Accelerate your Financial Journey with our

custom, optimized & scalable solutions.


About

Why Us

We Understand. We Analyze.
We Deliver.

Founded in 2005 and with offices in Miami, New York, and multiple locations in India, Indxx is a leading index provider delivering innovative products & services to the investment management community at large.

Indxx Capital seeks to help clients across the financial services spectrum stay ahead with its uncharted, intelligent, and flexible solutions enabled by its contemporary and pioneering technology.

Our USP

15+

Years of Expertise

100+

Domain Experts

50+

Technologies

5+

Global location

24x5

Coverage

100%

Client Satisfaction

Services

Model Analysis & Validation

We design frameworks that confirm the correctness, appropriateness & consistency of methodologies, data and calculation systems.

  • Model creation, back-test and validation
  • Input Data validation
  • Conceptual Soundness Test
  • Scenario Analyses
  • Output analysis and reconciliation

Parallel and Independent Model Reviews

We perform reviews and rebalancing for clients’ strategies, in parallel with them & independently, using multiple data sources and our state-of-the-art technology systems.

  • Daily Calculation & validation of levels
  • Selection, Weighting and rebalance
  • Input Data quality checks
  • Output composition quality control and reconciliation
  • Corporate Action Management
  • Dissemination & Publication

Data Governance and Research

We ingest, compare, validate & deliver multiple relevant and critical data points through standardized Golden Copies for downstream use, while also managing the entire Data value chain of clients - collection, storage, management, processing, quality, security & disposal.

  • Data Quality & Consistency
  • Data Compliance & Security
  • Corporate Actions & Events
  • Free Float & Shares Outstanding
  • Foreign Ownership Limits
  • Withholding Tax Rates, etc.

QA Services

We design & implement frameworks to test correctness of applications, calculation systems, websites, etc. using industry best practices, resulting in error-free software.

  • Requirement Analysis
  • Application Design Review
  • Testing Strategy & Approach
  • Website Permissioning & Login validation
  • Quality reports

Technology

We design and develop robust technical solutions through full stack development engagements, to automate, streamline and optimize various functions along the investment value chain.

  • Front-end, Back-end, Database & DevOps
  • Consultation-based tailored Solutions
  • Robust Design & Development
  • QA & Support
  • Reduced lead times and costs

Case Studies

1

Complex Model Development & Validation

We helped our client, a top 5 index provider, develop, test, validate, reconcile and operationalize 500+ index models that involved complex instruments like options, futures, & other derivatives.


2

Parallel & Independent Index Reviews

We helped our client setup independent & automated framework to review and rebalance portfolios, ranging from a few hundred to over 10,000 securities. This helped them ensure correctness, manage risk through quick reconciliation and better adhere to investors’ expectations.


3

Index Data Golden Copy

We helped our client identify & rectify discrepancies in its historical index data stored in multiple locations, that led to better client management as well as accurate product development and maintenance.


Complex Model Development & Validation

We helped our client, a top 5 index provider, develop, test, validate, reconcile and operationalize 500+ index models that involved complex instruments like options, futures, & other derivatives.

Problem Statement

  • Client had a suite of complex models that needed to be validated afresh or migrated from archaic frameworks like Excel/Informatica.
  • New models with increasing complexities and with derivative instruments as underlying were to be validated, a task which was impossible using client’s current framework.

Solution – Development of new model validation framework

  • Technology Identification
    • Scope of the project was assessed and model complexities were ascertained
    • Since data requirements were enormous, a framework built on new-age technology was imperative
    • MATLAB was selected as the choice of framework owing to existing libraries, and customer support
  • Development
    • Using MATLAB and SQL procedures, an initial set of code libraries were created for generic re-usable functions such as data retrieval, input/output, publication, etc.
    • Model-specific rules were then coded for each investment strategy, and the models were validated against the client values
    • Use of MATLAB afforded scale and efficiency, which enabled validation of models of even higher complexities than before
  • Maintenance
    • The service offering included regular operational and maintenance services
    • Since all these models are running live, a dedicated operations team looks after on-the-go issues pertaining to underlying data, model rule changes, resulting values, etc.

Achievements

  • A team comprising developers and domain experts was setup in under 15 days, and became operational in under a month
  • Over 500 such complex models have been successfully developed and tested, and are being currently maintained regularly
  • Entire development and maintenance run by Indxx, allowing client to focus on business development and sales efforts

Parallel & Independent Index Reviews

We helped our client setup independent & automated framework to review and rebalance portfolios, ranging from a few hundred to over 10,000 securities. This helped them ensure correctness, manage risk through quick reconciliation and better adhere to investors’ expectations.

Problem Statement

  • Client had around 12000 securities in initial pool to review each review/rebalance period.
  • There was no documentation of the rules/exceptions followed by 3rd party calculation engine.

Solution – Development of Review Tools

  • Model Validation
    • Setup standard libraries for selection and weighing rules.
    • Setup of data APIs to get processed data.
    • Setup of a master Python code covering calendars and investability checks.
  • Develop and Test
    • Master Python code run once every day through automated scheduler.
    • Automated scheduler fetched calendars and identify the calendars for which review process is active.
    • Performed review and rebalancing for all the indices linked to active calendars.
    • Internal quantity checks and controls on reviewed and rebalanced portfolio were implemented.
  • Parallel Comparison & Reconciliation
    • Automated comparison of client’s and Indxx files was executed.
    • Rebalanced and reviewed portfolios were sent to SFTP location where they could be ingested from by client.
    • Generation of a detailed discrepancy report.
    • Detailed analysis outlining source of differences and corrective action proposed.

Achievements

  • Generating reviewed and rebalanced portfolios along with a detailed report with entire universe having all the data points used in portfolio construction, with exclusions and calculation at each stage.
  • Discrepancies were analyzed and root cause analysis and remedial action plan was proposed.
  • The developed tools that helped to automate the review/rebalance process saved the client a huge 42% on operating costs.

Index Data Golden Copy

We helped our client identify & rectify discrepancies in its historical index data stored in multiple locations, that led to better client management as well as accurate product development and maintenance.

Problem Statement

  • Client received a request for historical data of flagship indices from fund managers, HNIs and family offices.
  • There were severe discrepancies in historical data with multiple versions for same dates at different locations.
  • This was impacting new product development where historical compositions were used as starting universe, and prices & FX rates from historical files were used for simulations.

Solution – Creation of a new Data Governance framework

  • Governance Process
    • Scope of the project (DBs, time period and indices) was defined.
    • Data reconciliation process was created.
    • Requirement document was created for development team.
  • Development
    • Using Python and SQL procedures, governance process was automated presented for analyses by data governance team.
    • Tools were created for automated comparison between different DBs and conflict resolution mechanisms were suggested.
    • Except for special cases (not defined in requirements and/or needing further root cause analysis), golden copy process could be completed for nearly 10,000 indices in 1 day.
  • Golden Copy
    • Index compositions, divisors, levels, calendars & index market cap were validated for parent indices.
    • Securities’ reference data, open prices for PR, GR and NR versions, close prices, market cap, free float and exchange rates were validated for securities in parent indices.
    • Iterative process was run to fix new/existing discrepancies at each iteration.
    • All special cases were handled per guidelines from stakeholders.

Achievements

  • Client made nearly US$ 1 million within 3 months of successful implementation of data governance framework.
  • Backtest of new products were more accurate as correct data for historical compositions and prices were used by backtest application.

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