Customer data to price, target and market their products and services
General industry benefits
Financial Services (big) data management provides many benefits, including:
· Customer profiling
· Tailoring the customer experience to each individual
· Understanding how customers buy
· Identifying opportunities for upselling
· Reducing the risk of fraudulent behaviour
Use Case Financial Services
Ostrica welcomes interactive, self-sustaining data insights with nucleoo
Future-proofing investment management with enhanced automated reporting.
An asset manager utilising data insights to offer investment portfolios with optimally balanced return and risk.
Optimising accurate data oversight to facilitate intelligent investment strategy
Asset managers rely on crunching data from myriad systems day to day. Excel is often the go-to tool, despite being far from infallible. Ostrica also aimed to minimise time spent preparing data to plug into its advanced investment strategy algorithms, facilitating their usability for both software developers and portfolio managers.
Digesting data for valuable, robust and interactive investment insights
nucleoo was deployed to create Ostrica’s Single Source of Truth, reducing dependency on high-risk Excels and enabling the firm’s non-technical business users to leverage advanced algorithms. Near real-time SSOT data transforms static, time-consuming fund reports into more accurate, interactive business resources.
Increased efficiency and lower risk in a more robust, self-sustaining internal data system
nucleoo’s SSOT ensures Ostrica employees throughout the firm have consistent access to the latest data, creating a resilient, reliable system. This is able to function independently of (while in tandem with) internal employee know-how, empowering Ostrica to keep its clients up to date with the very latest investment analysis.
Our take on this
“With digital transformation a must for banks wishing to stay in business over the long haul, banks must address a variety of challenges – e.g. rising data volumes and user demands for data – in order to become the data-driven enterprises they need to be.”