Code Willing Enters into Strategic Partnership with Phitopolis

Code Willing and Phitopolis partner up to bring the best financial data management technology and market data feed handlers. to clients all over the world.

Code Willing, a leading financial data management service in the fintech industry, announced today that it has formed a partnership with Phitopolis, a high-end technology company located in the Philippines, to assist in the software development process and to extend the global reach of Code Willing’s data services.

According to Code Willing, the duo has already successfully completed several proofs-of-concept that will enable Code Willing to utilize the latest technology to deliver better results to clients from their data services. The company further explained:


This allows Code Willing’s existing and future clients to leverage the improved performance of our services. They will get reliable results so that they can continue to focus on building strategies and trading.”


Code Willing also noted that the partnership aims to deliver the best-of-breed hardware and software solutions to clients that need market-leading latency and performance as well as global scale and coverage from their latency-sensitive trading applications. The two companies will work together to identify opportunities to bring the technology to market through Code Willing’s range of data management services, market data feed handlers and analysis tools. While sharing more details about the partnership, Mark Walbaum, Chief Technology Officer and Co-Founder of Phitopolis, stated: 


This partnership with Code Willing aligns with our strategy to provide the latest and greatest technology to users all over the world. We are focused on providing developmental and operational support to Code Willing. We have an experienced and talented team so that Code Willing can reach new heights.”


Baron Davis, CEO of Code Willing added:


We are delighted to be working with Phitopolis as Code Willing continues to focus on providing clients with flexible and transparent high-performance solutions for their latency-sensitive trading strategies. Leveraging Phitopolis’ multi-talented team to accelerate and enhance Code Willing’s data management offering is only the first step. We expect that this partnership will be the first of many opportunities to further enhance the data services being delivered to Code Willing clients.”


About Code Willing

Code Willing is a leader in data management solutions for the financial industry. Built on 20+ years of experience in fintech and trading, Code Willing offers data management services, cloud analysis tools, low latency market data feed handlers and scalable high-performance file storage. For more information, please visit www.codewilling.com. Follow on Twitter @codewilling.


About Phitopolis

Phitopolis enables financial companies to evaluate and run multiple Big Data solutions quickly, simply, reliably, securely and cost-effectively. Phitopolis is committed to delivering purpose-built Big Data solutions and services for the management and integration of commercial and proprietary technologies across multiple platforms. For more information, please visit www.phitopolis.com.

The 3 Most Common Data Management Challenges in the Financial Industry

Financial institutions look to grow their revenue by reducing risk, cutting costs, and making wise business decisions. Business decisions increasingly rely upon volumes of data which can pose serious production challenges in areas including data ingestion, data quality, and data production.

Production Challenges

If these problems are not overcome, they will become detrimental to your business by unnecessarily wasting time, man-power and money.

1. Manual Data Ingestion

It can be difficult and time-consuming to track and ingest so much data from so many vendors. Leveraging an automated approach can help re-focus your efforts towards strategy and trading if much of your organization’s time and resources are committed to this. Thoroughly tested extract-transform-load (ETL) pipelines managed by an experienced operations team coupled with meaningful and well-laid-out dashboards make data ingestion easy providing your team with confidence and a strong foundation necessary to build a performant data analytics system.

2. Poor Data Quality

Not having the proper analytics is like steering a ship blind. Poor data quality is just as bad if not worse. If you cannot rely on your data for accuracy then you will not be able to rely on your forecasts drawn from that data. Data quality should be built into the data production pipeline early rather than later so issues can be found, marked and fixed before production data sets are built.

Cleaning data draws focus away from prime goals. Usage of machine learning and other statistical approaches can put your team back in the business of trading confidently knowing that your data is of the highest quality.

3. Slow Data Production

Many financial firms are still working with legacy software that is not geared for today’s data volume. Processing large data volumes quickly will require new techniques such as:

  • Parallelization across many nodes
  • Vectorized processing
  • Distributed file systems
  • Efficient file formats such as Parquet and HDF
  • Pattern-based (machine learning) and statistical algorithmic approaches
  • GPU and other SIMD techniques

It will be difficult to keep up with increased volume, variability and breadth of data in the future if these techniques are not implemented.

The Outcome for Financial Firms

If these challenges are not met, financial firms will experience inefficiencies during all phases of their ETL. Problems that arise from manual data ingestion will only be exacerbated by a slow production pipeline. Without advanced customized software, your data will be of lower quality, more difficult to maintain and contain less actionable insights. Without better reliable data quality processing, you won’t be able to detect anomalies. All of this together produces bad data and leads to higher data management costs, increased risk and ultimately revenue loss.

This is definitely not the desired outcome, but it is not easy to adapt to an ever-changing technology landscape. Most financial firms do not have the man-power, time or resources to easily address these issues. That is why there are third-party companies that exist who have already solved these problems.

Third-Party Data Management Solution

Technology and the financial industry landscape are evolving quickly making it difficult to keep up with while maintaining your core business. With the help from a financial data management company, one with a proven track record and decades of experience such as Code Willing, you can stop fighting with your data and start leveraging it.

Only a few fintech firms provide end-to-end management of data production resources at this time but with more on the rise. They have a staff of Data Scientists, Data Experts and DevOps engineers that have experience ingesting cleaning, organizing, building and cross-referencing financial data sets from many vendors. Some have already developed complete solutions to these common data management problems and can help jump-start your technology and workflows into the future right now allowing your team to spend less time on administrative tasks and more time closing deals.

End-to-end financial data management firms can ensure a high-quality data product complete with analytical dashboards to provide insight into data content and the tools necessary to allow your team to extract targeted data allowing for decisions to be made that reduce risk, lower costs and increase revenue.

The data revolution is here and is firmly rooted in the financial industry. Data will increase in volume, variability, and complexity stressing ETL pipelines. Both data quality and processing speed will become more important and more difficult to handle requiring an experienced team of specialized data, coding and operation engineers to solve.

With the right fintech team working for you, your firm can overcome common data management challenges, become more efficient and gain an edge over the competition.

Code Willing Opens New Orleans Operations Center

Code Willing New Orleans Office

Code Willing, a software company that specializes in quantitative analysis and trading solutions, has officially expanded to New Orleans. We are happy to announce the opening of our second base of operations on St. Charles Avenue located in the New Orleans Garden District.

St. Charles Avenue is a tree-lined boulevard known for its plentiful Southern live oak trees and dozens of historical mansions. It is home to the famous St. Charles Streetcar Line and is one of the chief Mardi Gras parade routes. The facades of Tulane University and Loyola University are both located on St. Charles Avenue. 


There’s a lot of untapped talent down in New Orleans in the quantitative field. This is a great opportunity for Code Willing to build up our workforce with highly motivated, brilliant individuals who contribute to successful teams.”

– Baron Davis, CEO Code Willing


In addition to our development in New Orleans, our Baton Rouge team is rapidly growing. Since 2014, we have continually expanded our product offerings and have grown our user base. This exponential growth, coupled with the addition of customers, reinforces the growing market interest in quantitative data solutions.

We are actively hiring in both New Orleans and Baton Rouge for developers, software engineers, data scientists and interns with experience with databases, core data and storage systems.

See Our Featured Job Openings.

Take Control Of Your Data With The Code Willing Platform

Code Willing Alternative Data Management Solutions

Researchers should be able to focus on research, not on managing data.

Utilizing cloud services to manage and process time series data is rapidly becoming the go-to data solution. This is not surprising given the cost savings and processing power available in cloud-based platforms. 

Code Willing is an independent global provider of quantitative research and trading software specializing in cloud-based technology. We provide data management services to handle ingesting, cross referencing, cleaning and storing data. We pride ourselves on building efficient, clean and complete data solutions that allow our clients to focus on research.

Code Willing makes data easy and usable. 

By leveraging the Code Willing platform, processing raw vendor data into a clean, readily accessible and usable format is made easy allowing research staff to focus on the core of their business. These robust services include: cross referencing, data quality and scalable storage.

Aligning time-series data from different sources is a significant challenge. Cross-referencing independent vendor data sets and keeping them all in time synchronous order can be even more of a challenge. We accomplish this by assigning a unique identifier to all listings. This identifier, known as the “Code Willing Stable ID” or SID, is used to track specific assets through time and across multiple data sets. Additionally, we manage daily processing jobs in a very controlled and batch-oriented manner using Code Willing’s proprietary job scheduler HAL. HAL handles job dependencies, market schedules, time zone conversions and provides an extremely formattable alerting system to notify operation teams of all on-going processes.  

Data Quality is an integral part of the Code Willing suite. Anomalies in data behavior can be difficult to detect and can be very frustrating throughout the research process. We approach data quality using a two-phased approach. Our rules-based algorithms check against vendor supplied documentation to ensure correct formatting and overall content while our machine-learning/pattern-recognition processes can find deeper, more embedded anomalies. We are making great strides towards even more robust machine learning techniques. In general, our data quality processing detects outliers regardless of formatting and changes as it  automatically re-trains over time. By applying both a rules-based and an algorithmic approach to spot anomalies, the data quality program ensures that the data is clean and lowers the error rate as part of our daily data pipeline.

Content Addressable Storage (CAS) is a flexible platform for optimized content storage with customizable, role-based permissions. CAS stores the data securely in your data center or in the cloud so that it is readily accessible and it features a single, consolidated interface to all files, regardless of their physical location. The CAS platform works for anyone who requires local or cloud-based storage of large numbers of files and the ability to configure fine-grained permissions for access to those files. 

High-performance data access and data processing are core aspects of the Code Willing platform. Through these services, research staff can focus on research and investments without having to worry about routine data management. 

Learn more about our Data Management Services.

Code Willing is named one of CIO Review’s 50 Most Promising FinTech Solution Providers

The breadth and depth of data available for financial research is growing at a rapid pace. What used to be daily price and volume data sets has now grown to become order by order streaming data feeds, unstructured social media data, even geospatial imagery. Data issues like tracking assets through time sound like simple problems but are actually quite difficult challenges.

Even with large and well-known data vendors, financial organizations often find themselves straddled with significant data quality issues. As Baron K. Davis, CEO, Code Willing asserts, “Rather than using a large player that taps into multiple verticals, we think it’s better to hire a firm that understands the data specific to the finance industry. This goes a long way in processing financial data quickly and efficiently.” Code Willing, a financial technology startup, converts this idea into actionable insights for its clients. In addition, Code Willing provides data pipeline and management services to the financial industry.


We are familiar with a broad set of financial data sets, and that experience helps us quickly onboard new data from new, emerging data vendors. We understand difficult data issues facing our clients such as data quality and provide them with appropriate data management services at an affordable price,” states Davis.

Read the entire article as shown in CIO Review.