Introduction
One of the key challenges faced by financial services companies seeking to streamline their data processing operations is a lack of understanding of how their current systems work. To build a solution that can perform the necessary financial calculations effectively, a deep understanding of the operating ecosystem is needed to replicate the calculations in the new system.
This complexity is sometimes underestimated. Financial services companies often deal with outdated systems, undocumented logic, or systems knowledge that has faded over time, and without a clear map of current operations, modernisation efforts can pose a risk.
There are several scenarios that hinder the modernisation process.
1. Older / Legacy Systems
In the case of companies operating legacy systems, it’s often the case that a solution has been built in-house 20 or 30 years ago. The scale of the business has grown since then, and this older solution is no longer fit for purpose.
Unfortunately, due to the passage of time, the people who built the original solution are no longer working at the company, so there’s nobody who clearly understands how the application works. This leaves the company in a situation where they need to modernise their systems for efficiency, but they can’t create a detailed list of requirements, as they don’t know themselves.
2. Replicating Manual Calculations in a System
Another common scenario is when a company predominantly uses spreadsheets. In this case, the financial services team understands what the spreadsheets do, but to modernise, they need to be able to replicate the financial calculations they perform in a system, which can be time-consuming and labour-intensive.
The Challenge of Developing a Solution
Due to their lack of domain expertise, traditional software developers need a very detailed set of requirements to build a solution that works. The complexity of the current system and the lack of in-house understanding of how it works make designing and implementing an efficient data processing solution a daunting and seemingly impossible task.
IntegraLynx’s Unique Methodology
To build a scalable and future-fit solution, a combination of deep domain expertise and systems thinking is required. Through our extensive sector knowledge, systems expertise and methodical and step-by-step approach, Resolve’s team of actuaries can reverse-engineer the functionality of a current system by reading source code or tracing Excel calculations. We then rebuild the financial calculations in IntegraLynx.
A vital element of our work lies in the testing phase. Thanks to our methodology and the depth we go to when stripping back the original system, we have the foresight to determine all possible issues, ensuring that the solution developed covers all potential edge cases.
The result is that every instance of IntegraLynx we build is fully tested and validated for all eventualities.
Case Study
A client recently came to Resolve with a business-critical application they were running. Their existing vendor had given them 12 months’ notice of retirement, and the client knew that they needed to build an alternative solution.
Their main issue was that they lacked understanding of how the current ‘black box’ application worked, and in particular, how it performed calculations. This was preventing them from building a new application that could do the same thing.
By analysing and reverse-engineering the source code, our team was able to break out the calculations before rebuilding them in IntegraLynx. Our structured approach enabled us to test early and identify incorrect assumptions, meaning the solution we delivered captured all edge cases for the client.
Conclusion
Successfully replicating a financial calculation framework presents several challenges for companies. Resolve’s problem-solving methodology and extensive systems expertise allow us to reverse-engineer any system, regardless of complexity, while our foresight and rigorous testing ensure that every instance of IntegraLynx is future-fit and captures all edge cases.
Contact a member of our team today to learn more about how Resolve can help to streamline your data processing.