SCD is a company that develops complex custom software.
One of our main specializations is FinTech.
We offer the development of software products in the field of FinTech and their integration into existing infrastructure.
Our key expertise is understanding the needs of customers, conducting research, solving non-trivial problems, selecting suitable technologies and implementing high-quality solutions within the time frame required by the business.
We have vast experience working with big data and can solve such problems as fraud and anomaly detection, demand forecasting, sales performance optimization and a lot more.
We offer a full cycle research and development service to create new software products or extend existing software infrastructure in the financial area.
We take pride in our quality assurance approaches, security systems, methods of ensuring data privacy, project management and other critical elements of why SCD has excelled for our clients.
Our experience suggests that each customer’s problem area is unique, so we are eager to find out which topics may be interesting to you and see if we can offer you something useful.
Our most notable projects in the FinTech area
A German financial tech company has been supporting investors since March 2011.
It is an online platform and one of the leading European ETF specialists that reaches more than one million page views per month. Besides its home market - Germany, the system is active in European markets, such as Austria, Switzerland, Italy, the United Kingdom and the Netherlands.
The system offers DIY investors guidance and tools on investing with Exchange Traded Funds (ETFs). It is meant to address the needs of beginners as well as experienced investors.
We developed the system that enables users to follow ‘model’ strategies of professional investors who have added portfolios to the system as well as create their own ETF portfolios. We also built simulation, monitoring, rebalancing, and analysis features, and did it all with optimal user experience in mind.
The system was set up to provide an entire fluctuation history of quotes to enable the user to analyze the cost changes and profitability of their portfolio in real-time. The system has been working for more than 10 years and we have been developing it since that time.
Our custom software development team has considerable experience analyzing and automating specific business processes within our customers’ organizations.
The client hired us to develop a self-optimizing recruiting process for a large geographically distributed bank. The system allows you to set tasks for recruiting a certain number of people with specific competencies for a specific branch of the company and monitor the whole recruiting process, budget, and efficiency. The system accumulates data on what advertising tools and recruiting methods work best for each type of vacancy, and selects the optimal recruiting methods for each specific case. It can optimize the recruiting process according to the recruiting budget, quality of specialists, and recruiting speed. The system takes into account the expected capacity of every advertising channel and, if it is necessary to close a large number of vacancies at once, uses not only the most optimal (although limited in volume) channel but other channels, too.
Our customer is a leading wealth manager, with an emphasis on investment banking. Providing a wide range of services in investment management, the company was looking to create a range of software solutions to help manage different types of financial instruments.
As a subcontractor, we were hired to develop a suite of financial portfolio management technology solutions.
We built three business tools as part of this project. These were web applications with rich interfaces, with an emphasis on supporting certain business processes and ensuring proper access rights. Security was also a priority on this project. The tools are:
Our client provides professional security services. The group of companies offers a wide range of services to ensure the safety of life, health and property. The company approached us with the idea of creating a unified budgeting system for their internal operations.
We were asked to formalize the process of budget planning and execution and help create a unified system for the company’s multiple branches and entities. Having to take into account various transfers between the business entities, we enabled an effective mapping of budgeting processes that fits the client’s entire business model.
The system was designed using substitute data as we didn’t have access to the client’s live data. This presented a particular challenge, yet we established an effective process of testing and conducted preliminary data structure conversions before the product versions were transferred to the client.
A lot of our clients need solutions for extracting, transforming and loading specific data, and providing custom access to them via analytical reports. Here are a couple of samples:
The bank used a multitude of various sources to collect personal data. The data contained a lot of duplicates and was often inaccurate. The volume of data exceeded millions of lines. The client wanted to develop a solution that would help consolidate and clean the data.
As we dealt with personal data, the bank was not able to provide us with access to them. Therefore we developed a customizable solution for the bank staff and established a process of adjusting it, based on their feedback.
A regional Department of Education was looking for ways to arrange budget performance data. This involved processing and formalizing the collection of budget requests coming from educational institutions in the region.
We needed to:
1. Standardize budgeting data collection. Often the data arrived incomplete or people who filed it did not comply with the requirements and listed the information in an unknown format.
2. Create a system for budgeting data collection, which prevents and avoids human errors. Since new requirements arrived in the form of documents and instructions they were often misunderstood or ignored.
The solution we developed consisted of three parts: form editor, information collector and statistics server.
The form editor allowed for a prompt creation of the forms needed to collect the data.
The information collector displayed the forms and controlled if the entered data was correct (using complex consistency verification procedures), then encrypted the data and sent them to a centralized data store.
Finally, the statistics server allowed the client to build, use, and save for future use a set of analytical queries and reports to analyze the data.
We have vast experience in developing unique algorithms and approaches to solve non-trivial problems. Though most of these algorithms were developed for industries other than finance, we should note our Kaggle award for developing algorithms that helped Red Hat to identify their most promising customers.
Red Hat has accumulated a large amount of data on its solution selling methods, effective systems for customer communication, and customer profiles. Based on these data, we have developed an algorithm for customer segmentation to single out the potentially most profitable customers and effective ways to interact with them.