generating Digital Alpha for Asset Managers
Improve operational efficiency and reduce costs with digitalization
Generate impactful insights from advanced analytics and new sources of information
Why operations and technology costs doubled in the last 10 years?
INCREASE IN COMPLEXITY
Increased complexity – of financial markets, investment techniques, products, distribution, and regulation
EXPANSION OF LEGACY SYSTEMS
Manage complexity by expanding and patching legacy platforms
GROWTH CONSTRAINTS AND HIGH COSTS
Not optimized for growth in the digital era and outsized increase in operations and technology costs
Digital leaders are in the top decile in each of the following three dimensions
Manage a two-speed IT architecture, to carefully stage migration to new digital platforms mitigating the risks
data & ANALYTICS
Generate insights from data with real-time data pipelines, machine learning and artificial intelligence
Fundamental process redesign and automation with intelligent process automation
Digital Alpha Levers
Real-Time Data and Analytics
Faster Deployments and Auto Scale
One Version of the Truth
New Sources of Information
Improved Data Quality
Timely Access to the Insights
Data Engineering and Analytics Capabilities
Manual and Routine Tasks are Automated
Integrated Analytics and Operational Workflows
End to End Auto Reconciliations
Self Service with Conversational Digital Assistants
Our Solution Accelarators
Build API gateways and microservices to increase the organization’s ability to provide cross-unit and cross-application functions.
Through the use of microservices, business groups could take advantage of applications and assets previously available to only one group or the other and could improve their collaborations on hybrid projects that involve both groups’ assets.
The two-speed model puts desired business capabilities as a central factor for determining which parts of the enterprise architecture—that is, which technologies, working groups, and processes—should be on a fast track and which should remain steady state; bringing order and accountability to digital-transformation programs.
By using a two-speed IT model, instead of deploying a “big bang” approach to change, a company could carefully stage its migration to new technologies and digital ways of working, thus mitigating its risk of failure.
CI/CD and Data Pipelines
Organizations get significant value by adapting CI/CD and Data Pipelines.
Improvement in time to market
Reduce the average number of days from code completion to live production
Reduction in cycle time
Eliminate wait time, rework and non-value add work through standard processes and automation
Improvement in productivity
Reduce the number of DevOps handoffs per processing activity through improved development and operations communication
Being able to see problems before they affect functionality, being able to look at the bigger picture of how applications are working
3 main pillars of observability:
Metrics are a great and easily implemented way to get started with observability, and the data they provide helps start the context-building process.
Traces can be used to quickly determine code behavior and pinpoint many performance issues, and also give you a lot of control over what you measure in your functions, and are great for recording data specific to the problem your function is trying to solve
Logs tend to provide a lot of data that can’t be easily captured in metrics, and often provide a lot more context to those trying to debug an issue in their code
Decision Support System
A common interface for data, analytics, alerts/notifications, and decisions workflow operations across the value chain, providing the consolidated view needed for improved decision-making risk management and compliance as well as reducing dependency on third-party administrators.
New Information sources
The holy grail in finance has always been finding new, authentic and superior sources of information to gain competitive advantage.
We help asset managers manifest this quest by tranforming public and internal unstructured data sources to structured data enhancing their models
Anomalies in data must be quickly identified to take appropriate action, unaddressed it could lead to incorrect or sub-optimal decisions
An anomaly detection solution that can seamlessly integrate with your applications and data pipelines system will significantly enhance the confidence in the information used in decision making
The framework to build advanced analytics, industrial-scale solutions to exploit data for authentic business insights, and vastly improved decision making.
Best Insights live at the boundaries between data sets
Automation takes the robot out of human
Automation is not a tale of machines replacing humans, but of machines complementing humans
ROI of automation implementations varies between 30 and as much as 200 percent in the first year
Reduce the interface complexity of the systems via a hierarchical Web Service stack that reaches from the lowest technical granularity needed to the domain-specific granularity needed by the domain experts
Reconciliation for investment managers means that their records reflect their needs by accurately accounting and adjusting for differences with custodians and/or fund accountants.
With flexible technology and customized interfaces, this can be achieved daily through a highly automated process, placing less stress on human resources while providing other benefits.
Communicate with people, systems and things with a conversational UI that lives in the enterprise communication channels
Interact when needed – proactively, scheduled, on-demand
Complete simple tasks to highly complex workflows
Solutions & Insights
The solution that enables the building of new structured datasets from unstructured text data to power up the models and/or to make end-to-end automation possible
RIG is a data pipeline that transforms unstructured text data to the structured data. Businesses can leverage the data buried in various documents and tie them with their operational and analytic systems. The RIG is used both in the context of end to end automation and generating better decision making insights
Case Study Feature
A comprehensive data solution for our telecoms client
How we provided a 360˚ view of our customer in the insurance industry using Advanced Analytics, Machine Learning and Data Mining
Align your business with how your ecosystem to meet the customer dynamics