potential lenders may select the loan(s) they want. At that point, the loan contracts are established directly between the borrower and lender. From the borrower and/or lender, the platform operator takes fees such as for loan setup or loan repayments.
Loan selection occurs using criteria such as loan purpose, borrower industry, and borrower income. Loans will be established if they fall within the acceptable time period stated by the borrower.
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The platforms provide an overall credit rating or score that could be determined internally or obtained from a third-party. For an internal assessment, the process is proprietary but likely considers newer and less common kinds of data (i.e., online spending habits) together with more sophisticated methods of analysis.
Lenders are usually advised by platforms to lend to more than one borrower to adequately diversify their investment. In certain instances, there may be an automatic selection process for the loans based on predetermined criteria set by the lender, such as loan amount or credit score. If enough loans are selected by one lender, the result is a pooling of loans similar to a securitization scheme.
There are three basic methods in establishing loan interest ratesin general, borrowers establish the maximum rate and lenders establish the minimum rate. The platform operator uses the information together with the loan amounts to match borrowers and lenders.
Potential lenders make interest rate bids on loans within a range (i.e., minimum stated Potential lenders make interest rate bids on loans within a range (i.e., minimum stated by platform operator based on risk assessment and maximum stated by borrower).
The platforms provide the rate consistent with the credit risk assessment for the loan
(that may be flexible depending on supply and demand).
Borrowers are given a representative rate for an online loan based on a risk assessment
and can seek out appropriate lending alternatives based on the rate.
The majority of platforms allow for partial or full prepayment of loans on a penalty- free basis. On the assumption that payments are made as scheduled, there is no further monitoring of the loan and the borrowers could use the funds for any purpose.
In contrast, should a borrower be potentially delinquent on a loan, they should contact the platform as soon as possible to avoid the platforms contacting debt collection agencies to begin the loan recovery process. At the point of delinquency, the platform may start charging additional fees to the lender. Some platforms have methods to deal with credit losses, which could be in the form of insurance or guarantee/provision funds that provide partial or full coverage of the loan portfolio (i.e., there could be exclusions for higher credit risks). As for the percentage of loss covered, there is a wide range from 2.5% to 70% of the principal amount. An alternative method has the objective to pay out, at a minimum, the expected lifetime default rate for covered loans.
Should lenders wish to exit their loan investments, some jurisdictions allow those creditors to do so by paying fees to the platform and on the condition that other lenders will take over those loans. There also may be no exit guarantee if there are an excessive number of exit requests on the platform at the same time.
Notary Model
The notary model is used frequently in Germany, Korea, and the United States. There is a partnership agreement between a fronting bank and the lending platform because the fronting bank actually originates the loans. The loans are then sold or assigned by the fronting bank directly to interested lenders or through a platform subsidiary (securitization) to institutional investors. The following diagram presents the basic model; some differences exist in its application in some jurisdictions.
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Figure 2: Notary Model
Source: Graph 3: Stylized Notary Model. Reprinted from FinTech Credit: Market Structure, Business Models and Financial Stability Implications, BISCommittee on Global Financial Systems, May 2017, 13. This is the approach used in Germany because only authorized institutions (i.e., not lending platforms) are permitted to provide loans.
In Korea, there is no lending by the lending platform and it is all done by a separate subsidiary that sets up the loans using the funds provided by lenders to the lending platform. Alternatively, a fronting bank is used to set up the loans; the platform transfers the funds to the bank in the form of collateral.
In the United States, regulatory restrictions sometimes cause FinTech lenders to work with a lending institution. The lending institution issues the loans to borrowers from the lending platform. The lending institution may either retain the loans or hold them for a very short period of time and then sell them to the platform lender. The platform lender may then either hold the loans or sell them directly to investors.
Guaranteed Return Model
With the guaranteed return model, the lending platform guarantees the principal and/or interest on the loans.
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Borrowers
i \ Optional online-to-offline structure /
i
(cid:31) ———–4-
funds invested
repayment
Lenders
Source: Graph 4: Stylized Guaranteed Return M odel. Reprinted from FinTech Credit: Market Structure, Business Models and Financial Stability Implications, BISCommittee on Global Financial Systems, May 2017, 14. Historically, this model has been used notably in China and Sweden. In China, some platforms guaranteed the principal amounts on the condition that the lenders held an extremely diversified loan portfolio. Another platform simply provided a 12% return on investment. However, recent regulatory changes now prohibit online lenders from offering such guarantees. In Sweden, a 12% return was guaranteed by one online platform to investors together with very few access restrictions; ultimately, the platform was forced by regulators to cease operations due to findings of misconduct.
Balance Sheet Model
The balance sheet model involves the lending platform operating much the same way as a non-bank lender; it requires capital (i.e., debt, equity, securitization) to originate loans but it also retains the loan receivables as assets.
Figure 4: Balance Sheet Model
i Optional securitization structure
\
Institutional
investors
Retail investors
Platform s balance sheet
Lending platform
N/jfq %/ S .
V S N % S 0
s
*
”S
\>
Topic 78 Cross Reference to GARP Assigned Reading – BIS Committee on Global Financial Systems
Figure 3: Guaranteed Return Model
keeps loans
A1
i
i funds i invested 1 assignment b
i of claims ^ J of claims
Lending platform
> -v H y

r L
^ ^ credit risk analysis N
Borrowers
^ provision of funds
repayment
r
Source: Graph 5: Stylized Balance Sheet FinTech Lending Model. Reprinted from FinTech Credit: Market Structure, Business Models and Financial Stability Implications, BISCommittee on Global Financial Systems, May 2017, 15. This model is used extensively in Australia, Canada, and the United States with the United States being the largest in absolute dollars. In China and the United States, some platforms operate as a combination of the traditional P2P and the balance sheet models, or they combine P2P lending platforms with businesses such as wealth management, trading, and insurance.
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Firms often make credit sales and record corresponding receivables (or invoices) on their balance sheets. However, for quicker conversion of those receivables to cash, they will often sell (factor) them at a discount. If the receivables are sold on a non-recourse basis, the discount is larger and the credit risk of the receivables is transferred to the purchaser. On a recourse basis, the discount is smaller and the credit risk of the receivables remains with the seller. Given that non-recourse factoring is riskier, there may be a minimum amount of business activity required. Therefore, recourse factoring seems to be the most common form for start-ups or small businesses.
Invoice trading platforms providing recourse factoring have become popular because they include perks such as automatic invoice processing, less delay between invoice processing and cash payment, and a lower level of business activity required.
Lenders
P2P lending platforms originally began with individuals lending directly to borrowers. There has been an evolution in P2P lending such that institutional investors are funding a substantial portion of personal and business loans, especially in the United States and Canada. In contrast, much of the funding in Europe, the United Kingdom, and Japan is private.
Within institutional funding, securitizations have occurred almost exclusively in the United States with only a small number in the United Kingdom and Australia.
The majority of platform creditor funds are sourced domestically, especially in the Americas and Europe. Cross-border funding at about one-third of the total amount is highest in the Asia-Pacific region (outside China). Individual (non-professional) investors are usually limited to investing amounts ranging from $2,000 to$18,000, depending on the jurisdiction (amounts are generally higher in China and lower in Europe). There are no investment limits for professional or institutional investors.
Borrowers
The two main types of credit are individual loans and business loans, with debt refinancing and consolidation being the most common reasons for individual loans. The typical borrower sought by platforms is a low credit risk. Average individual loan sizes vary from $5,000 to$25,000. In the United States, the average is closer to $25,000 and in China, the average is in excess of$50,000.
Platforms provide business loans to small and medium-sized businesses on both a secured and unsecured basis. It is estimated that about two thirds of business lending is secured, most commonly with real estate. Business lending in the .Americas and Europe is primarily domestic while in the Asia-Pacific region, more of it is international.
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Microfinancial Benefits
Lower Financing Costs for Borrowers
With FinTechs lower costs through the extensive use of computerization and automation (i.e., loan approval, loan pricing) and the absence of physical bricks and mortar operations, the cost savings should theoretically flow through to borrowers in the form of lower interest rates.
Some studies have shown that overall, smaller loans to individuals are priced lower than traditional banks. Other studies have shown very close rates once adjustments for risk are considered. And other studies have shown marginally increased rates for mortgages (secured with real estate) once adjustments for differences in property location and loan attributes are considered.
Loans in certain lending platforms have a very wide dispersion of rates (i.e., 6% to 36% per annum) compared to regular banks, which suggests that lending platforms may be dealing with a more diverse group of borrowers and/or the existence of greater precision in loan pricing using specific risk factors.
Higher Returns for Lenders
Following the same logic for passing on cost savings to borrowers, the effect on lenders would be in the form of higher returns. However, quantifying the benefit is problematic because of the difficulty in finding comparable investments with the same risk features (i.e., duration and liquidity) as FinTech loans.
One study concludes on an average return of 7%, which is 3% higher than the return on a somewhat comparable index of asset-backed securities. A different survey suggests returns between 3% and 10%. Data from one platform shows rates of return ranging from 8% (lowest default probability) to 24% (highest default probability).
User Convenience
With substantial full use of a computerized environment for providing loan information and assessing loan risk, the search costs for borrowers and lenders is significantly reduced. With a very streamlined and easy process, lenders may be able to offer loans to borrowers at an amazing speed (i.e., minutes or hours). That is in direct contrast to traditional banks that typically operate in a less computerized environment with manual processes that ultimately delay the loan approval process.
Accessibility
FinTech could assist existing borrowers by offering additional types of financing when needed. Invoice trading platforms, for example, could be used by small borrowers to access cash quickly instead of paying overdraft interest at a high rate. In that regard, some jurisdictions actively support such lending to promote economic growth. The support is shown through tax benefits provided to FinTech investors.
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Some groups of (potential) borrowers, such as self-employed individuals and small business owners, have historically been unable to qualify for loans from traditional banks. With the introduction for FinTech lending, such forgotten borrowers can finally obtain the small- dollar loans that they require to grow their businesses.
Within emerging market economies, surveys indicate that many individuals have never borrowed from a traditional bank. With the user-friendliness of many lending platforms, FinTech is likely to increase accessibility to credit for a substantial number of users who otherwise would not have access.
Microfinancial Risks
Leverage and Liquidity Risk
The majority of lending platforms function as agents to bring investors together with borrowers. Therefore, such platforms have little or no leverage risk. A few platforms take on leverage risk in that they use internal resources to fund loans or provide return guarantees.
Most lending platforms also take on little or no liquidity risk (investment and loan durations are usually the same and investors must maintain their loan investments until they mature). At the same time, some platforms are now providing investors with the ability to withdraw amounts early. One example of such a platform allows investors to invest in loans and withdraw amounts at any time and at no charge. Although it is explicitly stated that there is no absolute certainty that the withdrawals will be granted, there is the risk that investors may expect liquidity regardless.
Operational Risk
FinTech platforms face cyber risks given their extensive use of electronic data. Such risks are likely to increase with the level of platform sophistication and will decrease with the strength of their procedures in managing confidential client data and strength of their cybersecurity procedures. With regard to data storage, for example, it requires the platforms to outsource that task to an external provider so there is operational risk should there ever be service disruption. Fraud risk exists because the nature of FinTech lending makes money laundering and other forms of misconduct (i.e., Ponzi schemes) a distinct possibility.
Credit Risk Assessment Quality
FinTech platforms make use of big data analytics, which includes some more unusual but relevant data, to supposedly improve credit risk assessment over that of traditional banks. By taking a more focused analytical process and avoiding the pitfalls of outdated IT systems, the credit assessment may be enhanced. To date, it is not possible to conclude with certainty that FinTech platforms have superior credit risk assessment processes.
Three key arguments against higher quality credit risk assessment of FinTech platforms include: (1) platforms likely do not have detailed borrower information such as income, assets, and liabilities, (2) some platforms use solely hard data sources and do not consider soft credit risk factors, and (3) loan default data for unchartered borrower segments may be unreliable or unavailable.
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The use of the agency model where lenders generate fees from creating new loans, but do not bear any credit risks, may promote the wrong incentives and ultimately lead to poorer quality risk assessments. For example, platforms that do not have to absorb any credit losses on defaulted loans would have the incentive to grant as many loans as possible to maximize fees earned. Or if a platform charges fees to borrowers based on risk, there would be the incentive to grant more higher-risk loans to attempt to maximize fees.
At the same time, if platforms earn fees based on servicing loans, then the incentive would be to grant loans that perform (and do not default) in order to maximize fees.
Attracting New Business Based on Investor Confidence
For lending platforms, there is less of a challenge bringing in new borrower business as long as the loan rates are competitively priced or priced below those of traditional banks or if the platform is targeting borrowers that are less of a priority for banks. However, the challenge in bringing in new investors for consumer loans seems to be the greater challenge. Reasons for the reduction in investor confidence of platforms could include one or more of the following: Other asset returns have increased relative to those earned by investing in loans on the
platform.
A greater percentage of FinTech actual loan defaults compared to expected, which could
lead to a loss of confidence in the risk analysis and loan granting processes.
The inability of investors to withdraw their investments early (even though there is no
guarantee that it will be allowed).
The platform is subject to legal action for the improper use of data or for the use of
improper marketing techniques. .Any event that causes a severe disruption to the platforms activities.

Low Barriers to Entry
Due to lack of regulation of the FinTech industry in many jurisdictions, the online nature of the services, and the common data sources used, there have been many new entrants into the industry. That reduces the opportunities for any individual platform to be profitable.
Additionally, there is always the threat that well-established banks could compete aggressively in the industry by establishing their own platforms. Banks would likely have access to more sophisticated resources pertaining to credit analysis and loan pricing.
Platform Profitability Risk
Many large platforms have incurred consistent losses each year, which calls into question whether they can continue to originate new loans into the future. Two arguments to support the continued existence include: (1) the FinTech industry is still in its early stages and requires further expansion to achieve the necessary economies of scale to become profitable, and (2) there is a specific objective to grow and avoid using profits in the short- term.
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However, if losses continue and concerns about maintaining enough investors persist, platforms may have to alter their operations by originating and funding their own loans, providing loan guarantees, or using leverage, for example. In such cases, the platforms may become inherently more risky and must become more skilled in capital and risk management matters in order to survive in the long-term.
G r o w t h o f Fin Te c h C r e d it

## LO 78.1: Describe how FinTech credit markets are likely to develop and how they

LO 78.1: Describe how FinTech credit markets are likely to develop and how they will affect the nature of credit provision and the traditional banking sector.
At present, FinTech credit markets are relatively insignificant compared to conventional markets although FinTech has been developing at a rapid speed in the past few years. In this section, we will examine reasons supporting development (subdivided between supply and demand issues) and potential challenges to development.
Development Due to Supply Reasons (Platforms)
FinTech lenders are likely to go further beyond conventional lenders in their use of technology, specifically digital innovations. Greater automation in the loan granting process as well as the use of non-traditional (but relevant) data may lead to more timely credit decisions, thereby resulting in stronger client service.
The use of an online business model for FinTech platforms typically has small upfront costs and may also result in a high level of standardization (i.e., digital contracts not requiring in- person meetings) that would lead to significant cost savings. Of course, there may be limits to the amount of standardization in a given geographical location due to its corresponding legal constraints and segmentation of credit markets.
1. Mark Carney, The Promise of FinTechSomething New Under the Sun? (speech at the
Deutsche Bundesbank G20 Conference on Digitizing Finance, Financial Inclusion and Financial Literacy, Wiesbaden, Germany, January 25, 2017).
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FinTech lenders may be able to operate in the same way as conventional lenders, yet avoid their large fixed costs (i.e., branch banking system, significant IT infrastructure) as well as regulatory constraints (i.e., capital and liquidity requirements).
Finally, conventional lenders have left some business opportunities open to FinTech lenders, including a reduction or discontinuance in lending in specific markets after the most recent financial crisis (or they have not fully exhausted the lending potential in particular markets). It is possible that tax and regulatory incentives pertaining to untapped markets will open the door to FinTech lenders. Additionally, some of those markets may generate excess profits to lenders for which FinTech lenders would like to earn.
Development Due to Demand Reasons (Borrowers or Lenders)
The fact that many customers are now extremely internet savvy and appreciate the ease and timeliness of online banking is a strong argument for the further development of FinTech credit markets. With many younger customers (e.g., age 35 and under) who have always lived in the digital age, there is a huge opportunity for online lending and borrowing. Additionally, with certain emerging markets that are finally entering the digital age, it opens up further opportunities for FinTech credit.
FinTech has a possible opening in the market resulting from the loss of trust in traditional lenders in the aftermath of their failures to provide credit to borrowers during the financial crisis. Also, a sense of social value-added [i.e., peer-to-peer (P2P) lending] may be associated with FinTech lending compared to the profit objective of traditional lending.
FinTech loans may be appealing to investors who view FinTech lending as investing in an alternative asset class that may provide higher returns and lower risk, the latter of which is achieved through a more diversified investment portfolio.
With the greater desire of lenders to lend online, it may eventually lead to borrowers following suit to borrow online given the increased availability in the marketplace.
Possible Impediments to Development
Traditional banks have been in the online banking world for many years and some customers are satisfied with their existing digital banking services and may not be willing to switch to an unknown digital lender.
Growth may be impeded during an economic downturn. To date, many FinTech lenders have not operated through an entire credit cycle of an upturn and a downturn. Therefore, considerable uncertainty exists as to whether emerging FinTech lenders would survive the downturn.
Regulatory requirements may vary widely depending on location and could severely limit the growth of FinTech in jurisdictions where the licensing requirements are overly onerous or where interest rate limits apply. With the ongoing development of FinTech, the related regulations will change and create significant uncertainty for borrowers (i.e., consumer protection) who may feel nervous about online borrowing as a result.
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There is also the generic concept of reputational risk should some FinTech lenders operate in an unscrupulous manner during a sensitive industry development phase when FinTech lenders are trying to create their presence as an alternative source of funds in the marketplace.
Fin Te c h C r e d it Pl a t f o r m s

## LO 77.4: Describe the implications of a stronger US dollar on financial stability

LO 77.4: Describe the implications of a stronger US dollar on financial stability and the real economy.
While the impact of a stronger dollar has been extensively discussed, the impact on the balance sheet of financial institutions is less well known. With a change in the dollar, both an institutions asset and liability values will change. A weaker dollar will benefit liabilities (make them smaller), while a stronger dollar will negatively impact liabilities (make them larger). To take the simple example of an emerging market company with dollar liabilities but domestic currency assets (we call this a naked currency mismatch), a weaker dollar will erode the value of the liabilities, thereby positively impacting the balance sheet position of the entity, reducing tail risk. This would allow the entity to borrow more in capital markets. Conversely, a stronger dollar increases the value of liabilities, thereby increasing tail risk and negatively impacting the balance sheet and credit borrowing capacity. As a result, a dollar appreciation is often accompanied by a decline in global dollar lending activities.
For global banks that provide both dollar lending (which requires them to borrow dollars) as well as domestic hedging services, an increase in risk on the lending side will reduce their capacity to provide hedging services to domestic institutional clients.
It is important to recognize that the strengthening and weakening of the dollar has opposite impacts in the export and lending markets. A foreign currency appreciation (domestic currency depreciation) is positive for economic activity in the export market, but is negative in the borrowing market as it erodes the strength of the balance sheet.
In t e r n a t io n a l D o l l a r Le n d in g
The dollar lending in international markets reflects changes in the size of balance sheets and is a good proxy for risk appetite and leverage. In response to a dollar appreciation, bank lending in dollars will decline, reducing banks hedging activities to institutional players. This creates a demand-supply imbalance and raises the cost of hedging, and will also result in wider divergences from CIR
When calculating the dollar credit by banks to an international borrower, it is important to look at bank lenders in all international markets, not just U.S. lenders. For example, European banks have historically been one of the largest dollar lenders to Asian borrowers and have played an important role in dollar intermediation. As a result, when assessing the total dollar credit to Asian borrowers, it is important to look at not only U.S. lenders but also European and other international lenders.
Volatility and changes in the dollar have important implications for the stability of financial markets and for the real economy. As banks reduce their intermediation activities in response to rising volatility, they would inadvertently magnify shocks, rather than absorb them. Furthermore, because the dollar now reflects global risk appetite, a strengthening dollar truly has global implications.
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Ke y Co n c e pt s
LO 77.1 A key takeaway in the post financial crisis period is that the link between banks and capital markets is now global.
LO 77.2 External market factors and wholesale creditor sentiment can cause forced deleveraging.
The VIX, which measures implied volatility and is a fear gauge, was a reliable measure of leverage prior to the financial crisis. High VIX implied low leverage, and low VIX implied high leverage.
In the post-crisis period, the VIX lost its predictive ability. Attempted explanations of this change include monetary easing, regulations, and higher bank capitalizations.
Covered interest parity (CIP) is a parity condition that states that the interest rates implied in foreign exchange markets should be consistent with the money market rate for each currency. If CIP does not hold an arbitrage opportunity exists. CIP held up well before the financial crisis but it has not worked well in the post-crisis period, creating a persistent gap between CIP-implied rates and observed rates.
LO 77.3 In the post-crisis years, the U.S. dollar replaced the VIX as a more reliable measure of leverage. During periods of a strong dollar, risk appetite is weak. A period of a strong dollar also implies a wider cross-currency basis, raising the incremental cost of borrowing in dollars. The dollar also effectively prices the CIP deviation.
The fluctuation in the cross-currency basis implies an opportunity cost and could be seen as a pressure of forced deleveraging.
The higher return in recent years of dollar assets increased the demand for dollars. To hedge the volatility of the dollar, international investors hedge any dollar currency risk through banks, which in turn hedge their own risk by borrowing in dollars. The global dollar intermediation will mirror currency hedging demands.
LO 77.4 Changes in the value of the dollar will affect an institutions asset and liability values. A stronger dollar will increase dollar liabilities, thereby increasing tail risk and negatively impacting an institutions balance sheet and credit borrowing capacity. A dollar appreciation is often accompanied by a decline in global dollar lending activities.
In response to a dollar appreciation, banks dollar lending will fall, reducing their hedging activities. This creates a demand-supply imbalance and raises the cost of hedging.
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Given the size of dollar lending by non-U.S. entities, it is important to factor in the dollar lending of all international lenders when calculating the dollar credit by banks to international borrowers.
As banks reduce their intermediation activities in response to rising volatility, they may inadvertently magnify shocks.
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Co n c e pt Ch e c k e r s
A rise in the haircut from 3% to 3% for a security under a repo transaction implies that: A. B. C. D. leverage decreased to 20 times.
leverage increased by 2%. leverage increased to 20 times. leverage decreased by 2%.
Which of the following factors would most likely be associated with a low volatility index (VTX)? A. Low volatility, high leverage. B. Lack of borrowing activity. C. High volatility, low leverage. D. Low lending by global banks.
Which of the following statements regarding covered interest parity (CIP) is not correct? A. If CIP does not hold, market participants could make arbitrage profits. B. The principle of CIP holds that interest rates implied in foreign exchange
markets should be consistent with spot short-term interest rates.
C. For currencies A (domestic) and B (foreign), CIP requires only the spot and forward exchange rates for A and B and the money market interest rate on A. D. CIP states that the forward and spot exchange differential on two currencies
should mimic the ratio of money market interest rates on these currencies.
Which of the following borrowers would likely benefit the most by a weaker dollar? A. Borrowers with dollar assets exceeding dollar liabilities. B. Borrowers with dollar liabilities exceeding dollar assets C. Borrowers with domestic (non-dollar) assets and dollar liabilities. D. Borrowers with dollar assets and domestic (non-dollar) liabilities.
Which of the following factors is most associated with a stronger dollar? A. Stronger balance sheet of dollar borrowers. B. Reduced tail risk in the borrowers credit portfolio. C. Less capacity for credit extension. D. Increased lending by creditors.
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Co n c e pt Ch e c k e r An s w e r s
1. D A rise in the haircut from 3% to 5% implies that entities can only borrow 95 cents on the
dollar, rather than the previous 97 cents. This implies a decline in leverage. Thus, the leverage factor declined from 33 times to 20 times.
2. A Because the VTX is a measure of implied volatility, a low VIX value implies low market
volatility. When volatility is low, leverage tends to high, with a large number of borrowers and lenders transacting in the market.
3. C For currencies A and B, CIP uses the spot and forward exchange rates for A and B and the
money market interest rate on both A and B (not just on A).
The other statements are all correct. If CIP holds, there are no arbitrage opportunities. If CIP doesnt hold, a market participant could make an arbitrage profit by borrowing money at the lower interest rate, lending money at the higher interest rate, and concurrently fully hedging currency risk.
4. C A weaker dollar lowers the value of both dollar liabilities and dollar assets. An entity with domestic (non-dollar) assets and dollar liabilities will benefit most, since the asset value would remain unaffected by the dollar weakening, but the liability value would fall. As a result, the entitys equity would increase.
5. C A stronger dollar increases the dollar liabilities of borrowers, which weakens their balance
sheet. As their balance sheet weakens, their demand for additional borrowing declines, reducing dollar lending activities in the market.
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The following is a review of the Current Issues in Financial Markets principles designed to address the learning objectives set forth by GARP. This topic is also covered in:
Fi n Te c h C r e d i t : M a r k e t St r u c t u r e , Bu s i n e s s M o d e l s a n d Fi n a n c i a l St a b i l i t y Im pl i c a t i o n s
Topic 7 8
Ex a m Fo c u s
FinTech can be defined as technologically enabled financial innovation that could result in new business models, applications, processes or products with an associated material effect on financial markets, financial institutions, and the provision of financial services.1 This purely qualitative topic begins by providing details as to how FinTech credit markets could develop as well as possible impediments. For the exam, focus on the mechanics of the traditional P2P lending model and be able to compare and contrast it with other models. A thorough knowledge of both the micro and macro benefits and risks of FinTech credit markets is key to this topic.
Fin Te c h C r e d it M a r k e t s

## LO 77.3: Discuss the US dollars role as the measure of the appetite for leverage.

LO 77.3: Discuss the US dollars role as the measure of the appetite for leverage.
We already noted that the VIX is no longer a reliable gauge of leverage. In recent years, the U.S. dollar emerged as a viable alternative to the VIX. During periods with a weak dollar, risk appetite tends to be strong. With a strong dollar, risk appetite is weak and market anomalies like the breakdown of CIP occur more frequently. This inverse relationship is readily apparent when comparing the value of the dollar (or of the dollar/euro exchange rate) against the cross-currency basis of a basket of advanced economy currencies over the last few years. As the dollar appreciated, the cross-currency basis widened. The relationship is particularly true since 2014, which marked the beginning of a strong dollar appreciation. The wider basis can be seen as an incremental cost of borrowing in dollars (i.e., wider basis, higher cost).
Any deviation from CIP can be interpreted as the price that banks place on leverage. Any gap between the CIP implied rate and actual rate would represent a profit potential for the banks, borrowing at a low rate and lending at a higher rate, while fully hedging currency risk. The fluctuation in the cross-currency basis in effect implies an opportunity cost (money left on the table) for banks and could be seen as a pressure of forced deleveraging.
What is clear is that following the financial crisis, the dollar has replaced the VIX as the reliable measure of the price of bank balance sheet and leverage. The dollar now functions as a risk factor that effectively prices the CIP deviation.
Why is the Dollar a Good Measure of Leverage?
In recent years, interest rates have fallen considerably around many parts of the world. U.S. assets, however, have remained above many advanced economy asset returns. As a result, investors have increased their demand for higher yielding assets denominated in U.S. dollars. However, this creates a currency mismatch and risk for institutional investors who hold dollar investments but have commitments to domestic stakeholders. For example, a German life insurance company has domestic currency (euro) obligations to its policyholders and beneficiaries. If the life insurance company has an investment portfolio denominated in dollars, it is exposed to volatility in the value of the dollar, and will therefore hedge any dollar currency risk. Hedging is typically done through a local bank that provides hedging services. The bank will also want to hedge its own currency risk by borrowing in dollars. As a result, the global dollar intermediation will mirror currency hedging demands.
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Th e Im pa c t o f D o l l a r St r e n g t h e n in g

## LO 77.2: Explain the effects of forced deleveraging and the failure of covered

LO 77.2: Explain the effects of forced deleveraging and the failure of covered interest rate parity.
Effects of Forced Deleveraging
Forced deleveraging refers to the reduction in leverage by a borrower following capital market events that necessitate deleveraging. A good gauge of leverage is the haircut in the repurchase agreement (repo) market. The haircut refers to the difference between the value of the collateral pledged and the amount borrowed. For example, a 2% haircut implies that a bank is able to borrow $98 dollars for every$100 in securities pledged. The lower
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the haircut, the higher the leverage implied in the transaction. The 2% haircut implies a leverage factor (or leverage ratio) of 50 for the bank (computed as total assets over equity).
Prior to the financial crisis of 20072009, leverage factors of 50 were not uncommon, with corresponding very low haircut values. However, such high leverage left many banks exposed to potential forced deleveraging. Indeed, in the period immediately following the financial crisis, the leverage factor dropped to around 25 in the U.S. securities broker-dealer sector, with the haircut increasing from 2% to 4%. In general, such a large change has material consequences. Assuming a banks equity isnt impacted, the bank would have to cut its assets in half. If the bank also suffers losses, the impact is even worse.
VIX as a Gauge of Leverage
Up until the onset of the financial crisis, the volatility index (VIX) represented a good gauge of the appetite for leverage in the markets. The VIX measures implied volatility from stock option (call and put) prices. Prior to the financial crisis, a low VIX implied low fear and therefore high leverage. The VIX was able to adequately capture the risk appetite within the financial system. Given that banks typically borrow in order to lend funds, easy conditions for borrowing also created easy conditions for lending, creating a circular series of events that led to ever easier borrowing and liquidity as well as higher leverage.
However, the VIX as a reliable gauge of leverage shifted dramatically following the financial crisis. The previous relationships of high VIX-low leverage / low VIX-high leverage ceased to hold and the VIX lost its explanatory power of leverage. While there remains considerable risk appetite for stocks, as witnessed by high stock valuations and low volatility, the banking sector has not fared comparatively well, with low market-to-book value ratios.
So what has changed? One explanation is that monetary easing has calmed markets and compressed credit spreads, although this explanation generally holds best when policy rates are positive. Another explanation could be the role of regulation, which impacts bank behavior and may constrain leverage. A counterargument to the role of regulation is that the financial crisis was not brought on by regulatory change (although regulatory change certainly followed in the post-crisis period). Capitalization also plays a role in the financial health of the banking sector. Better capitalized banks weathered the crisis better and have fared well compared to their weaker capitalized counterparts.
Failure of Covered Interest Arbitrage
Covered interest parity (CIP) is a parity condition that states that the interest rates implied in foreign exchange markets should be consistent with the money market rate for each currency. In other words, the interest rate implied between the forward and spot rates on a U.S. dollar forward or swap (one side borrows U.S. dollars and lends another currency) should be the same as the money market interest on the dollar. If the relationship does not hold, an arbitrage opportunity would exist for earning a profit on borrowing cheap in one currency, lending out funds at a higher rate in another currency, and concurrently fully hedging currency risk.
CIP held up reasonably well before the financial crisis. However, the relationship no longer worked well in the post-crisis period, and a gap between CIP-implied rates and observed
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rates has persisted. The primary reason for the difference is that CIP is a theoretical concept based on certain simplifying assumptions, including the ability to take on any position in any currency at prevailing market prices. In reality, borrowers and lenders need to transact through banks, which may not have sufficient capital to enter into these transactions or may find the spreads to be uneconomical. Capital may be insufficient partly due to regulation, although banks typically have capital well above regulatory requirements.
U.S. D o l l a r a s a Ga u g e o f Le v e r a g e