September 27

By combining vast swathes of data with fine-tuned risk management models, banks can accelerate legitimate transactions and flag suspicious ones, striking a balance between customer ease and safety. 

Deutsche Bank is baking an automated fraud detection system from Visa-owned Cybersource into its ecommerce solution for merchants. The tool automatically calculates a risk value for each individual transaction and will block those that meet a pre-determined risk level as potential fraud.  

The system, called Decision Manager, prevented the equivalent of $22 billion+ in potential fraud in 2021, according to Visa. By adding the tool to its platform, DB aims to make its online retail offering more helpful to existing clients (or more attractive to potential ones).  

“We combined the payment expertise of Deutsche Bank with the data and advanced technologies from Visa’s Cybersource for risk management and reduced the complexity of payment acceptance for our clients,” DB spokesperson Heinrich Froemsdorf told Insights Distilled, adding that it’s an optional value-added service that clients can choose depending on their own in-house fraud-risk management expertise.   

Along with Visa’s Cybersource, a slew of fintechs provide AI for fraud detection, including NetGuardians, Feedzai, and Featurespace, an Insight Partners’ portfolio company. 

Partnering with fast-moving fintechs can help incumbent banks roll out sleek digital tools to impress existing customers and win-over new ones.

If you can’t beat them, join them: HSBC just made a $35 million strategic investment in UK challenger bank Monese through its corporate venture arm.  

HSBC’s investment is just the latest example of a neobank-incumbent tie-up: In the past several years, BBVA invested $300 million in Brazil’s Neon, Goldman Sachs invested $50 million in digital bank Starling, and Santander led a $40 million investment in credit-focused Upgrade. 

“They essentially get outsourced product development,” Jonah Crane, partner at financial services advisory firm Klaros Group, told Insights Distilled of this investment strategy. “They’re bringing that more modern technology development by the fintechs in-house, as it were.”  

This model allows incumbents to better serve their entrenched customer base under their own brand, while helping challengers develop their platform-as-a-service model.  

Alternatively, Crane has observed that the relationship between fintechs and banks in the US is often reversed: Incumbents will power challengers behind the scenes, so the users know the fintech’s brand, but the big bank is also gaining new customers. 

Financial institutions are nearly unanimous on the appeal of a passwordless future, but there are many different approaches. Bank of America’s latest launch showcases a simple, creative way to bring smartphone-based biometrics to the web.

Bank of America wants to banish manually-entered credentials from its website for business customers, and it’s combining two popular technologies to make it happen.

Customers will now be able to use their smartphones to scan a QR code on the CashPro website, which will prompt a biometric scan of either their face or fingerprint on their phone (BofA has long enabled biometric access for its mobile apps). Once authenticated, they’ll be automatically signed in online.  

Following the pandemic-spurred onslaught of QR code usage, this launch represents a simple, creative way to bring a mobile app-centric capability to the web without requiring a complicated new process. 

Dealing with issues in trade settlement has historically been a fragmented process, where participants must manually resolve errors over email chains. The biggest players are investing in AccessFintech’s centralized (and secure) data management network because its collaborative workflows reduce the time and costs for all involved. 

By promising to streamline transaction processing, AccessFintech is winning converts: More than 100 organizations use its platform to share data and a slew of top financial firms just contributed to its $60 million in Series C funding.  

By making data exchange and communication easier between all the participants in a given trade, AccessFintech reduces manual work and human error, thus speeding up transactions and lowering overall costs. For example, after a year of using AccessFintech’s network, Citi and JPMorgan reported a 30% reduction in trade fails and a 76% drop in operations-related email traffic. 

AccessFintech recently expanded its network to include derivatives and syndicated loans, and the new funding will fuel further growth and expansion. The more players and asset types involved, the more useful the platform is for all. As BNY Mellon’s head of custody put it, “Democratizing data across market participants” reduces costs and improves settlement, which is critical to “the smooth functioning of the capital markets.”

Trade finance – which often still involves paper documents moving between banks, shippers, and exporters – is ripe for technological change. JPMorgan’s new partnership with Cleareye.ai digitizes the process and enables sophisticated automation. 

JPMorgan has partnered with Cleareye.ai to make trade operations and compliance more efficient and less risky. Through a combination of computer vision and natural-language processing, Cleareye.ai’s ClearTrade solution ingests documents and then analyzes and validates them based on algorithmic rules created to catch compliance and sanction violations or money laundering red flags.  

The product automatically creates reports that make it easier for trade operations analysts to do their jobs, drastically reducing processing times and human error. The platform will be integrated into JPMorgan’s system to “massively improve efficiency” for the bank and ultimately become part of its commercial trade processing tool.  

JPMorgan chose to work with Cleareye.ai after testing multiple technology providers, and head of trade Stuart Roberts told Finextra that Cleareye.ai stood out because its system was able to hit high efficiency ratios and learn and improve after mistakes.