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.

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.

What Cloud Consulting Can Do For Hedge Funds

In this day and age, everyone is spending more time in the cloud. This includes hedge funds storing all of their data and information in one convenient, accessible place. Adopting cloud technology can help financial companies reduce costs, promote innovation, open the door to new possibilities and meet business objectives faster. It is critical that companies stay ahead of the curve as technology continues to morph in the future.

It is clear that now is the time for companies to migrate to the cloud, but it can be a challenging task. Which is the best path to the cloud for your organization? How do you know which applications your business needs to host in the cloud? Which technologies are a good fit for your company? It is important to have a good strategy if a company wants to be successful and meet their objectives.

The Right Cloud Starts with the Right Team.

Code Willing offers Cloud Consulting to financial businesses. We help hedge funds plan the best path forward while keeping data intact. Code Willing reduces risk and increases returns by providing a road-map for cloud migration success.

Strategy

Our experts come up with the best strategy for data migration and design the ideal network architecture for companies. We can help design the cloud infrastructure along with the company’s existing infrastructure to form a hybrid solution.

Architecture

We design data architectures that deliver maximum performance and the lowest possible latency in a data center environment so that companies get the most out of their investment. The environments designed by our architects are highly secure and built to last.

Accuracy

It is most critical that all data stays intact and unchanged through the entire transition process and over its entire life-cycle. Code Willing maintains the completeness, accuracy and consistency of the original data.

Security

Security is also of great importance. Companies can rest assured that private data is kept private and only explicitly public data is generally accessible. Security protocols ensure that data is accessed only by authorized personnel.

We have a team of talented developers, who have extensive experience in setting up and managing data solutions for numerous industries. We support clients through every stage of the cloud life-cycle.

This is a great opportunity for start-up hedge funds or any company looking to get started in quantitative trading or to modernize their data structure. The Code Willing team helps identify and meet business and IT requirements, define a cloud road-map and help with the shift to the cloud so that companies’ IT teams do not need to worry about managing complex hardware and software infrastructure.

Code Willing is the cloud data migration service for you. You can read more about Cloud Consulting from Code Willing here.