HAWK:AI and BANKSapi enter into strategic partnership
Munich, Nov 16, 2020 – Customers of the open banking provider BANKSapi can now benefit from the anti-money laundering software of HAWK:AI. It can be flexibly integrated into the processes of BANKSapi.
The RegTech company HAWK:AI delivers its AML-CFT solution to BANKSapi as Software-as-a-Service. Besides fast integration and flexible workflows, the combination of conventional filters and machine learning is the core functionality in the suspicious case detection of the platform. HAWK:AI breaks new ground in money laundering prevention by analyzing large amounts of data in the cloud - even across institutions as in the BANKSapi use case.
As a BaFin-regulated payment institution, BANKSapi is obliged to fulfill requirements for the prevention of money laundering (AML) and terrorist financing (CFT). Through the cooperation with HAWK:AI, transactions can be monitored in real-time and suspicious cases can be identified, processed, and documented more efficiently. BANKSapi thus underlines its claim to innovation as an AI pioneer of the Banking-as-a-Service providers.
HAWK:AI will use BANKSapi's AI/Connect module, which enables the accurate categorization of account transactions to improve AML/CFT recognition rates. BANKSapi uses computer linguistics based on neural networks, as they are also used by big-tech companies.
"We are very pleased about the partnership with BANKSapi. In the race against organized crime, cooperation between technology providers is crucial to protect customers and the financial market in general. In particular, the use of both companies' technology at a central point where payment and account information from several institutions converge is the key to success. Our cooperation shows once again the need for better AML/CFT work in payment transactions, as we already serve in many places in the market" explains Tobias Schweiger, CEO and co-founder of HAWK:AI.
Felix Baaken, co-founder and CPO of BANKSapi, adds: "As a payment institution we are committed to the same standards in money laundering prevention as banks. However, the implementation of these standards to fight organized crime is relatively new for payment institutions. We have found a strong partner in HAWK:AI: This solution, which can be integrated quickly, will enable us to investigate suspicious cases faster and more thoroughly in the future. This way, we will be able to live up to our claim of making payment transactions a bit more transparent and secure.”
About BANKSapi Technology GmbH
BANKSapi Technology GmbH is a banking-as-a-service provider based in Munich. The company provides an API that, once implemented, allows users to access their accounts, credit cards, home loan and savings contracts, and custody accounts using the contractual partners' front-end applications. Banks, insurance companies, fintechs and brokerage companies are given the opportunity to redefine banking services, improve bancassurance services and increase the everyday relevance of their own offers. The technology is hosted in noris networks' high-security data center and meets the highest standards of data protection and IT security. BANKSapi Technology GmbH is backed by a team of founders and the B2B Company Builder Finconomy AG.
Find more information at www.banksapi.de / Twitter / LinkedIn
About HAWK:AI GmbH
HAWK:AI supports financial institutions in AML/CFT transaction screening and monitoring. The solution is built as a cloud-first, Software-as-a-Service offering, delivering maximum flexibility and allowing for modular, fast implementation (and even faster piloting).
The product range includes detection of suspected cases in Sanction/PEP/embargo screening as well as a full set of classic AML rules. In addition, HAWK:AI offers modules based on Machine Learning, with two objectives: First, the documented re-qualification of rule-based suspicious cases in real-time, making possible the auto-closing of False Positives. Machine decisions are based on learning from past and ongoing case decisions. Second, HAWK:AI identifies crime patterns and anomalies, based on deriving account-level signatures to allow for outlier detection. In addition to serving a single financial institution, the configuration can be extended to include transactions from other financial institutions – to address better network-level detection rates and facilitate information exchange.
To the user of the software, case investigation and configuration tools are provided in a state-of-the-art, browser-based User Interface. The same User Interface also provides access to audit trails on case level, detailing any machine decisions as well as all human interaction