Total SIPPs under administration, including third party administered, rose to 80,997 (June 2020: 76,306).

The firm reported healthy growth in mid and full SIPPs.

Gross organic growth for its own mid and full SIPP numbers was 8.6% (2020: 7.7%).

The attrition rate on its own mid and full SIPPs rose slightly to 6.3% (2020: 5.2%).

The firm said the increase in revenue was driven by acquisitions and organic growth. Last year the group acquired SIPP and SSAS provider Talbot and Muir and Dunstan Thomas, a provider of financial technology services.

Fee income from pension administration increased 9.3% year on year to £19.7m. Total fee income rose 23.7% to £22.3m, including the fee income from Talbot and Muir.

Assets under administration increased by 26% to £36bn (June 2020: £28.6bn).

Statutory profit before tax increased by 13% to £4.5m.

Will Self, CEO of Curtis Banks, said: “We have reached the half year point in very good shape. We have a robust operating model, we are on a growth trajectory, and the integration process of Talbot and Muir and Dunstan Thomas is going extremely well. I would like to give thanks once again to all our employees for their efforts during this testing time. Not only have we minimised the effect of Covid-19 on the Group, we are also making tremendous progress on our strategic priorities.

“The second half of the year is gearing up to be a busy period. As part of our effort to reach new areas of an ever-increasing addressable market, Curtis Banks is evolving from a primarily focused SIPP administrator to a more holistic retirement group which provides technology and complementary services to the advised retirement market. I look forward to updating you all at the full year as we continue to evidence good progress on our long-term plans for growth and diversification.”

The SIPP provider also announced an interim dividend of 2.5p per share, the same as the first half of 2020.

In its half year results, the SIPP provider also said it is prototyping “a bank of technical concepts”, including the adoption of machine learning (artificial intelligence) and the integration of capabilities directly on IFA platforms.