editions

The biggest firms have a joint incentive to create a shared platform to fix chronic issues in exchange traded derivates processing, like fragmentation and lack of transparency.

Bank of America, Barclays, Citi, Goldman Sachs, JPMorgan, Wells Fargo, and BNP Paribas just invested $25.4 million in FIA Tech and its Trade Data Network (TDN) initiative.  

TDN – which currently includes 16 banks and brokers and 40 investment managers and hedge funds – aims to add cohesion and transparency to exchange traded derivatives post-trade processing. It will ultimately reduce overall costs and clearing delays for brokers. 

This group investment is just the latest example of top firms banding together on a tech solution that serves their collective interests: Insights Distilled previously covered efforts to report scams and combat fraud, connect various blockchains, and bring trust to carbon credit trading.  

The dark side of efficiency for employees is that it can drive workplace reductions: As digital transformation plans make progress, banks are making layoffs. 

The progress of Citibank’s tech transformation projects is driving some of the thousands of layoffs it plans to make this year, chief financial officer Mark Mason said on stage during a recent Morgan Stanley conference.  

The bank is in the process of retiring legacy platforms and it’s moving its wholesale credit risk platforms to a standardized underwriting process.  

Over time, “we will no longer need the same level of people that we have at this particular phase,” Mason said on stage. “We’re reducing people even further … as we use that technology to automate a bunch of activities that we have to do manually today.” 

Citi’s tech-driven layoffs follows Capital One’s lead from earlier this year: The bank cut 1,100 people from within the agile development group of its tech department, saying that the frameworks it developed were becoming integrated into the bank’s core engineering practices, making jobs redundant. 

While online BNPL options exploded during the pandemic, Citizens sees a chance to differentiate itself by tackling in-person businesses, and it’s expanding its network faster by working with Wisetack. 

Citizens Bank is partnering with Wisetack to bring BNPL financing to more in-person services through the fintech’s network of merchants.  

“We’re excited to partner with Wisetack and their growing network of merchant partners to enable more customers to responsibly pay for critical purchases like home repairs, maintenance, and improvement,” Citizens exec Christine Roberts said.  

Digital BNPL providers like Klarna and Affirm have dominated ecommerce, while startups like Hokodo and Insight Partners’ portfolio company Resolve are taking on B2B-focused BNPL, but there’s a gap in service for SMBs that sell to consumers in-person.

Citizens has historically had high-profile BNPL partnerships with Apple, Microsoft, and Best Buy, but sees an opportunity to expand its reach. Working with Wisetack allows it to access many small-business customers through a single connection. 

Programmers are embracing AI coding tools, though some remain skeptical of their accuracy. FinServs should deal with AI-powered programming proactively.

Recent surveys from GitHub and Stack Overflow show that AI-powered coding tools are making a big impact.  

GitHub partnered with Wakefield Research to survey 500 US-based enterprise developers and found that 92% are using AI coding tools and that 70% believe that AI is providing significant benefits to their code. More specifically, AI tools are helping them achieve improved code quality, faster outputs, and fewer production-level incidents. 

A Stack Overflow survey of ~89,000 global developers, meanwhile, showed similar uptake with more nuance around trust. The survey found that 70% of programmers were already using or planning to use AI coding tools this year, but only around 42% said they highly trust or somewhat trust those tools.  

The results of both surveys highlight why FinServs should be taking a proactive approach in guiding experiments with their developers: Because if they don’t, the engineers will probably use AI tools anyway.  

By setting up pilot projects for tracking the accuracy, safety, and efficiency of tools like GitHub Copilot, Tabnine, and AWS CodeWhisperer, FinServs can protect themselves and get a concrete understanding of benefits.  

For example, Goldman Sachs started proactively setting up experiments that allow engineers to use generative AI tools to write and test code more efficiently and is tracking the progress. 

Trade finance often still involves paper documents moving between banks, shippers, and exporters, and JPMorgan just gave a vote of confidence to Cleareye.ai to disrupt that archaic process.  

JPMorgan’s Trade and Working Capital group has made a strategic investment in Cleareye.ai, a startup that it started working with last year to digitize and automate trade finance, which has largely been stuck in the past.  

Through a combination of computer vision and natural-language processing, Cleareye.ai automatically ingests documents and then analyzes them to catch compliance and sanction violations or money laundering red flags.  

Instead of manually poring over documents, trade operations analysts can now skim Cleareye.ai’s reports, which drastically reduces processing times, human error, and risk. JPMorgan previously said the tool could “massively improve efficiency” for its commercial trade processing tool. 

Cleareye.ai and JPMorgan aren’t the only ones gunning to transform trade finance, though: Santander’s corporate and investment banking arm just made its own strategic equity investment in Komgo, which also aims to increase the efficiency, transparency, and security of trade finance.  

One of the superpowers of ChatGPT is its ability to simplify complex topics, which makes it an excellent educational tool for fledgling workers. SouthState is already seeing a significant productivity boost among its employees. 

ChatGPT is an intern’s new best friend, according to an executive at SouthState Bank who spoke at a recent American Banker conference. The bank trained an enterprise-version of ChatGPT on its own documents, allowing the bot to answer questions about internal information, complete with citations and references.

“As you learn about any new topic, it doesn’t make you an expert, but it takes a below-average person or an average person and ups their game,” exec Chris Nichols said on stage. “We’re just bringing on a bunch of interns this week for our summer intern program and we’re training them first and foremost on how to use our version of ChatGPT in order to quickly become experts at learning about deposits or regulation.” 

This aligns with a recent study that showed how an AI-powered customer service chatbot at a Fortune 500 firm was particularly useful for new agents, who benefited more from automated advice than their more experienced coworkers.  

“It normally takes an employee 12 to 15 minutes to figure out the correct answer,” Nichols said. “That gets reduced to seconds.” 

It cost SouthState about $50,000 to bring the tool to production and about $30,000 a month to test and run. It pays for itself, according to Nichols: “If you have 5,000 employees using it and they’re five to eight times more productive, that $30,000 a month is nothing.” 

For more examples of how GenAI is transforming financial services, read Insights Distilled’s recent report. 

Google Cloud wants banks to embrace artificial intelligence for flagging fraud.  

The company just released a new tool that does away with rules-based systems for AML compliance in favor of an AI-generated risk score based on a bank’s historical data.  

In a typical system, 95% of alerts for review turn out to be “false positives,” which waste time and resources for compliance teams. Google’s tool cuts down on the overall number of alerts that need human review, without letting risk management wane, thus increasing operational efficiency and effectiveness, according to the company.  

Since HSBC became an early tester of the product (it began using it in 2019), the tech has cut down the bank’s number of alerts by as much as 60%. It also now detects two to four times more “true positive” risk, or confirmed suspicious activity, Google said.  

By integrating Google’s tool into its customer monitoring framework, HSBC has been able to “improve the precision of our financial crime detection and reduce alert volumes, meaning less investigation time is spent chasing false leads,” according to head of compliance Jennifer Calvery. “We have also reduced the processing time required to analyze billions of transactions across millions of accounts from several weeks to a few days.” 

JPMorgan picked an executive with 30 years of experience at the bank for a prominent new role, highlighting the importance of context and relationships in building a successful AI strategy.  

The head of JPMorgan’s new data and analytics unit, Teresa Heitsenrether, will be responsible for infusing artificial intelligence into every facet of the bank’s business.  

“Using AI technologies effectively and responsibly to develop new products, drive customer engagement, improve productivity, and enhance risk management will be a top priority,” CEO Jamie Dimon and president Dan Pinto said in a memo announcing Heitsenrether’s hire. “Teresa is an outstanding leader with an exceptional track record, helping to build and transform some of our most successful businesses.”  

It’s telling that JPMorgan selected an internal leader with deep context and relationships across the firm to lead the new unit, instead of a hotshot external technologist.  

Meanwhile, as Distilled previously reported, none of the biggest banks in the United States have the same organizational arrangements for their AI efforts.  

For example, Citi funnels work through its AI center of excellence, while Bank of America organizes its AI initiatives along business lines, with chief experience officers from different divisions, including consumer banking (Teron Douglas) and wealth management (Christian Kitchell). CXOs report into BofA’s chief digital and chief marketing officer, David Tyrie.   

As payments and fraud prevention become more complex, artificial intelligence will play a key role in creating a frictionless, safe experience for consumers.

As financial products and services are increasingly embedded and delivered through new platforms, there’s more opportunity than ever for bad actors to exploit the system and commit fraud. But as the conversations and trends from Money 20/20 Europe made clear, artificial intelligence will be a key tool for FinServs to fight back and evolve their processes.

“Particularly with real-time and global payments, AML compliance and risk and fraud monitoring have a long way to go to deliver true frictionless experiences, while minimizing false positive and false negative flags,” according to an Insight Partners rep who attended the event. “This is one place where AI can be a true game-changer.”  

In addition to the Google example above, Insights Distilled has previously reported on how innovative tech firms are trying to use artificial intelligence to flag hidden patterns in payments data and automate continuous know-your-customer monitoring. The best fintech providers will be those that make orchestration easy across various data layers, Insight adds. 

The team also identified several other key narratives that emerged from Money 20/20 Europe: 

Disrupting B2B payments remains an untapped opportunity. Business-to-business transactions have been stuck in the past, making it a segment ripe for modernization. The fintechs that succeed will be those that take on specific geographies industries, or size cross-sections and solve the largest pain point within that niche.  

AI will change everything – eventually. Financial institutions are not standing still in the wave of GenAI, but regulatory and fairness risks remain – as well as questions on who should hold the burden of customer education. Service and support, product recommendation and delivery, risk scoring, payments optimization (particularly within FX and capital markets), and transaction processing and reconciliation are ripe for disruption, but timelines for production-level rollouts remain uncertain. 

Through a partnership with Subaio, Mastercard is offering an in-demand service that could help banks wrest power from third-party providers and reduce costly chargebacks. 

Consumer subscription fatigue is real and the resultant chargeback costs can be steep, so Mastercard launched a product that can save time and money for both banks and their customers.  

The technology will allow customers to see all their subscriptions within their banking app and unsubscribe to goods or services automatically without having to contact the merchant directly. Banks can enable the new subscription management tool, created through Mastercard’s partnership with fintech Subaio, through an API. 

Mastercard’s pitch to banks is that offering this tool to their customers can help reduce chargeback disputes, pressure on call centers, and operational costs in general. They’d also have ownership over a value-add service, which could increase customer goodwill and loyalty.  

Some banks already make it easy for customers to automatically track subscriptions (for example, Capital One’s Eno chatbot will display all recurring payments), but third-party tools like Rocket Money and PocketGuard have so far dominated subscription cancellation and management. This product would give banks ownership over that capability.  

Mastercard first started working with Subaoi through its Start Path program, which engages dozens of fintechs per year, and this latest launch is a proving point for that model.