March 7

Customer obsession needs to come from the top. Digital strategy execs should marry data with a person-first mindset, rigorously monitoring feedback to keep a constant pulse on how clients feel, according to BofA’s David Tyrie.  

Bank of America’s chief digital and marketing officer, David Tyrie, pairs his morning coffee with customer feedback.  

The exec uses BofA’s “client imperative” dashboard every day to dig into an overview of customer activities, interaction ratings, and any complaints. 

“My first morning coffee goes with looking at what’s happening,” he told The Financial Brand. “Are people happy with the experience they’ve had over the last 24 hours? What things are customers saying need to be improved? What things are missing that they wish they had from us?” 

Tyrie’s routine illustrates his focus not only on the bank’s digital IQ, which encompasses its tools for online and mobile banking, but its EQ (or emotional quotient), which represents how those tools make customers feel.  

He posits that this often-overlooked aspect of digital transformation is ultimately more important than the nuts-and-bolts of how a bank’s technology works. Executives should have an easy way to understand EQ – both general trends and hyper-specific issues – on a regular basis. By starting his day with the imperative dashboard, Tyrie makes client experience his north star.  

“Customers put a much greater premium on how your bank, as an organization, makes them feel. It’s almost like how a doctor with a good bedside manner makes a difference,” Tyrie said. “I don’t think you can over index on how customers are feeling.” 

While cloud computing lets big financial firms quickly scale their IT capabilities, its costs can spiral out of control. Tech leaders need best practices for monitoring and optimizing their budgets.

The cloud frenzy is starting to wear off as companies ogle their bills amid ongoing budget tightening.  

For the first time in over a decade, spend management ranked above cybersecurity as the top challenge enterprises face with the cloud. So how can big financial firms keep costs under control?  

While there’s no one answer, execs at major financial institutions have weighed in on their own tactics.  

For example, Jack Henry CIO Rob Zelinka told The Wall Street Journal that his team scores discounted rates with multiple cloud providers by committing to a certain amount of usage, which requires it to hyper-accurately forecast its compute, so it doesn’t go over (or too far under) its commitments. 

“The last thing we want to do is leave money on the table,” he said. 

Wells Fargo holds daily meetings to review a detailed dashboard that showcases expense trends and identifies anomalies, which helps the team determine if there are workloads that can be paused during off-hours.  

Meanwhile, Capital One told Insider that it uses a tool that automatically moves less-used data into cheaper tiers of storage, which helped it decrease its AWS storage costs by 35%. 

Recent IDC research predicted that 70% of enterprises will become more adept at managing their cloud spend by next year. How is your firm reducing cloud costs? Let us know your tactics by replying to this email.  

Washington Federal wants to help other banks partner with fintechs, so they can better compete with larger rivals – and it’s the latest financial firm to bet that its homegrown tech tools will reel in external customers. 

Washington Federal – known as WaFd Bank – launched a separate firm to help other regional and community institutions create more consumer-friendly digital experiences.  

Washington Federal originally created the unit, now dubbed Archway, to advance its own tech goals, but realized that its learnings and tools could have a wider industry impact. Archway’s platform makes it easier for banks to consolidate data from disparate systems and build or integrate other apps, like budgeting tools, voice chat, or AI.  

Ultimately, this service helps smaller regional banks more easily up their tech chops, so they can offer the experiences that customers expect from national competitors with bigger innovation budgets.  

“Archway provides a platform that hooks into the services these banks are looking for, and the team has the experience to know the roadblocks – technological and cultural – that need to be overcome,” president Dustin Hubbard told Insights Distilled. “Other solutions are agnostic of industry and most community and regional banks don’t have the inhouse development expertise to effectively deploy them.”   

Archway just announced $15 million in funding from WaFd, as well as venture capital firm Madrona.   

There are two trends at play here:  First, the need for abstraction layers to help banks take advantage of cutting-edge tech (similarly, a firm called Sandbox Banking just raised seed funding to be the Stripe of fintech integrations). Second, financial firms’ growing realization that the highly specialized nature of their software means they can successfully sell it to other banks.  

For example, ING recently spun out its homegrown regtech software, Banco Santander is partnering with Google to sell technology it created to help move mainframes to the cloud, and Capital One productized Slingshot, software it originally created to manage its own use of the cloud data tool Snowflake.    

As artificial intelligence usage swells within financial firms, they’re woefully behind on ensuring that the tech is deployed safely. Execs need to be rigorous about maturing their responsible AI strategies.

Financial services firms need to drastically increase their focus on responsible AI, according to a recent survey by industry giant FICO.  

The survey found that 27% of organizations are yet to start developing responsible AI capabilities and only 8% describe their responsible AI strategy as “mature.”   

Responsible AI standards encompass a firm’s commitment to making sure its AI systems are explainable and auditable, which, in turn, reduces reputational or regulatory risks and protects customers.  

“Many AI systems lack a way to trace or explain how they make specific predictions,” according to Insight Partners’ managing director, Lonne Jaffe. “This makes it hard to test these systems and also makes it difficult for these systems to engender trust and meet regulatory requirements.” 

Companies like Insight portfolio firms Fiddler and Zest AI have emerged to manage the process of creating explainable and responsible AI. After all, ethically monitoring and managing these systems should be non-negotiable:

“It’s just part of the cost of doing business,” State Street managing director, Dan Power, told FICO. “If you’re going to have models, you’re going to have to govern them, and monitor them, and manage that evolution.” 

While the study found that financial firms are generally behind on self-regulation, they are treading carefully when it comes to one of the buzziest new AI applications, ChatGPT: A handful of banks have banned employees from using the tool.  

As threats rachet up, banks’ fraud investigation teams need to lean on AI-powered tools to help them more efficiently prioritize high-risk issues. 

Citi Ventures and S&P Global just contributed to the $23 million funding round of Quantifind, a risk management startup that counts four of the world’s largest banks among its customers. Quantifind uses AI to flag anti-money laundering (AML) and know-your-customer (KYC) risk signals and hidden patterns amid an increasing amount of data.  

Tools that automatically detect and triage issues can reduce costs and boost efficiency. For example, one of Canada’s biggest banks said that its investigations experienced upwards of 40% productivity gains using Quantifind’s tools.  

“AML-KYC operational costs continue to increase every year,” Quantifind COO Graham Bailey told Insights Distilled. “A complete automation solution that leverages AI to fully capture the value of external data in detecting, assessing, and investigating risk can help turn the tide.”  

Thanks to AI’s specialty in pattern matching and anomaly detection, a swathe of startups has emerged that use machine learning to fight fraud – including Chekk, Symphony AI, and Insight Partners’ portfolio company FeatureSpace.