How Can Custom Trading Software Benefit Financial Operations?

How Can Custom Trading Software Benefit Financial Operations

The necessity of keeping pace with emerging financial markets and ever-changing regulations has led to the widespread adoption of custom trading software. Why custom trading software, not a ready-made one? The former option seems to boost greater efficiencies while bringing down costs. 

Nowadays, a wide range of pre-made software is available on the market. Each financial enterprise, however, has its own set of functionalities and operates in a distinct working environment. There is no one-size-fits-all platform in reality. That is where custom trading software development can come in. These platforms are tailored to fit the unique culture and workflow of every different business. They are game-changers for supporting enterprises to enhance their digital customer journey and transform manual operation into robotic process automation. 

Below are the four significant benefits that customized trading software can bring to banks, financial groups, brokerage firms, and fintech companies. 

#1 Improve Operational Efficiency

Operational efficiency is a key performance indicator of any enterprise. This metric is the ratio of the optimal output to the minimum resources used. It reflects the health of an enterprise. In other words, it measures operational productivity and effectiveness. No wonder any business manager wants to enhance this metric. But how? 

Improving operational efficiency requires finding an alternative way to automate manual and repetitive tasks. These obligatory tasks are time-consuming, yet, have added no value to both enterprises and their clients. For instance, a traditional onboarding process requires clients’ physical presence. That means clients must go to a bank branch before work, at lunchtime, or after work. Alternatively, they must take half a day off work to wait in lines and deal with a lot of paperwork afterward. Meanwhile, Know Your Customer (KYC) can smooth and speed up the process, thus, enhancing bank staff and client experiences.

Depending on the understanding of workflow and working culture, developers can specifically design custom trading software to help an enterprise become more productive. Many low-cost technologies can be leveraged to save time, money, and energy. Robotic process automation (RPA), artificial intelligence (AI), and machine learning (ML) are just some examples. 

#2 Support Processes Across the Entire Trade Lifecycle

The trade lifecycle is a core process of any commercial enterprise. It reflects the interplay between the buyers and sellers through a string of logical steps involved in a trade. The steps include pre-sale, trade capture/execution, validation/confirmation, and settlement. 

When it comes to business operation, the entire trade lifecycle process can be split into two different categories: trading activities (front end) and operational activities (back end). As the financial market has evolved and new trading instruments have accelerated, so too has trade lifecycle complexity. It’s necessary to invest in a superior infrastructure for the entire trade lifecycle digital transformation. 

With the support of custom trading software, every step in the trade lifecycle can be automatically executed in the blink of an eye. For instance, the adoption of robo advisors technology can optimize interactions with clients. In detail, it can help enterprises manage client orders from social media platforms, handle client credit scores, notify them about upcoming payments, and even create realistic budgets. 

It takes a lot of work to create trading software of a high caliber. These solutions must provide a wide range of functionality, adhere to industry standards, perform flawlessly, and have numerous additional requirements that must be considered throughout the process. Custom software development, however, can address the issue.

#3 Respond to Emerging Market Regulations in Time

The wave of volatile regulations has placed a burden on banks and other similar financial groups. A set of far-reaching financial principles is constantly added by policymakers to respond to the growth of new markets.

Let’s take data regulations as an example. The open-source movement in finance has initiated data sharing between banks, financial groups, and third parties. This trend has been attributed to many client-oriented products, services, and solutions. Yet, which client data will be shared, when, and how is still a hotly discussed topic. As data sharing is expanding at a rapid rate, lawmakers have enacted secure and transparent data regulations to protect end-user privacy. For instance, the General Data Protection Regulation (GDPR) is the most well-known regulation on data protection and privacy in the EU. GDPR went into effect in 2018. 

In this case, good custom trading software can help enterprises not only rapidly react to ever-changing market conditions promptly. But it can also facilitate data operations in accordance with new fundamental rules of consent, insight, and flow.

#4 Aggregate Financial Data

Large enterprises and multinationals are increasingly confronting an array of data management challenges. Ever-increasing data volumes, poor data quality, inadequate data security and protection, and insufficient data-savvy human resources are a few examples.

These challenges seem tougher for banks, financial organizations, brokerage firms, or fintech companies. By nature, these entities acquire and manipulate the mass of data constantly. Their complex operation heavily depends on an intricate network of business rules made up of this data volume.  Fortunately, custom trading software exists to assist in every stage of the data management process. A data aggregation platform, for instance, can gather information from multiple sources such as client accounts, client histories, social media, marketing campaigns, third-party sources, etc. 


In addition, this type of platform can create a single reference point. Thanks to that, it provides easy access to information for staff at different levels. With such a wide breadth and in-depth data collection, entities can gain further insights into clients’ behavior and identify upcoming trends. It may attribute to a strategic decision to develop new products, and increase sales and revenues.

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