Amex and Microsoft turn to AI to make expense reports; The rise of livestream shopping on TikTok, Amazon And YouTube; Financial OS for healthcare;

Sam Boboev
13 min readFeb 15, 2023

In this edition:

1️⃣ How to operationalize the SME lending opportunity

2️⃣ Amex and Microsoft turn to AI to make expense reports

3️⃣ Understanding social commerce business

4️⃣ It’s interest rates of 20% or even 30% that are crushing people

5️⃣ AI-linked coins surge; some post double-digit gains in a week

6️⃣ Financial OS for healthcare

7️⃣ The Rise Of Livestream Shopping On TikTok, Amazon And YouTube

And many more….


How to operationalize the SME lending opportunity

To realize value from the SME lending opportunity and compete effectively with fintechs and challengers, FIs must consider the business model, technology and operating models they need to empower their product development and delivery.

Outdated legacy systems require high maintenance levels and significant effort to update and change. They incur additional costs, slow down time to market for new products and hinder flexibility in existing products. They can also make it difficult to compete in the new tech-enabled world of financial services where customer centricity and great experiences are paramount.

When looking to update their tech stack, there are some key principles that FIs should adhere to if they want to empower innovation:

• Composable architecture: makes it possible to swap in and swap out components freely without any vendor lock-ins, leveraging “best of breed” technology at the “best of time”.

• Cloud-native infrastructure: enables rapid deployment and provisioning of solutions while leveraging the best-in-class resilience standards and computing power of the public cloud.

• Data-driven: creates a comprehensive data lake allowing data-driven real-time decision-making and potentially delivering dynamic products for niche segments.

• API-first platforms: build and orchestrate ecosystems using application programming interface (API) ready core platforms, enabling seamless integration with various internal applications and third-party solutions.

• Configurable platforms: use low code core platforms to enable quick product rollouts and changes and create bespoke offerings for specific customer segments and geographies.

• SaaS solutions: leverage proven softwareas-a-service (SaaS) solutions to enable rapid scaling and optimize costs via vendor-managed services (e.g. upgrades, maintenance) and allow focus on value-adding activities, e.g. product innovation and customer acquisition.

Source Mambu


Amex and Microsoft turn to AI to make expense reports

Microsoft and American Express announced a deal that aims to do just that. The companies agreed to expand their decades-long partnership to build solutions that leverage Microsoft Cloud and AI technologies, starting with expense report management.

According to Amex, the initial solution will leverage machine learning and AI to automate expense reporting and approvals.

This goes beyond simply learning how to classify certain expenses, as many of today’s tools already do. Instead, the new system will implement an AI-powered decision engine that understands the company’s own travel and expense (T&E) policy and how it applies to submitted expenses. It will use that understanding along with other factors — like the employee’s purchase and payment history — to categorize and assign a risk score to individual transactions.

To make this work, the employee will be prompted to snap a photo of their receipt after paying with their Corporate Amex card. The system will then apply one of three risk scores: red, yellow or green, based on whether the expense is recommended for automatic approval or not, or if it needs another look. This information is passed along to the company’s expense management system with the receipt details attached to automatically generate reports for managers and auditors to use in their own decision-making. Amex says the AI is something it built in-house — it’s not leveraging Microsoft’s partnership with OpenAI, as Bing is, but is using Microsoft Cloud.

Over time, the expense management system will get smarter thanks to machine learning. As more expenses flow through the system, it will improve its algorithms around what sort of expenses can be automatically approved.

Microsoft will be the solution’s first tester and will integrate it with its own internal expense system later in the year, American Express notes. Over time, it will roll out to more Amex Corporate clients and add support for more expense management tools.

While it’s not exactly ChatGPT for expense reports, if successful, the solution could save time and reduce headaches around corporate expense management.

Imagine, instead of spending hours manually categorizing expenses, uploading receipts and justifying the charges, corporate employees would only have to focus on the outliers that actually required further explanation.

Of course, it remains to be seen if the solution is capable of actually accomplishing this goal, as described, or if corporations will even utilize the tech when it becomes available.

Source Techcrunch


Understanding social commerce business

So what makes social commerce so different? Fundamentally, it represents a real shift in power from retailers and brands to people. And it’s being turbocharged by the rise of social media. In contrast to the relative anonymity of big-box retailers and transactional emphasis of e-commerce behemoths, it’s commerce available where people choose to spend their time and underpinned by the authenticity and trust that social connections provide. It’s nothing short of a people-powered democratic retail revolution. And it’s incredibly effective. Why? Because it seamlessly blends social experiences and e-commerce transactions through a single path to purchase, all enabled by a single platform.

Social commerce engages in three principal ways, via brands, influencers or individuals themselves:

1. Content-driven: Unique content created by brands, influencers or individuals drives authentic discovery, engagement, and action. For example, social media users are discovering new goods and experiences via shoppable posts and in-app stores on Pinterest, YouTube, TikTok, Facebook, and Instagram to name a few.

2. Experience-driven: These experience driven channels enable shopping within an overall experience, most commonly livestreaming, but could also include AR / VR experiences or gaming. Look at Obsess’s “Shop with Friends” which enables groups to visit virtual shops with their friends.

3. Network-driven: People are harnessing their existing social networks to buy and/or sell. That could mean getting together to procure bulk discounts — a model used so successfully by Pinduoduo in China that it now has more active buyers than Alibaba10. Or it could mean individuals using their influence and network to drive sales and earn commissions. India’s Meesho now has 13 million+ entrepreneurs who connect with their customers on social media platforms such as WhatsApp.

Source Accenture


It’s interest rates of 20% or even 30% that are crushing people

As part of a push to get rid of “junk” fees, President Joe Biden wants to limit how much consumers owe when they’re late with a credit card payment. Instead of hitting customers with a penalty as high as $41, card issuers would typically only be able to charge a maximum of $8.

For anyone who has had to pay one of those fees, the cap is welcome news. But if the plan goes through, it’s likely banks and other card issuers would look for ways to recoup the loss of an estimated $9 billion from lower late fees. A possible target: interest rates assessed on balances, which is where the industry makes the bulk of its revenue in the first place.

There is no federal rule on the books capping credit card interest rates. Many states have their own usury laws that limit the amount of interest charged, but tend to exempt banks and credit unions. In addition, banks can often get around state rules if they are headquartered in a state without a cap — then they can adhere to their home state’s rules, not the consumer’s.

For years, market forces have kept rates under 30%, but that’s starting to change. Store-branded cards from retailers like Macy’s, Gap, Dick’s Sporting Goods and Wayfair as well as gas companies Exxon and Shell now offer cards with rates above 30%.

While the standard industry argument against pro-consumer changes is that they will be forced to stop serving low-income people with bad credit, that rarely happens. Instead, they usually just find ways to charge them more. The industry made the same complaint before the Dodd-Frank reforms of 2010, and credit didn’t dry up.

Sure, there are other fees lenders might come up with to compensate for the losses from smaller late fees, but the 2009 credit card legislation has been pretty effective at curbing most hidden back-end fees.

And it’s worth pointing out that how different card issuers respond to a late fee cap will depend on how much of their revenue actually comes from late fees. Issuers who have more subprime customers tend to collect more money in late fees, as do issuers of private-label cards, which can usually only be used at a single store or affiliated stores.

Setting an interest rate ceiling isn’t without precedent. Credit unions typically cap their interest rates at 18%. And members of the military generally can’t be charged more than 36% for many types of consumer loans. Adjustable-rate mortgages have caps too (although they’re secured by the home as collateral, unlike credit cards).

The Biden administration and the Consumer Financial Protection Bureau said they’re focused on late fees because the costs card issuers are charging customers far exceed the costs they incur when someone makes a late payment. The federal government should use the same argument to go after lenders who charge sky-high levels of interest.

Source Bloomberg News


AI-linked coins surge; some post double-digit gains in a week

Count on crypto fans to jump on any burgeoning trend as fast as they can.

Digital assets focused on artificial intelligence have been skyrocketing since OpenAI’s chatbot known as ChatGPT became an internet phenomenon and spurred buzz about its future potential.

Nearly all the tokens classified under the AI category by CoinGecko have posted at least double-digit moves over the past week. SingularityDAO jumped 138% over a seven-day period. SingularityNET was 126% higher over that stretch while Artificial Liquid Intelligence rose 87%.

For market-watchers with long memories, it’s reminiscent of other obsessions in the sector. This includes the phase when initial coin offerings were hot, or when a bunch of companies in 2018 jumped on the “blockchain” bandwagon by reinventing themselves — at least on paper — into crypto-adjacent firms.

ChatGPT has recently shown its prowess in everything from writing poems in the style of Shakespeare to creating stock portfolios. There’s even an exchange-traded fund planned around the concept. And while tech behemoth Microsoft Corp. is investing billions in OpenAI, Google owner Alphabet Inc. has demonstrated its new artificial intelligence chatbot Bard after coming under pressure from ChatGPT’s popularity. But even for crypto standards, where wild price swings are de rigueur, the surges in AI-linked tokens are eye-popping.

The phenomenon saw an extreme when the price of ARPA, the token of privacy-focused network also called ARPA, jumped by more than 10% over one hour on Tuesday. The specific reason behind the price pump remains unknown. But Crypto Twitter pointed out that the sudden price appreciation only happened after Felix Xu, the co-founder of ARPA, shared — in a now-deleted tweet on Tuesday — a two-year-old news release on the project’s collaboration on machine learning with a group led by Alibaba.

“It is all pure nonsense,” said Michael O’Rourke, chief market strategist at JonesTrading. The stock market is rife with instances of what O’Rourke considers “speculative” behavior, he said.

Trends come and go, warn analysts who have seen this play out before. The initial-coin-offering boom in the late 2010s burst in a spectacular way that left deep scars for many years. The repercussions of the crypto bubble popping during the pandemic are also still being felt across the industry.

To be sure, the resurgence in crypto prices so far in 2023 could be bringing about new capital and interest from certain investors, as the industry shows some signs of improvement after the collapse of crypto exchange FTX.

Source Bloomberg News


Financial OS for healthcare

A financial OS for healthcare would act as a real-time, action-oriented engine that ingests financial data from the EHR, RCM, banking and credit products, and payroll to become the financial system of record for the practice; predictive analytics to surface opportunities for proactive and reactive improvements; and a trusted source of truth for lenders, vendor partners, and insurance companies when underwriting loans or contracts.

Automated budgeting and forecasting: Streamline and up-level financial planning and analysis (FP&A) by pulling in accurate, comprehensive, and real-time financial data that enables finance teams to re-focus their time on strategic financial assumptions and decisions.

Smart revenue reconciliation: Ensure consistency across claims (EHR), submissions (RCM), and final record (GL) tools, again primarily via real-time data integrations and up-to-date chargemaster linkage.

Financial regulation modules: Offer bespoke bookkeeping infrastructure for complex corporate structures like those in value-based care or managed service organizations (MSOs). Help customers navigate federal and state-by-state regulations and reporting compliance.

Products with these properties are well positioned to become the financial source of truth for accounts payable, accounts receivable, and other payment flows through the practice. From here, the doors open to an even broader product footprint (and higher annual contract values) by integrating adjacent financial products, such as business bank accounts, credit cards, expense management, asset-based lending, patient financing, claims coding, and even data-driven revenue cycle management and payor contracting. A financial OS of this reach and centrality to a practice’s financial state holds the promise of re-orienting the focus of the EHR (and of care) from billing to patient outcomes.

Leaning into financial services has become more possible with the widespread proliferation of fintech infrastructure, which makes it easier than ever for non-bank entities to offer their existing customers financial services, driving higher LTV with no incremental CAC. In many cases, systems of record are even better positioned than banks to underwrite said customers, since they have ongoing access to all key operating data of the business. In fact, either wedge — software or financial services — could be viable for an initial go-to-market approach. It’s essential that any business truly pursuing the full financial OS for healthcare vision ground itself in the platform architecture referenced above, and lay down sturdy roots in the form of core software functionality.

As healthcare increasingly takes up more of the nation’s GDP — while still relying on disconnected, outdated financial rails — building in the healthcare x fintech space becomes more critical to the health of the system as a whole.

Source a16z


FinTech Annual Almanac

- Private FinTech company funding volume fell 38% in 2022 to $88.1 billion. While 2021 reached unprecedented levels of funding activity ($141.0 billion in volume) the 2022 total is still 95% higher than the volumes recorded in 2020, 2019 and all prior years as well.

- Driving the lower overall funding volume, 53% of financing rounds were less than $10 million dollars compared with 46% in 2021.

- Emerging markets FinTech activity continued to thrive in 2022 with Africa and Asia both reaching a record number of funding rounds during the year, led by activity in Nigeria, India and Singapore.

- The Banking / Lending Tech sector was the most active in 2022 with $24 billion in financing volume across 1,010 capital raises, beating out the Crypto & Blockchain sector which recorded $17.5 billion and 877 deals.

- FinTech M&A totaled $129.6 billion in volume, the lowest level since 2017. With a total of 1,270 M&A deals though, 2022 was the second most active year ever only behind 2021, which had 1,485 deals.

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The Rise Of Livestream Shopping On TikTok, Amazon And YouTube

Livestream shopping took China by storm during the pandemic, growing into an estimated $423 billion market in 2022. Think of it like QVC, but entirely online and hosted by famous influencers with millions of followers. The trend has caught on more slowly in the U.S., but now Amazon, TikTok, YouTube and Shopify are making big investments in hopes it takes off. CNBC goes behind the scenes with creators like Myriam Sandler to find out what it’s like to sell via livestream, and what it’ll take for the emerging model to become a mainstream way that U.S. consumers shop.


AI comes to expense reports

Rebrands are not uncommon in the startup world, and the fintech space is no exception. They are particularly more prevalent when companies pivot to adapt to external circumstances. Last week, TripActions announced it was rebranding and is now called Navan.

TripActions pivoted from being a travel expense management company to a corporate card and expense management for enterprises more generally soon after the COVID-19 pandemic hit in March 2020. In 2021, CEO and co-founder Ariel Cohen told me that its revenue didn’t just drop — it bottomed out . . . to zero. That’s when execs decided to focus its efforts on its then-new Liquid offering, which appears to have worked out pretty well for the company. In October, amid its continued growth, the company raised $154 million in equity at a post-money valuation of $9.2 billion, up from its prior valuation of $7.5 billion, as well as a $150 million structured financing deal from Coatue. Then in December, it secured $400 million in credit facilities from Goldman Sachs and Silicon Valley Bank (SVB).

Its rebrand is more than just a name change, apparently. The company said it has now unified its travel, corporate and expense offerings into “a single super application.” On top of that, Navan — a combination of navigate and avant (or forward) — claims to be the first travel company to integrate OpenAI and ChatGPT APIs across its infrastructure and product set.

The company says it is currently using the generative AI technology to write, test, and fix code with the aim of increasing its operational efficiency and reducing overhead. So now, through Ava — Navan’s virtual assistant — travel managers are able to personalize recommendations and increase traveler engagement, execs claim. They say also that admins can use the tool as a personal assistant to perform tasks such as performing personalized data analysis, providing granular carbon emission details or ordering corporate cards for their company. Meanwhile, travelers can do things like perform a travel search, solve customer support issues and even recommend an Indian restaurant near their hotel in London, for example.

Source Techcrunch



Sam Boboev

I am a fintech enthusiast and product leader passionate about crafting simple solutions for complex problems. Subscribe