Explore Our Technology Case Studies
Vichara has helped multi-billion dollar investment managers, global banks, hedge funds et al, to leverage cutting-edge technology solving complex problems across business functions
PORTFOLIO MANAGEMENT REPORTING FOR A GLOBAL INVESTMENT MANAGER
Client
- Multi-strategy investment manager
- $45B+ AUM across multiple asset classes
Challenges
- Lack of an enterprise portfolio reporting system for various asset classes and strategies
- Manual portfolio performance analysis
- Inability to view market data & indices corresponding to portfolio holdings
- Lack of consolidated reporting across all product groups
COMPENSATION SYSTEM FOR AN ALTERNATIVE INVESTMENT MANAGER
Client
- Multi-strategy alternative investment manager
- $83B+ AUM across multiple asset classes
Challenges
- Lack of an incentive and compensation information system
- Information manually maintained in spreadsheets
- Unable to roll-up to a high-level view of the grants for particular funds or group of funds
- Considerable work gathering consolidated data across spreadsheets
- Unable to report detailed views of the data
- Spreadsheets not tied to any legal documents
MORTGAGE RISK REPORTING FOR A REAL ESTATE INVESTMENT TRUST (REIT)
Client
- Mortgage Real Estate Investment Trust (REIT)
- $400M+ AUM across multiple asset classes
Challenges
- Lack of a central system to keep track of risk information
- Manually maintained spreadsheets created from 3rd party risk systems
- Manually generated risk reports
DATA WAREHOUSING & SURVEILLANCE REPORTING FOR A CREDIT HEDGE FUND
Client
- Credit focused hedge fund
- $5B+ AUM in structured products
Challenges
- High turnaround times for data processing and analysis
- Various data sets required for reporting in disparate databases
- Inefficient ETL processes
- Lack of canned reports
- Frequent outages and delays in reporting
SECURITY DATA SERVICE FOR A GLOBAL INVESTMENT BANK
Client
- Major global investment bank
- Fixed income technology group
Challenges
- Inflexible legacy system with high maintenance cost
- Redundant data design
- High costs for structural change/updates to data
- Common business logic code duplicated across multiple asset classes
- Continued performance degradation
- Lack of documentation