A Peek into the Heart of Our Technology
Built using a distributed computing framework, the Tookitaki analytics platform and suite of proven machine learning-enabled software applications deliver end-to-end solutions and support multiple stakeholders across anti-money laundering and reconciliation space in the overall regulatory compliance value chain.
Provides actionable recommendations and insights in the reconciliation and AML process workflows which improves the operational efficiency of the analyst and the investigation teams.
(data scientists and analytics teams)
Provides detailed model management and audit capabilities to the analytics team so that the team is prepared to handle business and regulatory deep dives.
Applications: Provides smarter actionable insights and facilitates efficient decision-making.
Anti-Money Laundering Suite (AMLS)
A client application that enables a workflow to handle alerts management across monitoring and screening programs.
Reconciliation Suite (RS)
A client application that enables a workflow to handle automated matching and exceptions management across applications in financial institutions.
Data Science Studio (DSS)
A client application that enables end users to work with data and build machine learning analytic flows at scale.
Analytics Platform: Supports comprehensive analytics infrastructure and services for applications.
Pre-packaged connectors for various data sources make Tookitaki software adaptable to various enterprise architectures and up-stream systems. Well-designed REST interfaces and detailed integration guides make it easier for downstream applications to consume the output from Machine Learning pipelines.
Dynamic, multi-layered clustering and anomaly detection combined to produce superior results.
Scheduled supervised models blend the latest insights with historical data to adjust to changing data patterns and keep your system performing at its peak.
We ensure sustainability of solutions with auto model evolution and consistency in predictions accuracy over a period of time. With advanced self-learning algorithms that incorporate incremental changes in data, leveraging a champion-challenger framework, we make sure to keep the models updated with the ever-evolving data and business scenarios.
Making a decision is as important as understanding why that decision was made. Tookitaki demystifies modern machine learning and gives you the knowledge and tools to outperform your competition. Our solutions feature a ‘Glass box’ audit module that brings algorithmic transparency by providing thorough explanations for predictions.
Helping identify complex money laundering schemes by looking beyond simple transaction monitoring and understanding the multiple layers and players in modern criminal financial networks.
Enterprise Data Infrastructure: Ensures scalability, flexibility, security & faster time-to-market
Built with distributed data parallel architecture, leveraging Spark and Hadoop ecosystem projects, Tookitaki software simplifies performing end-to-end machine learning on enterprise workloads. The system is horizontally scalable to move hand-in-hand with ever-growing datasets. With In-Memory analytics, enterprises can run machine learning for most complex business use cases.
Tookitaki software integrates seamlessly with enterprise security mechanisms to facilitate single sign-on (SSO) and audit log monitoring. Services ranging from data security in-transit and at-rest, role-based authorization, granular permissions model and admin panel are pre-bundled with each product deployment. Our system facilitates enforcing ACLs starting from the application layer to all the way down to the Hadoop layer.
Tookitaki software comes with flexible deployment options on both cloud and on-premise environment. Organizations can choose their deployment environment and decide on CPU clusters, storage, load balancers, etc.
Optimum Security for Clients
Tookitaki is System and Organisation Controls (SOC) certified in validation of the operational efficacy of the controls we apply to process users’ data and the confidentiality of the data processed by our systems.