Four critical actions ensure finance AI success; DeFi lender moves to tokenize real-world loans on-chain; Why tokenize real estate;
In this edition:
1️⃣ Sequoia Capital enters Pakistan’s startup economy by backing fintech
2️⃣ Four critical actions ensure finance AI success
3️⃣ Why consumers will accept financial products from nonbanks
4️⃣ Why AI Customer Journeys Need More Friction
5️⃣ Why tokenize real estate
6️⃣ Crypto venture investment firm Variant has raised $450 million
7️⃣ DeFi Lender Moves To Tokenize Real-world Loans On-chain
8️⃣ The Crypto Banking System
9️⃣ Aave DAO voters have approved creating a new stablecoin
🔟 E-Commerce Software Funding Slows As Shoppers Pull Back
Sequoia Capital enters Pakistan’s startup economy by backing fintech
Pakistani fintech company “Dbank” pulled off the nation’s largest early-stage fundraising round, which also marked venture giant Sequoia Capital’s entry into the nation’s startup economy.
Dbank raised $17.6 million in the seed round co-led by Sequoia Capital Southeast Asia and Kleiner Perkins. Digital banking platform Nubank, RTP Global, Rayn and local partner Askari Bank also participated.
Pakistan, the world’s fifth-most populous nation, came under the spotlight with record funding of about $350 million in startups last year. The South Asian nation is in the early stages of its startup economy.
Still, the nation is feeling the impact of the global downturn with Uber’s Careem unit suspending food deliveries and Airlift Technologies shutting down after raising the nation’s largest-ever round last year.
Dbank was formed by two former Google employees, Tania Aidrus and Khurram Khalil Jamali (张可容) خرّم خلیل جمالی, who have worked together for over a decade. The company has applied to become a digital retail bank in Pakistan, with an aim to operate in the Pan-Islamic world.
Pakistan as an emerging market has immense potential, according to Mamoon Hamid, a partner at Kleiner Perkins. Dbank is targeting the country’s 110 million adults without access to banking services, which makes it the third-largest unbanked nation after India and China, according to World Bank.
“Pakistan has a fast-growing middle class with increasingly sophisticated banking needs,” said Johan Surani, vice president at Sequoia Southeast Asia. “This signals a unique opportunity to build a large, customer-centric bank for millions of people.”
Source Bloomberg LP
Four critical actions ensure finance AI success
Gartner research shows that leading AI deployers share four common behaviors that enable them to quickly meet or exceed the expected impact of their AI projects and deliver critical finance and business outcomes.
№1: Hire external AI-specific talent
There are three options for securing talent with AI skills and expertise: hire new talent, upskill current talent or borrow talent from the IT department. Organizations that focus their talent strategies on hiring outside AI-skilled employees are significantly more likely to become leading AI finance organizations.
AI-specific talent brings invaluable experience in working with the nuances of AI. This allows the organization to overcome inertia in working with AI applications and shortens the technical learning curve. While upskilling finance staff may be less expensive, doing so runs the risk of slowing progress and introducing greater potential for error. New AI-specific talent changes traditional processes and mindsets by bringing fresh ideas to support AI deployment.
№2: Invest in software with embedded AI for quick wins
Purchase software with embedded AI capabilities to experiment with AI and apply it to finance use cases to quickly build pilots for unique business problems. Building in-house AI solutions for all finance processes creates far more work and reduces bandwidth to explore new pilots or use cases.
№3: Experiment early and broadly
Top finance AI organizations take a “fail fast” experimental approach to AI deployment rather than make a few big bets. With early pilots comes more uses of AI, and deployment is faster as you can zero in on the most successful pilots.
The three most common AI use cases are accounting processes, back-office processing and cash flow forecasting. Customer payment forecasting is a use case explored by half of leading organizations, but very few of the less successful ones.
№4: Choose an analytical AI implementation leader
You must select the appropriate person to head AI deployment to realize the benefits. This could mean the head of financial planning and analysis (FP&A) or the head of finance analytics leading AI implementation rather than a controller.
Heads of FP&A and finance analytics are successful in leading AI due to their strong analytical and data backgrounds. They rely less on understanding traditional finance processes and more on understanding the complexities of AI in a business setting.
Why consumers will accept financial products from nonbanks
The future for banks providing embedded finance, which many see as bright, will hinge on more consumers ignoring the banks themselves and concentrating on doing business with their favorite retail brands.
The use of embedded banking is already in motion, so there is some experience to explore. 35% of consumers had already used embedded financial services with technology/electronics sellers, for instance, most typically in the form of a credit card or an extended warranty.
Given that an embedded relationship must pay off both for the nonbank brand and the financial provider, Cornerstone also asked consumers what impact embedded finance had on their relationship with the nonbank brands. This produced a nuanced picture. While nearly a third of people surveyed reported spending more money with sellers who offered embedded finance, for example, an almost identical number of people said that nothing had changed.
Though spending more money with sellers was cited only about a third of the time, focusing only on that ignores other important results seen in the chart. Choosing sellers over competitors also means more sales (and volume for the embedded provider) and increased loyalty and recommendations can also go to the bottom line.
The study then looked at willingness to use financial services provided through nonbank sellers.
The strongest reasoning seen among those who would use financial products came down to price — four out of five assumed that obtaining the financial product from the seller would make it cheaper. It’s possible this is influenced by consumer observation of the way most buy now, pay later programs have worked in the past — the seller is seen as putting the BNPL offer forward on behalf of the provider and there is no interest charge.
However, hurdles exist in moving forward with the embedded finance model. As seen below, 77% of consumers said they would not trust financial products obtained from a nonbank. It may be that the invisibility of the bank or fintech in the mix may be a handicap with some segments.
Incentives and innovation may help move those needles. The study provides a long list of variations on product themes:
- A credit card that rewarded players for the purchase of games and for in-game purchases: 75%
- An in-game deposit account (real money) used to buy and sell in-game items and to store real rewards for progress in the game: 74%
- Health insurance with rates pegged to personal fitness habits: 68%
- An investment account integrated into fashion and luxury brand apps, for investing in the brand’s stock, crypto and other assets: 65%
- A savings account that sets aside extra money towards a future auto purchase, beyond current car payments: 52%
- A home equity line of credit built into home improvement stores’ own apps to handle payments for big projects: 49%
Source The Financial Brand
Is DeFi entirely new, or taking the best from traditional finance and improving on it?
“Everything old is new in crypto” what the Bloomberg LP crypto team means by that is that while there’s a perception that ideas like the blockchain are novel and groundbreaking, the reality is there’s lots of precedents for concepts like DAOs (decentralized autonomous organizations) or ICOs (initial coin offerings). This is particularly clear right now, as crypto experiences its own version of a “Bear Stearns moment.” Which all begs the question: Is decentralized finance just reinventing traditional finance with more complexity and a sprinkling of blockchain? Or is there genuine novelty here?
Bloomberg Opinion columnist Matt Levine and Bloomberg reporter Muyao Shen join host Stacy-Marie Ishmael on this episode.
Why tokenize real estate
Here are a couple of reasons.
Low entry barriers
Just like how REITs made real estate investments more accessible to regular people, real estate tokenization does the same — on steroids.
In 2019, a luxury villa in Paris valued at €6.5 million was tokenized and put on the Ethereum blockchain. The asset was subsequently split into 1 million pieces of as small as €6.5 (!)
With a piece of real estate costing about the same price of a burger, tokenization drastically lowers the entry barriers. A much wider range of investors is able to access the real estate market.
As the entry barriers of owning tokenized real estate become lower, investors are able to create highly diversified portfolios.
The wider audience that’s able to be reached due to lower entry barriers is not the only driver behind a more liquid real estate market.
As digital tokens on a blockchain are able to be securely and efficiently transferred without a middleman, trading of these asset-backed tokens suddenly becomes much easier and cheaper as well, leading to increased liquidity.
Blockchain technology, with its ability to automate processes and to cut out middlemen, can lead to cheaper and more efficient processes.
Bottlenecks all around
2017–2018 marked a huge ICO boom. Ever since then, regulators have entered the field, and investments in ICOs have been declining.
It seems like regulators have pushed ICOs away, moving the market towards their more regulated counterpart: STOs.
While there are some options which allow you to dodge the bullet of a full SEC registration (like going for a “Regulation A+” offering), doing an STO is still far from easy.
This is shown by, for example, ARCA Labs, who got approval for their US treasury backed security coin Arcoin. It did not take less than 605 days though to make it through the regulatory funnel.
In other words, regulation is a bottleneck for real estate tokenization projects to take off.
The Proptech Connection mentions they see many benefits in using blockchain technology for real estate, but that without a structured framework, there will be a bottleneck to adoption.
Another bottleneck, as shown by the $30 million Manhattan project discussed earlier, is that institutional appetite was not enough. As Sam Tabar, Fluidity co-founder, mentioned: “The market was just too young at the time. It didn’t have sufficient institutional appetite.”
What’s to come
One can conclude that real estate tokenization might not have lived up to the high expectations that were set during the 2017–18 hype.
But hey — how often does reality actually live up to hype?
Especially in a market like real estate — infamous for its complexity, paperwork and intransparency — we shouldn’t expect disruption to just happen overnight.
Crypto venture investment firm Variant has raised $450 million
Crypto venture investment firm Variant has raised $450 million across two new funds targeting the beleaguered market for Web3 and decentralized finance.
In a Thursday announcement shared with The Block, the company said it raised $300 million for a so-called opportunity fund as well as $150 million fund to invest in earlier-stage startup projects. Led by general partners Li Jin, Jesse Walden and Spencer Noon, Variant closed its first fund in 2020 and most recently announced a $110 million fund following a merger with Atelier Ventures in 2021.
The two new funds will have a mandate that’s breadth reflects Variant’s investing history, with the firm noting in press materials that it will look at four specific buckets of investment opportunities: decentralized finance, blockchain infrastructure, consumer applications in Web3, and projects experimenting with new forms of ownership.
“Tokens and NFTs enable net-new user experiences that satisfy diverse motivations and ‘jobs-to-be done,’ from control to belonging, to financial alignment with the products you use everyday,” the firm explained. “Ownership is a design space for new product features and experiences.”
The two new funds launch amidst an unsavory backdrop for the crypto market, which has seen volumes across various platforms decline, users retreat, and prices broadly sink. Yet Variant isn’t alone among investors in forging ahead with fresh fundraising. Crypto vets Jason Choi and Darryl Wang launched a new fund targeting web3 this summer. David Gan, a former executive at Huobi, launched his latest venture fund of funds in June.
As for Variant, the firm remains bullish on the long-term future of web3. According to Walden, the technology powering the emerging web3 industry will only improve from here.
“In the history of technology, technology doesn’t get worse and disappear — it gets better and more pervasive,” he said. “And that’s happening at an exponential rate in web3, because this is all software, it’s all open source, and there’s just tons of talent jumping in… So the tech is working, and again, I think that means it’s only going to be more pervasive.”
As noted by The Block Research, venture funding in the blockchain sector declined roughly 22% in the second quarter of this year, from $12.5 billion the previous quarter to $9.8 billion.
Source The Block
DeFi Lender Moves To Tokenize Real-world Loans On-chain
Decentralized lending protocol Polytrade is tapping a fresh source of liquidity: DeFi loans targeting startups and midsize businesses looking for lines of credit.
Polytrade’s latest counterparty, Teller protocol, ought to permit Polytrade to tokenize real-world invoices and bring those assets on-chain.
In traditional finance, invoice financing helps businesses borrow money from insurers via collateral owed by borrowers. Now, on Polytrade, invoices will be assigned to the platform at the loan maturation date and then tokenized.
“By utilizing Teller protocol, Polytrade [can] unlock an entirely new liquidity pool, offering a wider array of qualified lenders the chance to provide trade finance credit,” Piyush Gupta, founder of Polytrade, said in a statement.
Ryan Berkun, CEO of Teller Finance, told Blockworks he wanted to build Teller because he felt that for DeFi (decentralized finance) to grow up and increase market share, “we needed to expand to some type of lending based financing or under-collateralized lending.”
Knowing that borrowers were on the hunt for access to more capital to grow operations, Berkun said he “wanted to create an infrastructure that would make it easy for businesses to launch their own lending book.”
“That is what Teller is today — a lending marketplace that enables fintech business owners [and] developers with easy infrastructure to source capital from DeFi,” he said.
Unlike many other DeFi lending protocols, Teller does not have an internally operated liquidity pool.
“Every borrower is different,” Berkun said. “They need different interest rates and different terms.”
Teller, as such, has a number of design parallels to non-fungible token (NFT) marketplace OpenSea — with loans standing in for digital collectibles.
The protocol lets borrowers to bridge off-chain data to on-chain loan transactions. Businesses and individuals requesting assets will propose a loan request on the platform, and suppliers will commit to assets and loan requests of their choice.
The last step to seal the deal is agreeing to terms.
Berkun said Teller’s new partnership with Polytrade will help solve international financing trade problems.
“Polytrade is bringing legitimate invoicing from trade financing to the on-chain world, so they can source capital for these invoices,” he said. “They’ve been doing this since 2014 in the traditional finance world and have insurance built in on all of these invoices.”
The Crypto Banking System
On the right, we have ultimate lenders (households with excess savings, financial institutions, sovereign wealth funds, …), agents with excess cash that could be used (for a cost, the interest rate) to finance ultimate borrowers (households with a mortgage, small and medium enterprises, big corporations, governments) on the left.
As you can see in the chart, while native crypto-assets (think ETH, BTC, …) are in the legend, they appear nowhere. It is by no means complete and further work will analyze the place of crypto-assets. You can also consider Cash being a crypto-currency and, assuming real-world assets are using the same unit of account, it would work the same.
As we will see, the keys components of the Crypto Banking System are the followings:
- creation of deeply liquid tokenized bonds representing real-world credit (private credit and public markets).
- core infrastructure of a market-based economy with decentralized exchanges and repo markets, the crypto market.
- intermediation of saving and lending with crypto-banks that operate in maturity transformation.
An overwhelming majority of Aave DAO voters have approved creating a new stablecoin
The proposal, submitted by Aave Companies, was backed by 99.9% of voters, who pledged half a million AAVE in approving the measure to create GHO, a stablecoin that will be backed by collateral consisting of other cryptocurrencies.
Users looking to mint GHO first will deposit cryptocurrencies accepted by Aave. People who borrow GHO against crypto assets will still earn interest on the underlying collateral used to mint the stablecoin. The lending protocol will also charge interest on loans taken out in GHO, with payments going back to the Aave DAO.
The deposits users allocate in order to mint GHO will have to be greater than the value of GHO they receive, meaning that the loans will be over-collateralized. When users repay a borrowing position or are liquidated, the GHO lent will be burned from the protocol.
Even though the measure was approved, GHO’s introduction will take time as it’s implemented through an Aave improvement protocol (AIP), with the Aave DAO in charge of supervising the stablecoin’s distribution once its creation has been vetted.
The vote spanned a total of three days, and the price of AAVE — the coin native to the lending platform — spiked immediately following the proposal’s approval, to around $108 from $95.40. At time of publication, AAVE was valued at $102.50, up 4.5% in the past 24 hours.
As of now, the market capitalization of all stablecoins is over $153 billion, according to CoinMarketCap, and primarily composed of Tether’s USDT and Circle’s USDC. Legislation in the U.S. regarding the regulation of the digital asset class has recently been pushed back.
GHO will be pegged to the U.S. dollar and the stablecoin will be backed by a mix of cryptocurrencies that users can already deposit on the platform. The native interest rate of the stablecoin will be determined by the Aave DAO, according to an introduction of GHO on Aave’s website.
E-Commerce Software Funding Slows As Shoppers Pull Back
With inflation running at multidecade highs, budget-strapped consumers are cutting back on discretionary spending.
For retailers, this has translated into fewer buyers for items like clothes, furniture and gadgets. Walmart shares tanked earlier this week after the retailer said it is having to cut prices to reduce merchandise levels, which brings profits down. Items like kitchen appliances and exercise equipment that were backlogged a year ago are now overflowing stores and warehouses.
The slowdown also has extended to providers of backend software and services to online retailers. This week, Shopify — the stock market poster child for the e-commerce boom of 2020 and 2021 — posted a quarterly loss and downwardly revised forecasts, and said it will cut 10% of its workforce.
Shopify shares, down about 80% from highs last fall, are also emblematic of broader sector woes. Others in the e-commerce software space, including relatively recent market entrants like BigCommerce and Global-e, are also down sharply.
For startup investors in the retail-focused SaaS startups, meanwhile, all of this is happening at a particularly inconvenient point in time.
That’s because last year, investment in e-commerce software companies hit an all-time high, with more than $4.8 billion in global venture funding, per Crunchbase data. This year started hot as well, with a decline in funding in the past couple months only slightly offsetting a rollicking first quarter.
Where did venture investments go in 2022?
Salsify, a provider of tools for retailers and brands to beef up their e-commerce presence, was the largest equity funding recipient in the space this year, per Crunchbase data. The Boston-based company closed on a $200 million Series F round in April at a $2 billion valuation.
Market conditions, however, are sharply different from even a couple quarters ago. And the swell in online shopping that began in the early days of the pandemic has since receded.
As Shopify CEO Tobi Lütke pointed out in a letter to employees this week, when the COVID pandemic set in, almost all retail shifted online, and demand for software to help with that shift skyrocketed.
For venture-funded e-commerce software software startups, it’s likely a similar trajectory will apply. Consumers haven’t abandoned their online shopping carts. And it’s reasonable to expect steady growth ahead. But the environment is now one in which supercharged growth will likely be much harder and costlier to achieve.
Why AI Customer Journeys Need More Friction
Friction isn’t always a bad thing, especially when companies are looking for responsible ways to use AI
The trick is learning to differentiate good friction from bad, and to understand when and where adding good friction to your customer journey can give customers the agency and autonomy to improve choice, rather than automating the humans out of decision-making.
Companies should do three things:
1) when it comes to AI deployment, practice acts of inconvenience;
Perhaps the first and most critical inconvenient act is for your team to take a beat and ask, “Should AI be doing this? And can it do what is being promised?” Question whether it is appropriate to use AI at all in the context (e.g., it cannot predict criminal behavior and should not be used for “predictive policing” to arrest citizens before the commission of crimes, “Minority Report” style”).
Deliberately place kinks in the processes that we have made automatic in our breathless pursuit of frictionless strategy and incorporate “good friction” touchpoints that surface the limitations, assumptions, and error rates for algorithms. Consider external AI audit partners that may be less embedded in organizational routines and more likely to identify areas where lack of friction breeds a lack of critical, human-first thinking and where good friction could improve customer experience and reduce risk.
2) experiment (and fail) a lot to prevent auto-pilot applications of machine learning;
This requires a mindset shift to a culture of experimentation throughout the organization, but too often, only the data scientists are charged with embracing experimentation. Executives must encourage regular opportunities to test good friction (and remove bad friction) along the customer journey. For example, at IBM all marketers are trained in experimentation, tools for experiments are user-friendly and easily accessible, and contests of 30 experiments in 30 days occur regularly. This requires management be confident enough to have ideas tested and to let the lessons about the customer drive the product.
3) be on the lookout for “dark patterns.”
Gather your team, map your digital customer journey, and ask: Is it easy for customers to enter a contract or experience, yet disproportionately difficult or inscrutable to exit? If the answer is yes, they are likely in a digital version of a lobster trap. This entry/exit asymmetry undermines a customer’s ability to act with agency, and nudging along this type of customer journey can start to resemble manipulation.
Examples include subscriptions that frictionlessly auto-renew with fine print that make them seem impossible to cancel and data sharing “agreements” that mask violations of privacy. Increased transparency into options along the customer journey, though not frictionless, preserves customer agency and, eventually, trust. This is a critical for customer loyalty.