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Intelligently collecting data

Capita Pension Solutions (CPS) manages over 450 schemes across the public and private sectors and hosts 4.5 million members, within one of the UK’s largest pensions administration databases. Committed to helping trustees and scheme owners fulfil their pension scheme responsibilities, including Guaranteed Minimum Pension (GMP) rectification and equalisation activities.

CPS were looking for a more efficient and technology-driven solution to assist with the review of data for a large consumer goods company, and engaged with Capita Intelligent Communications (CIC) to utilise our Artificial Intelligence (AI) platform to ingest and interrogate pension data for scheme members.

CPS established a partnership with CIC 25 years ago, with both businesses continually seeking innovative ways to delight clients with automated, secure and forward-thinking service delivery. From digitising large volumes of pension scheme member files to establishing digital mailroom services or capturing business critical data.

The GMP rectification project for this large consumer goods company required CPS to review pension scheme information dating back 60 years and identify which subsidiary company members of staff were employed by, when contributing to the company’s pension scheme. However, the documents were in a range of formats including handwritten/typed letters, forms and digitised microfilms.

CPS wanted to look for an efficient, technology-driven approach to review this data, rather than commit staff resource, and called upon the services provided by CIC.
By combining machine learning and automation, CIC established an Artificial Intelligence (AI) solution that ingests, captures, validates, understands and structures data from multiple formats. This innovative solution provided CPS with the opportunity to work with a technology partner who could automate the essential, but resource-intensive and time-consuming data review tasks.

CIC and CPS understood the need to achieve the highest levels of accuracy to manage the company’s GMP responsibilities, as well as delivering a data review service of the highest quality. A phased, but focused, approach was agreed by all parties to allow for testing of the solution and review of the outputs, before final approval.

CPS exported their digital scheme member documents from their pensions administration system and uploaded them onto a secure portal. The digital files were then ingested into the AI platform for fully automated processing.

The AI solution was configured to interrogate circa 385,000 electronic documents of historic pension data for 6,354 scheme members. Data from each of the documents needed to be accurately extracted and a system validation routine was performed to remove unnecessary spaces and special characters, such as hyphens and underscores.
Once these processes were complete, the AI solution, supported by business validation rules, identified from over 2,400,000 words (equating to more than 14,000,000 characters), the name of the company’s employer(s) that related directly to the GMP rectification data cleanse exercise. The end to end system processing time for the exercise was under 6 hours. Once completed, all records processed were transferred to CPS via a secure portal.

The AI solution produced highly accurate results and has helped considerably in enabling CPS and its large consumer goods company, to meet their complex GMP obligations.

CPS now have the option to utilise a CIC solution that complements their wider administrative workflows and have the capability to not only identify, extract and classify various types of data, but can also extract text and customer sentiment from unstructured printed, as well as handwritten, correspondence.

By automating the review process and enabling staff to focus on their core data analysis and specialised GMP activities, tangible cost savings were made for CPS which in turn saved the global brand company circa £28,000


Business efficiency – Staff resource freed to focus on core business objectives
Higher output, lower outgoings – Streamlined automated operations improve productivity whilst driving down costs
Improved quality – Significant reduction in processing and verification time and risk of errors

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