Fenergo is busy infusing its Client Lifecycle Management software solutions with intelligent technologies like Machine Learning and Robotic Process Automation to deliver a better client experience across the lifecycle.
Machine Learning (ML) is an application of artificial intelligence (AI). It is a statistical process that enables software to learn through finding patterns in data. ML can be supervised (users provide feedback/validation) or unsupervised (tries to identify patterns by itself) to improve accuracy. ML can enhance evidence-based learning to make smarter, more informed decisions. It also delivers greater business efficiencies through reduced risk, improved accuracy and improved productivity, and enables financial institutions to discover new insights across data silos.
Robotic Process Automation (RPA) is the use of software robots to do basic tasks across applications just as human workers do. The software robot can be programmed to follow a workflow with multiple steps and applications. RPA enables financial institutions to automate repetitive, non-value adding and data intensive tasks, giving employees back time to focus on higher value client-centric activities whilst improving accuracy, reducing risks, and reducing total cost of ownership.
Here are a few examples of what we’re working on:
- Core Banking Up/Downstream Integrations: RPA is helping to further automate ‘swivel-chair’ activities across disconnected applications (e.g. legacy applications) such as downstream integrations with core banking systems.
- Hierarchy Manager: In early 2019, Fenergo will be officially launching its new Hierarchy Manager solution, which delivers enhanced performance, data capture, visualization and interactions across the client lifecycle.
- Document Automation: Machine Learning is helping to auto-classify data, document types and meta-data. It can enhance data capture, extraction from documentation and processing e.g.populating fields with data obtained by either Optical Character Recognition (OCR) / Intelligent Character Recognition (ICR).
- Document Understanding: Both Machine Learning and Natural Language Processing (NL) technologies are helping to automate the interpretation and translation of unstructured documents into structured data (e.g. hierarchy data sources, annual reports, funds prospectus, ISDA docs etc.).
- AML Screening: Machine Learning is helping to lower the number of False Positive hits in the screening process through probabilistic matching algorithms and supervised learning.
Ultimately, the reason why financial institutions choose Fenergo is because our solutions deliver true return-on-investment. We will continue to invest in leading-edge technologies to accelerate operational processes and deliver more efficiencies. Some of our core ROI benefits that we currently offer financial institutions include:
- 82% faster client onboarding;
- Ability to re-use 75% of existing client data/documentation;
- 37% headcount efficiencies on KYC reviews;
- 80% reduction in regulatory change management costs.