數位金融創新實驗室

How AI Boosts Fintech: 7 Promising AI-Powered Industries To Follow

發表人  研究員    發表日期  2023-11-02    點閱次數  652


When Willie Sutton, once one of America’s most wanted fugitives, was asked why he robbed banks, his response was remarkably simple, “Because that’s where the money is.”

This is the same answer that could be given to those who inquire about the growing tendency towards regulation in the fintech sector, and who believe that increasing legislation could damage innovation in the field. That’s where the money is, therefore, the stakes are high, and more regulation will be there. This will most likely happen sooner than later, as Michael Hsu, Acting Comptroller of the Currency, said recently. Therefore, we can expect compliance to be at the forefront of the conversation, and to become a priority for venture capitalists, CFOs, and other stakeholders alike.



全文來源:https://www.unite.ai/how-ai-boosts-fintech-7-promising-ai-powered-industries-to-follow/




https://fintechmagazine.com/banking/top-10-digital-banks-of-2022

發表人  研究員    發表日期  2023-10-20    點閱次數  1179

FinTech Magazine runs through our Top 10 most ethical banks of 2023


FinTech Magazine takes a look at the Top 10 most ethical banks of 2023, looking at the ESG initiatives they employ to put them in our Top 10 list

Economic social governance (ESG) is becoming one of the most important considerations for financial institutions and banks alike. 

Below, FinTech Magazine runs through our Top 10 most ethical banks of 2023. 


全文來源:https://fintechmagazine.com/articles/top-10-banks-for-esg-in-2023





THOUGHT LEADERSBuilding Trust in AI with ID Verification

發表人  研究員    發表日期  2023-10-01    點閱次數  954

Generative AI has captured interest across businesses globally. In fact, 60% of organizations with reported AI adoption are now using generative AI. Today’s leaders are racing to determine how to incorporate AI tools into their tech stacks to remain competitive and relevant – and AI developers are creating more tools than ever before. But, with rapid adoption and the nature of the technology, many security and ethical concerns are not fully being considered as businesses rush to incorporate the latest and greatest technology. As a result, trust is waning.


全文來源:https://www.unite.ai/building-trust-in-ai-with-id-verification/



Top 10 fintech startups based in the US 2023

發表人  研究員    發表日期  2023-09-28    點閱次數  1322

Startups are a strength to any economy, bringing new skills and ideas to industries like fintech.



e have collated a list of the Top 10 fintech startups based in the US, limited to firms who are Series A stage or earlier and ordered by amount raised

The US startup scene has ridden recent economic volatility, geopolitical instability, a downturn in the fundraising environment and even a global pandemic to be where it is today – so the early-stage and growth-stage fintechs who are still thriving deserve all the more credit for where they find themselves today.



全文來源:

https://fintechmagazine.com/top10/top-10-fintech-startups-based-in-the-us-2023



Top 10 open banking platform providers in fintech 2023

發表人  研究員    發表日期  2023-08-11    點閱次數  1074

Open banking has made a new generation of financial tools and use cases possible.https://fintechmagazine.com/articles/top-10-open-banking-platform-providers-in-fintech-2023

These are some of the most influential companies creating technology solutions and APIs to help power the open banking revolution evident in fintech today


全文來源:https://fintechmagazine.com/articles/top-10-open-banking-platform-providers-in-fintech-2023



140+ Blockchain and Crypto Words: The Ultimate A-Z Glossary

發表人  研究員    發表日期  2023-07-12    點閱次數  1295

The most comprehensive dictionary online of blockchain and cryptocurrency-related buzzwords, from HODL to NFT, these are the terms you need to know


全文來源:https://fintechmagazine.com/financial-services-finserv/140-blockchain-and-crypto-words-ultimate-z-glossary




AI in Finance? Use Cases, Benefits, and Challenges

發表人  研究員    發表日期  2023-07-01    點閱次數  646

AI-in-finance

AI in finance? If you’re unfamiliar with this combination, chances are you are missing out on a lot. The main goals of financial institutions  – banks, hedge funds, and insurance companies – are minimizing risks, reducing costs, and providing high-end customer services to clients using AI.


全文來源:https://www.unite.ai/ai-in-finance-use-cases-benefits-and-challenges/



A model-based assessment of the macroeconomic impact of the ECB’s monetary policy tightening since December 2021

發表人  研究員    發表日期  2023-05-23    點閱次數  2537


The monetary policy normalisation that started in December 2021 has taken the ECB’s policy stance from a highly accommodative position into restrictive territory.
 

In December 2021 the ECB announced that it would begin normalising its policy stance by slowing the pace of net asset purchases, with net purchases under the pandemic emergency purchase programme (PEPP) and the asset purchase programme (APP) eventually ending in March 2022 and June 2022 respectively.
[1] The ECB’s interest rate guidance was revised in June 2022, and its key policy rates were increased by a total of 350 basis points between July 2022 and March 2023, rapidly tightening policy and ultimately taking rates into restrictive territory. While the speed and magnitude of this tightening is high from a historical perspective, monetary policy is transmitted to the economy with lags, implying that the full impact of the tightening will unfold over the next few years. This box uses a variety of empirical macroeconomic modelling frameworks to illustrate the impact on economic activity and inflation in the euro area.


Uncertainty about the impact of monetary policy on the economy can be addressed by drawing on a suite of models. This box presents details of a stylised exercise analysing the impact of policy tightening so far and illustrates the analytical challenges that surround such an assessment. There are two main challenges in assessing the impact of policy tightening. First, financial and macroeconomic variables are driven by a host of factors on both the demand side and the supply side. These factors need to be disentangled from the impact of monetary policy itself, calling for a model-based identification approach. And second, there is uncertainty regarding the transmission channels and lags of monetary policy, and it is therefore necessary to consider alternative methodologies with different transmission mechanisms in the interests of robustness. For these reasons, this assessment uses a suite of models: two structural DSGE models (NAWM II and MMR) and one large‑scale semi‑structural model (ECB-BASE).[2] This approach is in line with the conclusions of the ECB’s recent monetary policy strategy review, which emphasised the importance of robustness in carrying out model-based analyses within the Eurosystem.[3]

The assessment is carried out in two steps: first, by estimating the impact that monetary policy has on the yield curve, and second, by translating the impact on the yield curve into macroeconomic effects using macro models. The first step is to identify monetary policy-induced changes in short and long-term interest rates. The impact on short-term rates is calibrated on the basis of the upward shift observed in the forward curve for the euro short-term rate (€STR) at short to medium maturities since December 2021, which reflects both actual increases in policy rates and the anticipation of future increases. The impact on long-term rates is derived from the upward pressure on yields that is exerted by revisions to expected APP and PEPP holdings. In a second step, the policy-related effects on interest rates and the Eurosystem’s balance sheet are translated into macroeconomic effects using the suite of macro models, either directly or indirectly via the impact that balance sheet expectations have on long‑term rates.[4] In the DSGE models, the conditioning on the short-term interest rate is done through monetary policy shocks, which are partially anticipated in MMR and unexpected in NAWM II. In the ECB‑BASE model, short and long-term interest rates are assumed to be exogenous and the counterfactual is imposed as an alternative path relative to the baseline (i.e. the interest rate path expected in December 2021). In practice, market-based The results show that the policy tightening can be expected to exert substantial downward pressure on real activity and inflation over the period 2023-25. Since December 2021, short-term interest rates have increased by around 270 basis points on average over the projection horizon 2022‑25. Expectations for long-term interest rates, which account for anticipation, have increased by around 230 basis points over the same horizon (a significant percentage of which can be attributed to changes in APP and PEPP expectations, as Table A shows).[5] Short-term interest rate expectations began shifting upwards even before the first policy rate increase in July 2022 (Chart A), which shows the importance of accounting for policy expectations. The associated upward shift in the yield curve has an effect, in turn, on broader financing conditions and exerts a tangible impact on the economy. Averaging results across the three models, this assessment suggests that policy normalisation has exerted significant downward pressure on inflation and real GDP growth across the whole of the projection horizon (Chart B). Most of the impact on inflation is expected to be seen in the period from 2023 onward, with that impact peaking in 2024. The tightening of policy is estimated to have lowered inflation by around 50 basis points in 2022, while the downward impact on inflation is expected to average around 2 percentage points over the period 2023-25, with estimates differing substantially across the three models. The transmission to economic activity is faster, with the impact on GDP growth expected to peak in 2023 and a downward impact of 2 percentage points on average over the period 2022-25.[6] [7]financial assumptions also change as an endogenous reaction to other drivers, such as energy prices. In order to compute the impact of monetary policy, this exercise quantifies the macroeconomic impact of policy had it not followed the historical regularities captured by market‑based financial assumptions. This counterfactual is computed using policy shocks. Sensitivity to these assumptions is explored in more detail later in the box, particularly as regards the role of the expectation formation process.

Sources: Bloomberg, Refinitiv and ECB calculations.
Notes: The impact on short-term interest rates is calculated as the average difference between the short-term interest rates expected in the December 2021 and March 2023 MPE projections. The short-term interest rate curve is based on monetary policy-dated €STR forward contracts. The impact on ten-year yields is computed on the basis of changes to balance sheet expectations in the Survey of Monetary Analysts. The estimated impact on ten-year yields in the period from October 2021 (in order to account for anticipation) to May 2023 is around 65 basis points, while the average impact on expected ten-year yields over the period from 2022 to 2025 is 55 basis points. The impact is computed as the average across two models: a term-structure model (see Eser et al., op. cit.) and a BVAR model (see Rostagno et al., op. cit.).

Chart A

Impact on the monetary policy-dated €STR forward curve

(percentages per annum)

Sources: Bloomberg and ECB calculations.
Notes: This chart shows, for each Governing Council monetary policy meeting with updated economic projections, the €STR forward curve on the first available day of the maintenance period that follows the meeting. The purple line represents realised values for the deposit facility rate (DFR), with data being adjusted for the DFR space by applying a spread of 8 basis points. The cut-off dates for the data used for the various lines are based on the following final cut-off dates for projections: 23 November 2021 (December 2021), 28 February 2022 (March 2022), 17 May 2022 (June 2022), 22 August 2022 (September 2022), 25 November 2022 (December 2022) and 15 February 2023 (March 2023).


Source: ECB calculations based on the NAWM II model (see Coenen et al., op. cit.), the MMR model (see Mazelis et al., op. cit.) and the ECB-BASE model (see Angelini et al., op. cit.).
Notes: This chart reports the results of a simulation involving changes to short-term rate expectations between December 2021 and March 2023 and changes to expectations regarding the ECB’s balance sheet between October 2021 and May 2023. The reported values refer to year-on-year growth rates. “Mean” denotes the average across the three models.


The impact estimates are surrounded by significant uncertainty, reflecting differences in transmission channels across models, with the structural models displaying a stronger impact. The structural models are specifically designed for the purpose of deriving conditional correlations between identified monetary policy impulses and macroeconomic aggregates, while semi-structural models seek to achieve a satisfactory combination of identification and empirical fit. This can result in monetary policy tightening having a more limited impact, as the estimated impact based on such models probably conflates the effect of a “pure” monetary policy impulse with that of other non-policy drivers. In practice, there is a trade-off between the scale of the model and the number of drivers that can be identified, as abstracting from many of the cross-equation restrictions required for full structural identification allows a richer model structure (e.g. as regards consumption). In the DSGE models used for the simulations, consumption is closely linked to expected future short-term rates via the Euler equation. On the other hand, the richer modelling of consumption in the ECB-BASE model includes individual income risk and differing propensities to consume out of different income sources.[8] This implies that the dynamics of consumption are less dependent on expected short-term interest rates but better capture the observed persistence in consumption.

The larger impact of monetary policy in structural models also reflects stronger expectation channels. In particular, while structural models are forward‑looking, semi-structural models typically involve more backward-looking expectations, resulting in slower propagation of shocks.[9] Similarly, in DSGE models, an endogenous fall in inflation expectations in response to a rate rise leads to a further increase in real rates, thereby creating a reinforcing loop – a channel that is not present in semi-structural models, as these do not directly incorporate expectations of future inflation. This role played by expectations can be illustrated using sensitivity analysis. If it is assumed that agents do not anticipate policy decisions, the impact that the normalisation of policy has on inflation is halved in the MMR model (pale red bars in Chart C), bringing its estimates closer to those derived from the ECB-BASE model. Likewise, in the case of the NAWM II model, if the forward-looking expectations mechanism is modified to incorporate an adaptive learning scheme that makes households and firms’ expectations more backward‑looking, the impact that monetary policy has on inflation is mitigated (pale yellow bars in Chart C). Conversely, using more reactive expectations and strengthening the impact that asset prices have on the valuation of wealth in the ECB-BASE model (pale blue bars in Chart C) brings its responses closer to those produced by the two DSGE models under a tempered expectations channel.[10]

Source: ECB calculations based on the NAWM II, MMR and ECB-BASE models.
Notes: The reported values refer to year-on-year growth rates. “Mean” denotes the average across all three models using the standard expectations channel in each model, and is therefore equivalent to the mean in Chart B.

This model-based assessment can serve as a useful cross-check, but is no substitute for a data-dependent approach to the setting of policy and the monitoring of transmission over time. First, the current situation is characterised by exceptionally high levels of uncertainty about economic relations. The pandemic, the large energy shock, the fiscal responses to those two events and the unprecedented pace of the tightening of monetary policy are all likely to affect economic decisions and structures in ways that go beyond the historical regularities captured by available models. This uncertainty is compounded by the fact that macroeconomic outcomes reflect shocks from many different sources beyond monetary policy, and those shocks will propagate differently across the various models. Second, these estimates do not capture the prevention of any adverse non‑linear dynamics that might have materialised in the absence of monetary policy tightening, such as a risk of destabilising inflation expectations. Finally, the results point to considerable lags in the transmission of monetary policy to the economy. For all those reasons, while this model-based assessment can serve as a complementary cross-check, it is necessary to monitor indicators such as financial and credit variables, as well as leading indicators of activity and prices, to establish a timely and comprehensive medium-term inflation outlook.

  1. Furthermore, in December 2022 the ECB announced its intention to reduce the size of the APP portfolio by not reinvesting some of the principal payments from maturing securities. The APP portfolio will decline by €15 billion per month on average until the end of June 2023, and the Governing Council expects to discontinue all reinvestments thereafter.

  2. For details of the NAWM II model, see Coenen, G., Karadi, P., Schmidt, S. and Warne, A., “The New Area-Wide Model II: an extended version of the ECB’s micro-founded model for forecasting and policy analysis with a financial sector”, Working Paper Series, No 2200, ECB, November 2018 (revised December 2019); for information on the MMR model, see Mazelis, F., Motto, R. and Ristiniemi, A., “Monetary policy strategies for the euro area: optimal rules in the presence of the ELB”, Working Paper Series, No 2797, ECB, March 2023; for details of the ECB-BASE model, see Angelini, E., Bokan, N., Christoffel, K., Ciccarelli, M. and Zimic, S., “Introducing ECB-BASE: The blueprint of the new ECB semi-structural model for the euro area”, Working Paper Series, No 2315, ECB, September 2019. NAWM II is a fully micro-founded small open economy model with (i) an explicit intertemporal substitution channel, (ii) a banking sector with a financial accelerator mechanism, (iii) central bank asset purchases, (iv) interest rate-sensitive investment decisions and (v) a foreign economy block allowing for international spillovers. The MMR model is a closed economy DSGE model with (i) optimising households and firms, (ii) central bank asset purchases and (iii) a time-varying neutral interest rate. It also estimates the degree of attention to central bank communication, thereby helping to address the forward guidance puzzle encountered in standard DSGE models. ECB-BASE is a large semi-structural model designed to combine theoretical considerations with a good empirical fit and a comprehensive structure, reflecting its role as a workhorse model in the context of projections and policy simulations at the ECB. Its monetary policy transmission mechanism is stronger than in standard semi‑structural models, thanks to the explicit (VAR-based) role played by expectations and a multitude of financial channels.

  3. See “Review of macroeconomic modelling in the Eurosystem: current practices and scope for improvement”, Occasional Paper Series, No 267, ECB, September 2021.

  4. Both structural models capture asset purchases directly via the inclusion of the central bank’s balance sheet. In the ECB-BASE model, asset purchases are captured indirectly via their effect on long-term rates, so the impact of monetary policy normalisation is computed using both short and long-term interest rates.

  5. The impact that monetary policy has on short-term rates is computed on the basis of the upward shift observed in the forward curve for the €STR over the 2022-25 horizon. As increases in policy rates are typically transmitted one-to-one to the overnight rate, it is assumed that all changes in the €STR forward curve can be attributed to the tightening of policy. For long-term rates, the tightening impact stems from changes in expectations regarding balance sheet reduction. The impact of the latter is computed by mapping changes in balance sheet expectations derived from the Survey of Monetary Analysts into yields using an average across two models: (i) a term-structure model with a quantity variable and duration risk (see Eser, F., Lemke, W., Nyholm, K., Radde, S. and Vladu, A., “Tracing the impact of the ECB’s asset purchase programme on the yield curve”, Working Paper Series, No 2293, ECB, July 2019); and (ii) a large BVAR model where the impact of policy is identified using a dense event study (see Rostagno, M., Altavilla, C., Carboni, G., Lemke, W., Motto, R. and Saint Guilhem, A., “Combining negative rates, forward guidance and asset purchases: identification and impacts of the ECB’s unconventional policies”, Working Paper Series, No 2564, ECB, June 2021). The exchange rate is allowed to move endogenously.

  6. In all models, monetary policy is neutral in the long run. This implies that GDP growth will eventually turn positive after the initial negative impact. This happens earlier with the MMR model, as the exercise is conducted with expected shocks, hence the impact of policy is more frontloaded. This is illustrated in Chart C, which shows that, when shocks are unexpected, the profile of GDP growth is more similar to those of the other models.

  7. The May 2023 median expectations for the ECB’s balance sheet tightening are broadly consistent with the discontinuation of reinvestments under the APP programme as of July 2023. The tightening of balance sheet expectations is expected, on its own, to lower annual inflation by slightly more than 10 basis points in each year over the period 2023-25 and reduce GDP growth by the same amount over the period 2022-25.

  8. In contrast, there are fewer differences between ECB-BASE and the two DSGE models in terms of the modelling of the investment sector, with ECB-BASE featuring a financial accelerator mechanism.

  9. In the ECB-BASE model, expectations are modelled using VARs.

  10. More reactive expectations are obtained by increasing the elasticity of short-term inflation expectations relative to movements in interest rates (whereby greater elasticity is obtained by estimating the underlying VAR used for expectation formation using a different sample and an OLS estimator) and by allowing actual inflation developments to have a stronger effect on the perceived long-term inflation target. The impact that asset prices have on the valuation of wealth is strengthened by endogenising house prices and by increasing the elasticity of the revaluation term in financial wealth relative to movements in returns on financial assets.

全文來源:https://www.ecb.europa.eu/pub/economic-bulletin/focus/2023/html/ecb.ebbox202303_06~b2bdff5cda.en.html



在充滿挑戰的市場中籌集資金的 16 條法則

發表人  研究員    發表日期  2023-05-03    點閱次數  2562

Between inflation, rising interest rates, geopolitical tensions, and growing recession concerns, 2022 was a year of reckoning for both public and private markets. Since the beginning of 2022, the tech-heavy Nasdaq Composite has declined 23% (versus the S&P 500’s 14% decline) and global venture funding reached a thirteen-quarter low in Q1 ’23. Further dampening investor confidence, the failure of several long-standing institutions serving the startup ecosystem, such as Silicon Valley Bank, Signature Bank, and First Republic Bank, sent shockwaves through capital markets and the broader financial services industry. Today’s market represents a radically different fundraising climate—one not seen in nearly 15 years. Many founders find themselves in uncharted territory as concerns linger around the overall health of the fundraising environment, from venture capital to growth equity.

The View from 30,000 Feet: How is the Market Trending?

With seismic changes occurring across the broader capital markets and tech multiples at a multi-year low, we are seeing some key trends emerge in the venture landscape: 

  • The macro environment has impacted investor sentiment. Given the recent political and economic uncertainty, much of private market activity has been put on pause. Despite ample dry powder in the venture space, some investors are not willing to step up to price and set valuation terms, particularly in later-stage funding rounds. 
  • Early stage valuations have been more resilient. According to recent Pitchbook data, growth-stage companies have been more adversely impacted by the recent market correction and current macro environment than early stage companies. This is in part, due to the growth-stage’s proximity to public markets, whereby investors are confronted with a large gap between the valuation multiple that a growth-stage startup raised at in its most recent round versus where its public peers are trading at today. 
  • Up rounds are still happening, but taking longer. Despite challenges in the broader public equity markets, companies with proven traction, a path to profitability, and good unit economics are raising up rounds. However, with continued macro and market uncertainty, investors have become more discerning with longer and more rigorous due diligence, causing rounds to take longer to come together.
  • Flight to structure. In the startup world, it is customary to raise capital through the issuance of preferred equity, and for founders and employees to hold common equity. As deals became more competitive in recent years, investors also purchased common equity in an effort to obtain the maximum amount of ownership in a given financing round. With today’s more volatile and uncertain markets, investors have returned their focus to preferred equity. Increasingly, they are also requiring terms that provide downside protection and minimum return thresholds, such as payment-in-kind (PIK) dividends, liquidation preferences higher than 1x, valuation ratchets, and participating rights. That said, while structure is becoming more commonplace, it is more prevalent in growth rounds than in early stage rounds. For more on this topic, please see this article written by our Growth investment team on the impact of different structures. 
  • In SAFE hands. A SAFE, or Simple Agreement for Future Equity, is a financing structure pioneered by Y Combinator. With a SAFE, a company is able to raise capital without formally assigning a value to the business in exchange for certain protections for the investor upon conversion (typically either a valuation cap, a discount to the next financing round, or both). Historically, SAFEs have been primarily used by companies that are pre-product or pre-launch. In the current climate, we have observed the SAFE structure being utilized by an increasing number of revenue-generating Series A and Series B companies, who need to raise an interim round to get to certain milestones ahead of a more formal priced round. Such companies usually have the internal support to defer an interim valuation event. 
  • Convertible notes have taken off. Convertible notes are a form of debt that can be converted into equity either at a valuation cap or at a discount (typically 20-30%) to a company’s next financing round just like a SAFE. However, unlike SAFEs, convertible notes offer downside protection given the asset class of debt, as well as potential minimum-guaranteed thresholds. They also incur interest (that can convert into equity in the next priced round) and have a predetermined maturity date which creates a ticking clock for the company to raise future financing and repay its debt. In this current climate, we are observing a number of companies raise convertible notes as well as the emergence of creative new structures such as pre-IPO convertible debt with a conversion price set at a premium to the company’s eventual IPO price.
  • Recaps are due to make a comeback. When companies looking to raise capital find interest from investors who are not willing to sit behind the company’s existing investors, or preference stack, the standard solution is for the new investors to “reset” the ownership by proposing a financing not only at a different valuation (in order to achieve their ownership objectives) but also to put the new investment at the top of the preferred stack (most senior), and sometimes reduce the existing preference stack to make a return for the new investment more likely. This form of financing, through an ownership restructure, essentially force-converts existing preferred equity holders into not only a common equity position, but also often at a down-ratio whereby their ownership percentage is also significantly reduced. A variant of this deal structure, known as a “pay-to-play,” offers existing preferred investors the right to participate under the new financing terms and by doing so, are offered a conversion mechanism to preserve some or all of the preference of their original investment. While pay-to-play financing structures tend to be uncommon in strong markets, we have seen more of these situations arise in the current climate and expect to see this trend increase.

What it Means for Startups: The 16 Commandments of Raising Equity in a Challenging Market

Despite the current environment, we believe that great founders and great businesses will always have options when raising capital. Amidst this period of market uncertainty, we offer a series of recommendations and advice—our “commandments”—for founders looking to raise in this “new” normal.


  1. Be flexible on structures and sources. Our Managing Partner Ben Horowitz puts it best: “If you are burning cash and running out of money, you are going to have to swallow your pride, face reality, and raise money even if it hurts.” For startups looking to raise in this current environment, it is imperative to internalize that there are a number of viable paths to raise equity (as depicted by the diagram below), including down rounds and flat rounds. There are also many alternative pools of investment capital to tap into beyond VCs, such as strategics, sovereign wealth funds, and family offices. Eliminate artificial boundaries and taboos from your vocabulary: “I want a valuation of at least $X,” “I won’t accept convertible debt,” “I don’t want strategics on my cap table.” Be open-minded when different opportunities arise. Having an inflexible attitude will greatly decrease your options and make it more challenging to raise capital.
  2. Don’t begin conversations with price expectations. Founders should avoid anchoring conversations around price expectations or last round’s valuation. You run the risk of not receiving any term sheets if you convey up front an expectation of a high price. Securing even a low-valuation term sheet early on will help build competitive tension, which you may be able to leverage towards additional term sheets and better terms. You just need one “yes” to get the ball rolling.
  3. Optimize for size, not dilution. For founders who have raised capital during the last few years, the standard approach has been to optimize for dilution given the easy accessibility to capital. However, in today’s environment, founders should instead consider optimizing for round size. If a round has come together and you are being offered more capital than you had intended to raise, taking the incremental dilution now for the additional capital can be a prudent move. This will not only offer a runway extension, but also help avoid a potential situation down the road where you are forced to raise again following a short interval.
  4. Start early to account for the unexpected. During a period of market uncertainty, it is critical to prepare and build in sufficient buffer time to account for unanticipated obstacles, such as partner-level meetings taking longer to schedule, extended confirmatory diligence, or other unforeseen funding delays. By starting your fundraising journey early, you can ensure that you have a time-cushion to fall back on when the unexpected happens.
  5. Prepare well to run an efficient process. Take time up front to thoroughly rehearse your pitch, sharpen your delivery, improve your deck, and prepare a data room. Diligent preparation and deliberate planning will help reduce your chances of making an error, which can be costly and time-consuming to fix later on. Completing a fundraising process expeditiously is imperative in this environment. You do not want your company to become a “stale listing,” which in real estate, refers to properties that have spent too many days on the market. Stale listings are often caught in a vicious cycle: the perception is that something is wrong with it, which keeps other would-be buyers from purchasing it. Similarly, in the venture capital world, startups may also be viewed as “stale” or unattractive to investors. The key to avoiding this stigma is to run an organized and efficient process aimed at creating competition. 
  6. Engage your insiders. Proactively engage with your existing investors (insiders) about your upcoming fundraising plans. Having an insider commit to participating in or leading your round may serve as a strong endorsement and vote of confidence that can encourage other market participants to also invest in the round. However, insiders may be at different stages of their fund lifecycle and may have limited reserves so it is important to have honest and open conversations with them on whether and how much they are able to commit. 
  7. Nurture ecosystem relationships.As our team has discussed in the past, we believe it’s never too early to begin building relationships within your ecosystem, from both a commercial and strategic partnership perspective. Relationships take time to nurture, so this is time well-invested and will pay dividends in the future. These developed relationships can be incredibly useful in helping to catalyze a potential financing, whether it be a bridge round alongside existing investors, a strong signal for new investors to co-invest as part of a larger financing round, or a stage-setter for a potential strategic transaction in the near to long term.
  8. Ask yourself the difficult questions. Even before you meet with investors, think about where investors may push back. Why are newer cohorts showing lower retention? Why is CAC rising? Why have organic acquisitions stagnated? This enables you to anticipate key investor concerns and proactively address them by preparing materials and answers in advance. Investors want to engage with founders who are thinking critically about what they’re doing right, what they’re doing wrong, and what they intend to do differently.
  9. Pressure-test your burn multiple. Stress-test your burn multiple, which we define as cash burned divided by net ARR added. In other words, how much cash are you burning to generate each incremental dollar of revenue? Evaluate how your burn multiple is changing across months and quarters and explore what you can do to improve this metric. Moreover, identify areas that are your largest sources of burn, which areas represent “burn-sinks” vs. burn-investments and have a rationale for why spending is justified. Investors are looking to invest in companies that are able to balance growth and cash burn, as well as those who know how to do more with less. 
  10. Don’t pursue growth at the expense of profitability. The Rule of 40 (Ro40), defined as the sum of a company’s revenue growth and profitability margin, is a metric used by investors to gauge a growth-stage startup’s performance. It succinctly captures the trade-off between growth and profitability. Companies with identical Ro40 scores aren’t necessarily treated the same, since the pendulum between growth and profitability swings over time. During the strong market environment of recent years, the scale tipped in favor of growth, with investors rewarding startups that were able to demonstrate rapid growth even at the cost of poor unit economics and profitability. Since then, the goalposts have moved drastically—the “growth at all costs” mantra has come to an end. Today, investors are putting more weight on profitability. If your unit economics are in the red, consider prioritizing efforts to improve your company’s profitability even if it means achieving lower growth in the present. Growth efforts can always be ramped up later in the company’s journey, but the quest for good unit economics can feel like a Sisyphean task when already operating at scale.
  11. Be deliberate and precise on use of proceeds. Investors want to partner with founders who efficiently overcome roadblocks. It is not enough to show how much and where you plan to allocate future capital; you must also demonstrate that the juice is going to be worth the squeeze. Which acquisition channels are not saturated and thus will provide the best returns on marketing spend? Which customer segments will you deprioritize because their unit economics will not work even at scale? Which features are you pushing to drive better retention? Demonstrate to investors that you know your business inside-out and present a realistic plan on how you will mobilize funding to target the highest ROI levers and achieve specific milestones. 
  12. Grow into your valuation at normalized multiples. If you’re a company that raised capital over the past few years, you likely did so at a strong valuation. Given the recent market correction, your focus today should be setting near-term financial targets that enable you to grow into that valuation at normalized multiples. Balancing offense and defense is key—recalibrate your business plan and adopt operational discipline by evaluating how you’re going to use the capital you’ve raised in the most efficient manner possible to hit the required financial milestones ahead of your next raise. Please see this article written by our Growth investment team on how to think about navigating down markets and scenario planning. 
  13. Don’t myopically view a structured up round. In today’s climate, there are some who believe that securing an up round, even in the form of structured equity, can be a Fountain of Youth that will help maintain both the actual and perceived health of the company. However, founders should be aware that an up round is not a solution for all of the company’s issues. Implementing structure into the company’s capitalization solely for the sake of preserving your last round’s valuation is not an act that is easily reversible and will have downstream effects on future financings. For example, future investors may expect that in subsequent rounds they too will receive the same rights, thereby further diminishing returns to common equity holders, including founders and employees. As such, startups that are several years or rounds away from a liquidity event, may be better off raising a “clean” flat round or down round than an up round that comes with structure such as higher liquidation preference, participation parameters, ratchets, and other atypical governance rights.
  14. Treat deferred valuation as a Band-Aid, not a cure. To address the potential valuation gap between a wide bid and ask spread, some companies are electing to raise capital via SAFE or convertible note structures that defer the topic of pricing. The rationale behind this approach is that it gives the company more runway and resources to achieve key milestones ahead of an eventual formal priced round. The notion of deferred valuation as a magic bullet solution is alluring, but may ultimately present challenges and could derail the eventual priced round. Founders should exercise caution and consider this approach carefully before committing. If you have immediate liquidity needs or anticipate reaching near-term milestones, then this solution between financing rounds may be suitable for you. However, depending on your specific circumstance and the terms of the instrument, it may also lead to misaligned incentives between existing and deferred round investors, as well as present long-term issues with your capital structure if milestones are not met.
  15. Communicate with candor. There may be a tendency to not discuss or communicate a fundraising outcome that on the surface seems sub-optimal. One misconception is that it might spook employees, partners, and vendors by raising concerns that the company’s prospects are limited or challenged. On the contrary, it is imperative in such instances to be transparent with employees about where things stand and to listen to their concerns. Candor and honesty in such moments will help build loyalty and enable you to lead more effectively. 
  16. Preserve optionality. As you embark on your fundraising process, there is a chance that you may not be able to secure the funding you need. As such, it is important to be prepared for the possibility of a sale, soft landing, acquihire, or wind-down. Make sure to set aside sufficient cash and time to explore these alternative paths and potentially dual-track alongside the fundraising process.

Conclusion  

While the strong market environment over most of the past decade has yielded many positive fundraising outcomes, it is important to take a step back and treat fundraising for what it is—a milestone versus a destination. A flat or down round should not be viewed as a death knell for a startup. Many successful, category-leading companies such as Airbnb, Doordash, Block, and Meta raised flat or down rounds along their startup journey. The current environment represents a great time to build, without the distraction of hype cycles, speculative valuation chasing, and unbridled market exuberance. While the capital markets environment has undoubtedly changed following an extended market run, the future most certainly holds great opportunity for founders and investors alike.

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The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. In addition, this content may include third-party advertisements; a16z has not reviewed such advertisements and does not endorse any advertising content contained therein.

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Top 10 Digital Banks of 2022

發表人  研究員    發表日期  2023-03-15    點閱次數  2974


As neo and challenger banks disrupt traditional global incumbents, we rate the leaders of the pack




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