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Recent events have proven that social media should be integrated into banks’ risk-management programs, and that firms should deploy dedicated tools and proactive communication.

Silicon Valley Bank’s collapse – as well as subsequent failures and recent hearings – taught the industry an important lesson: The havoc that negative social media chatter can wreak on banks shouldn’t be taken lightly. 

Tweets questioning SVB’s financial health “prompted nervous customers to pull $1 million per second from their accounts,” according to Reuters, which reports that banking execs have spent the past several months looking for ways to amp up their emergency response and risk capabilities around social media. 

Here are three concrete steps banks should take to shore up their social media strategies: 

Dedicate resources to tools and the staff managing them: “There are so many social media monitoring tools today, but the use of those tools is often delegated to threadbare marketing teams or third-party vendors,” according to Jim Perry, senior strategist at Market Insights. Banks need to both fund tools and “dedicate more human resources to social media monitoring,” he added.  

Be proactive in resolving customer concerns and quashing misinformation: Banks should identify and communicate with their “influential community members” and proactively counter any misinformation, according to Consumer Bankers Association CEO Lindsey Johnson. Contact people directly who complain on social media and address their issues quickly.  

Educate customers through transparency: In addition to tackling communication from key people, spread facts and resources to all depositor bases via email, Twitter, and LinkedIn, Johnson added.   

You can read Reuters’ full report here. 

Quantum computing is still in its infancy and UBS’ experiences demonstrate how FinServs’ efforts may not lead to any real-world products. Still, the experimentation is worth it for the skills-building and research.  

UBS abandoned its efforts to use quantum computing for trading, because the technology didn’t provide any substantial advantage, its former chief data officer, Lee Fulmer, said at a recent conference.  

Quantum – an emerging computing paradigm that promises to perform calculations at blistering speeds – is still in its experimental phase. And those experiments don’t always work out, per Fulmer’s experiences.  

UBS was trying to use quantum computing to speed up the bank’s existing trading models in order to “give us a competitive advantage,” he said. “In investment banking you live and die by microseconds: The end result of all of that effort was that we found we weren’t getting a substantive uplift.”  

Fulmer left the firm in March, but his sobering perspective shows why early experimentation is crucial in shaping an overarching quantum strategy: Certain domains may never benefit from quantum computing, but it’s better to try and fail to find an advantage than to be left behind.  

 As Insights Distilled has previously reported, other FinServs are testing quantum in other areas of their businesses with varying results:  

Credit Agricole successfully completed two real-world experiments earlier this year that found it could achieve “faster valuations and more accurate risk assessments” using quantum techniques, while Banque de France is preparing to protect itself against encryption-breaking quantum tactics. Mastercard, meanwhile, is experimenting with ways to use quantum computing to improve its loyalty and rewards program, and HSBC, JPMorgan, and Ally have their own tests, too. 

17 Australian banks launched a new digital platform called the Fraud Reporting Exchange (FRX) that enables near real-time prevention tactics, which are particularly helpful for authorized push payment (APP) fraud, where victims get swindled into willingly sending money to bad actors under false pretenses.

It’s mateship in action: A group of banks including HSBC, ING, and Westpac are involved in a new effort in Australia to halt payments to scammers.  

The bank-funded Australian Financial Crimes Exchange launched a secure communication platform that provides near real-time fraud reporting, shared intelligence, and the ability to halt transactions for member banks.   

Previously, communication between banks would largely take place over phone calls and email. 

The FRX endeavors to stop fraud by allowing banks to better share information about potential bad actors and interrupt multiple transactions taking place as part of the same scam.  

This new platform is particularly crucial for mitigating APP fraud, where banks often deny culpability for refunds since victims authorize payments themselves. As consumer protection advocates turn up the heat on banks to provide reimbursements to victims of these scams, the platform aims to prevent people from losing money in the first place.

The FRX is a “world-leading initiative” and “means more and more scammers are going to hit a brick wall,” according to Australian Banking Association CEO Anna Bligh.  

In a trial of the platform, the time to resolve most scam cases dropped by more than half.  

In the United States, regulators have also ramped up pressure on banks to add protections and grant reimbursement for APP victims. Banks, in turn, have increased their customer education and have experimented with biometric technology. Australia’s new system models preliminarily effective another strategy. 

Truist’s new app has benefits for both itself and for consumers: It keeps a loyal audience logging in regularly while helping that group earn rewards and build savings. 

Truist’s innovation studio, Foundry, just released a mobile app called Long Game that rewards users for building healthy financial habits through prizes and education.  

“The ultimate goal is creating digital experiences that are fun and engaging, that make people love Truist and increase their financial wellness,” according to Linsday Holden, head of Foundry. The app’s trivia and savings challenges are targeted at people who are relatively early in their financial education journeys.

The game gives Truist, the 7^th largest bank in the US by total assets, a new way to keep its clients engaged at a time when digital banks are using higher interest rates to lure depositors.  

Ultimately, interactive financial literacy tools helps FinServs form stronger bonds with their clients, especially younger users whose loyalty they crave and who benefit the most from boosting their money knowledge. For example, Morgan Stanley is leaning on an education suite from fintech Greenlight while TD Bank has a virtual stock market game and a resource hub for kids called the Wow! Zone. 

Financial firms have begun testing how they can use generative AI for wealth management, engineering, document analysis, and personalized advice.  

Generative artificial intelligence – AI trained on enormous datasets that can create new content resembling human output – is set to disrupt financial services as we know it.  

“There’s a mad scramble right now to figure this out,” the CEO of Evident AI, Alexandra Mousavizadeh, told Insights Distilled, including pressure from board members and top executives.  

As part of this process, FinServs are crafting experiments to help build out their strategies and roadmaps. Our latest Insights Distilled report explores these uses cases and how they’re being deployed by your peers and competitors, including for wealth management advice and document analysis. 

For our analysis and expert advice, download the exclusive report here.  

AI is helping banks supercharge their ability to detect financial crime, adding context to sanctions lists, cutting down on false flags, and speeding up investigations.

Artificial intelligence is bringing more context to compliance, according to Ryan Schmiedl, chief data officer and head of trust and safety for JPMorgan’s payments division.  

“With the innovation going on with large language models, there’s a lot of opportunity in the financial crime space,” he said on stage during the Finovate conference in San Francisco. He gave an example of how LLMs could help algorithms better understand the context of a sanctions list:  

“With sanctions, most of the time you get a list with very little context to what you’re looking for other than a name, or vessel number, or particular company. And so you’re searching through a bunch of unstructured text,” he said. “In the old systems, if vessel number 138 was flagged, guess what? Every time you had ‘138 Main Street’ in the data, it’s a hit, right?” The latest algorithms can use context to parse out what’s actually meaningful and cut away “a lot of unnecessary friction” and false flags, Schmiedl said.  

Ultimately, the goal is to use AI to catch more fraud, faster: “There’s value in offloading very manual, repetitive tasks that don’t require a lot of human IQ, that have a basically consistent pattern,” he said. “We’re laser-focused on capture rate and precision: We want to capture a larger percentage of these malicious events, with better accuracy and fewer false positives.” 

Insights Distilled has previously covered the various ways that FinServs are using artificial intelligence to fight fraud, including through better know-your-customer checks and more comprehensive investigation reporting.   

Incumbent banks and fintechs alike want to understand how their features and experiences stack up against those of their competitors; this platform gives them a real-world look at all the digital tools on the market.  

Fintech Insights is winning customers by letting them compare every single one of their digital features to those of their competitors – and see what experiences they’re missing.  

The idea is simple: The company’s platform includes details about (and videos of) over 500,000 different “user journeys” – from onboarding to fund transfers – from hundreds of digital banks and incumbents. Customers can search the site by company or product to see all the features and functionality that their competitors offer. 

Traditionally, banks have only conducted benchmarking or gap analysis a few times a year, Fintech Insights executive Nickolas Belesis told Insights Distilled during the Finovate conference. But the platform allows them to conduct competitive analysis on the fly, leading to better product road-mapping and testing. 

By giving banks a clear-eyed, comparative view of their user experiences, the platform is helping them up their game and deliver better products. The firm’s clients include UBS, Bank of America, Fifth Third Bank, Zelle, ING, and US Bank, whose exec called the platform “an invaluable resource for our product teams in prioritizing our product roadmap.” 

“The teams have more confidence that the design of new or improved features will be best-in-class,” VP William Calice told Insights Distilled, adding that users at the bank have described it as “a digi-superpower” and “the coolest tool” they’d deployed at work.  

Fintech Insights updates its feature logs and videos every week and is always adding new banks and fintechs to its libraries, Belesis said.  

“We’re the gold standard of digital banking,” he added. “Everything is up to date.” 

Nymbus just raised fresh funding for its mission to help banks replace their legacy tech stacks, as smaller institutions and credit unions fight to stay competitive. 

A technology provider for banks just raised a $70 million Series D in a funding round led by Insight Partners.  

Nymbus aims to help financial institutions seize the benefits of digital transformation, without needing vast in-house tech resources. Its cloud tools ultimately help banks and credit unions evolve their operations and stay competitive. 

“It’s not just about surviving in the current industry; it’s about thriving and transforming it for the better,” chief financial officer Frank McAnally told Insights Distilled. “This urgency is what makes Nymbus’ mission more vital now than ever before.” 

Before beginning their relationships, banks and fintechs should establish quantifiable success metrics and make sure they’re aligned for the long haul, according to BNY Mellon and JPMorgan execs. 

There’s no magic formula or one-size-fits-all approach to crafting successful relationships, but BNY Mellon and JPMorgan execs shared their perspectives on working with fintechs during a panel at the Finovate conference. 

Every partnership begins after the bank has defined a clear need and concluded that it makes sense to buy a solution versus build one in-house, both execs said. From there, the banks do extensive research to select the right potential partners.  

JPMorgan’s outreach to fintechs has been very focused lately: “We’re doing fewer, but more targeted proof-of-concepts,” said Dora Matheidesz, executive director of fintech strategy at JPMorgan. “We don’t want to do POCs just for the sake of POCs, or just testing ideas. It takes a lot of work and effort for both the banks and the startups to get a POC off the ground.”  

As a POC begins, “it’s really important to set a quantifiable metric of success upfront,” according to Zakie Twainy, head of digital partnerships and enterprise innovation at BNY Mellon. That way, both sides have a clear understanding of impact and whether goals are being met.  

It’s always a green flag when firms come prepared for the bank’s significant due diligence, she added: “By coming to that process prepared, a startup shows a maturity level that indicates that they’re ready to work with a bank. And that’s really important.” 

Figuring out whether a firm is poised for growth is crucial, Matheidesz agreed: ““We want partners that will be able to support us for years to come and that will be able to scale more broadly,” she said. “They need to have the resources, the right people, and a product roadmap that we can be a part of. It’s really important for a partner to present that long-term view.”  

Startup Kasisto created a banking-specific large language model (LLM), which it says is more bespoke, easier to customize, and less likely to “hallucinate” false info than generalized AI tools – and Westpac is its first user. 

Westpac is increasing its focus on generative AI through a deepened partnership with chatbot developer Kasisto. 

Kasisto just announced Kai-GPT, a custom LLM trained on data and documents specific to the financial services industry (versus the broad training set of OpenAI’s model, for example). Its specialized approach will provide FinServ clients with a more accurate, transparent, trustworthy, and customizable GenAI experience, the firm says.  

To make the tool even more targeted, Westpac will also train Kai-GPT on its own proprietary content. Employees will be able to correspond with a conversational chatbot to enhance their work, whether in the mortgage lending process or for general customer service.  

The specialized, layered LLM will “formulate these really rich, wonderful answers, but in an accurate and concise way,” according to Westpac CTO David Walker. 

Westpac has worked with Kasisto since 2020 and co-led its $15.5 million funding round late last year. The startup also counts JPMorgan Chase, Standard Chartered, BankSouth, and TD among the customers for its original chatbot service.  

For more ways that FinServs are experimenting with this hot new technology, check out Distilled’s latest report.