March 14

Silicon Valley Bank’s implosion threatened software startups that relied on it, forcing financial services CIOs to take stock of the potential impacts on their partners. The situation highlights how important it is for execs to build backups into their technology supply chains. 

Silicon Valley Bank’s rapid fall will continue to have ripple effects throughout the banking and tech industry.  

Before US regulators announced plans on Sunday to protect SVB’s clients – many of which were tech startups, including some of Insight Partners’ portfolio companies – corporate leaders rushed to assess the stability of their vendors. They needed to understand whether there would be any impact on their firms’ own operations if tech providers in their supply chains needed to shut down because of SVB’s collapse.  

As a result, one key reminder emerged for those CIOs and other tech execs: Expect the best but prepare for the worst. When it comes to critical software, your firm should always have a contingency plan in place should something go wrong.   

For example, Magesh Sarma, CIO and chief strategy officer at AmeriSave Mortgage Corp., told The Wall Street Journal that the firm has back-up plans in case of vendor failures.  

“We have redundancy and fail-over in place for all critical services, because we cannot control what we cannot control,” he said. “It’s better to be prepared.”  

Figuring out a business continuity plan from the outset is key to any new fintech relationship. Even before the SVB fiasco, banks have realized that working with innovative, fast-moving tech startups involves a certain amount of risk. For example, Insights Distilled previously highlighted how Wells Fargo locks down its strategy for managing customer needs if a fintech winds down from the very beginning of a new relationship.  

“We figure out how we’ll ensure that – if something happens – it’s seamless to customers, that they can go on managing their finances,” Wells Fargo’s head of digital Michelle Moore said at the time. The bank obviously hopes that any startup it works with will succeed in the long run, but it still creates a plan for its demise.  

Running through worst-case scenarios is crucial: “My legal, risk, and compliance partners are my best friends,” Moore said.    

SVB’s fall is the second high-profile event this year to underscore the importance of backup plans: When a cyberattack crippled financial software firm ION in February, the disruption forced its banking and broker clients to resort to manual trades to keep markets whirring. 

Although quantum computing is still in its infancy, financial institutions can benefit from considering future use cases, setting up experiments, and skills-building. For Mastercard, that means seeing how quantum could help personalize rewards programs. 

Mastercard has partnered with D-Wave to research how quantum computing could supercharge its loyalty and rewards programs.  

Quantum – an emerging computing paradigm that promises to perform calculations at blistering speeds – is well suited to the challenge of sorting through the gobs of customer data that financial firms use to offer incentives to their customers. That’s why Mastercard has begun experimenting with how it could use quantum computing to help issuing banks and merchants better customize their loyalty programs. 

“Some of these retailers have customer bases in the hundreds of thousands, with hundreds of rewards programs,” Mastercard’s vice president of AI and machine learning, Steve Flinter, told American Banker. “So, how do you give which reward to which customer, and at what time? It’s really a hard problem to solve, even with the best technology that we have today.”   

Using data on payments, sales, redemption, demographics, and hundreds of other sources related to how consumers engage with incentives, Mastercard could help its clients shape their loyalty programs.  

Beyond its work with rewards, Mastercard also recently announced that it plans to issue “quantum-resistant” contactless credit cards that can maintain their encryption even when up against quantum computers.  

“Quantum computing is an emerging technology that can be revolutionary for our industry,” Flinter said. 

To that end, HSBC, JPMorgan, and Ally are also experimenting with ways to use quantum computing technology for their benefit, like improving the speed and precision of risk analysis. Meanwhile, Banque de France is preparing to protect itself against encryption-breaking quantum tactics and Credit Agricole just successfully completed two real-world experiments that found it could achieve “faster valuations and more accurate risk assessments” using quantum techniques. 

While money mule accounts don’t generate direct losses for banks, they can still have negative impacts, including maintenance costs and regulatory scrutiny. Banks should take advantage of advanced analytics and diverse data (including dark web intelligence) to help protect themselves. 

Money mules – people who receive and move money stolen from fraud victims – are particularly pernicious for banks. They’re often a key player in authorized payments fraud, money laundering, and other scams, but their accounts are difficult to identify (often because the mules themselves are unwitting pawns for criminals).   

A new survey by NICE Actimize found that financial institutions’ fraud leaders consider money mules one of their top five challenges. Similarly, more than 80% of fraud execs believe that more can and should be done to mitigate mule activity at their institutions.  

Banks have incentive to root out these accounts: They’re costly to maintain, aren’t profitable, and can expose FIs to regulatory scrutiny for enabling money laundering. While a mule account may not raise any red flags when it’s first opened, banks should rely on advanced analytics, behavioral biometrics, and diverse datasets (including dark web intelligence) to continuously monitor accounts, and flag potential risks.  

“Monitoring doesn’t stop at day zero,” the report recommends. “Data collected at the beginning serves as a solid foundation for continuous due diligence and monitoring. Think of it as a never-ending background check.” 

Flagging fraud and money laundering – including potential money mules – is one of the most promising (and well-funded) applications of AI in financial services; you can find more of Insights Distilled’s coverage of this critical topic here. 

As the world undergoes the largest intergenerational transfer of wealth in human history, financial providers need to offer the digital access and real-time transparency that younger clients demand. 

Wealth management is at a time of major transition, and providers need to ensure that their technology infrastructure and features keep up.  

That’s why Masttro, a wealth tech company focused on serving ultra-high-net worth families, just raised a $43 million round of funding led by FTV Capital, with participation from Citi Ventures.  

Masttro’s software uses advanced data processing and analysis to provide digital access and real-time visibility into client portfolios and total net worth. Its platform enables financial advisors and family offices to better and more efficiently serve their customers.  

“We like to say, ‘Why settle for 80% of your wealth being visualized?’ Managers – and end clients – should strive for a 100% view of wealth,” head of marketing Michael Melia told Insights Distilled. “Masttro is the all-in-one aggregator, synthesizer, and visualizer for every kind of asset class in every region around the world.” 

For example, Santander’s high-end wealth management division uses Masttro’s software to automatically aggregate its clients’ financial and non-financial assets, eliminating human error, saving the bank “hundreds of man hours,” and ultimately allowing its bankers to deliver better advice, faster.  

The software also helps advisors serve younger clients according to their preference: Digitally and in real-time. With an estimated $84 trillion in wealth expected to transfer to younger generations through 2045, it’s critical for wealth management providers to equip themselves with technology that allows them to adapt to changing expectations. 

Stakes are incredibly high for financial services firms undergoing digital transformations, and yet they often flounder. To boost results, tech execs need to create a culture of empowerment through incentives and clear messaging. 

Nearly all banks are using technology to rethink their processes, features, and operations, but the road to reinvention is bumpy: A stunning 70% of leaders report witnessing a banking transformation that has underperformed in the last five years, according to a new Tearsheet report. 

One of the key reasons for those lackluster results may be a culture of fear versus trust, and stagnation versus reorientation. 

After all, only 43% of execs clearly communicate to employees that unsuccessful experimentation will not adversely impact their career or compensation, according to Tearsheet. In other words, banks need to learn to fail faster.  

Teams from across the bank need to work together and be aligned on positive incentives, not negative ones. Beyond the nuts-and-bolts of new technology, that requires a mindset of experimentation, teamwork, and trust. As former Credit Suisse CIO Radhika Venkatraman previously put it to Insights Distilled: “If you want to disrupt yourself digitally, you must reimagine your data, operations, talent, and culture.”

Summed up another way by Tearsheet’s Rabab Ahsan: “A successful transformation is less about jumping on technological bandwagons and more about ensuring that clear roadmaps, communication across teams, and incentivization for everyone are in place.”