The finance and insurance sector plays a huge role in the UK’s economy, making up 6.9% of total economic output in 2019 alongside assisting businesses across the UK and abroad. During the COVID-19 pandemic, the UK’s financial services sector has proved more resilient than most others and is expected to continue to grow in the future. The ability of companies within this sector to gather and correctly analyse data and predict future trends is what has allowed the UK’s financial services sector to become one of the largest in the world. This need for constant innovation will naturally push businesses into R&D and some examples are given below.
AI has already been used to help insurance providers and credit lenders make smarter decisions and accurately assess the risk in particular decisions. AI has also assisted stockbrokers by performing real-time analysis of market trends, as AI can analyse massive amounts of data far quicker than any trained professional.
Telematic Devices and data collection
Many insurance companies have begun using technologies such as GPS to collect data on their clients, to better insure them by fully understanding their driving habits. Similar technologies/ systems are continuously being developed in the insurance sector alongside methods to work with and analyse the data collected.
Cloud-based data storage/collection
In recent years many industries have moved to cloud-based storage systems to manage their data. Efficient data collection, storage and management are vital in the finance and insurance industries. However, the rise of cloud-based technologies has also introduced a lot of technical challenges and uncertainties that companies must overcome through R&D.
EXAMPLES OF R&D IN THE FINANCE AND INSURANCE SECTORS
One of our clients provides insurance services in a wide range of sectors, and as part of this process they must collect and analyse large sets of data. When first acquiring new clients, the company are required to import data from legacy systems in different data formats into their home server. However, in one project, they had no way to efficiently extract this information and could only process structed data (e.g. in excel spreadsheets). Their previous system was also not scalable and numerous errors were present in their imported data.
Our client chose to use a cloud-based platform (Azure) to build a system that could handle aggregating data from 20 different source systems into a useable format on their own home server. As there was no readily available module within the public domain to perform this task, our client had to design a new module to suit their needs. They had to carefully consider and test several programming languages before deciding upon one suitable for the building of the module. The module was then built to be performed in batch by multiple systems in parallel. This allowed for the extraction of data to take place overnight, resulting in a huge productivity improvement. Development was also done on the module to improve usability and allow AI to assist in the processing of the data.
WHAT DOESN'T COUNT AS R&D
The work done to overcome the technical uncertainties of how to implement and build the system would be considered R&D for tax purposes. This would also be true for the work done to improve the usability of the dashboard for our client’s employees but would not include the work done to improve the format/aesthetics of the dashboard as the information to do so is readily available.
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