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A central investment proposition - no guarantee of consistency of outcome

Daryl Roxburgh, President and Global Head of BITA Risk® part of the corfinancial® Group

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BITA Risk provides BITA WEALTH with module options as follows:  BITA Wealth Profiler - multi-dimensional suitability profiling of a client’s investment needs, matching to investment proposition and linking to portfolio building and monitoring BITA Wealth Portfolio Analytics - institutional strength risk capabilities, risk models and portfolio modelling - incorporating reporting, pre-trade compliance checks...

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by BITA Risk
| 02/03/2023 14:00:00

A Central Investment Proposition (CIP) is no guarantee of consistency of outcome, whether measured by performance, risk, or cost. In this blog, we review two case studies where BITA Wealth helped deliver the CIP and resulted in more consistent results – key to Consumer Duty obligations.

Case A – freedom within a framework. The firm had autonomous managers, central asset allocation models and a non-mandated research list. When we undertook an initial assessment of portfolios, it was found that there was:

  • Little portfolio risk consistency within risk bands.
  • An issue with concentrated portfolios.
  • Patchy take up on the research list.
  • A high variation in portfolio performance.

Asset allocation drift had previously been relied upon as the key metric and was measured by the front office system.

Following an analysis phase, looking at the portfolio risk and construction characteristics across the book and by mandate in BITA Wealth, initial guidelines were set for each risk category. These covered portfolio risk (volatility), maximum holding weights by asset type, off-research list percentages, high volatility holdings, tracking error and asset allocation against the assigned model.

BITA Wealth gave investment managers a dashboard on which they could identify significant outliers for each metric and the tools to model portfolio changes and bring them into line. Where this was not possible, they could record a known exception and apply a deferral against a test. The governance and oversight team had information instantly available, so could focus their time on reviewing critical outliers and managers’ progress, rather than having to collate data.

Within a year, the external party that reviewed the firm’s client performance and risk against their peer group commented positively on the significant improvement in the consistency of outcomes.

Case B – rebalanced models. The second case study is a little more surprising. A firm was running 300,000 plus client portfolios, all rebalanced to model on a weekly basis.

They were consistently finding, each quarter, that around 10% of portfolios were outside the acceptable deviation from the model performance.

They had a team of six consultants working on investigating and seeking rectification. Given that in many cases,  they were looking at outlier portfolios months after the event that triggered the performance deviation, there was a lot of time spent trawling through historic data.

Using BITA Wealth to analyse all the portfolios down to holding level in an analysis phase and then on data through time, a series of issues were discovered in the process that contributed to the performance deviation. Because of the quarterly review cycle, these were not identified at the time and so resulted in performance deviation. Moving to daily monitoring with BITA Wealth and exception management, would enable next-day rectification of issues and significantly reduce any performance impact.

In some instances, the performance deviation was to be expected, such as the closure of the account mid-quarter or a client holding cash pending investment or withdrawal. However, these had not been consistently identified and marked as known exceptions previously, and so the performance team was required to investigate.

In other cases, cash had come in and not been invested on a timely basis – daily monitoring not only resolved this but enabled root cause analysis of what was causing these failures.

Lastly, the commonality of holding weight between the model and each portfolio was tested daily. This identified the third primary cause of performance deviation. While portfolios were rebalanced to the model, in a number of cases, the portfolio value was significantly below the stated minimum. Given that the portfolios were invested in a wide spread of direct equities, this meant that for assets with a large price per share, these smaller portfolios were not in line with the model weights. This was a more fundamental business model issue. Again, having been identified through the monitoring, the affected portfolios could be carved out for separate action.

These brief case studies give an insight into the challenges of running a Central Investment Proposition, gaining adherence, and ensuring that the outcomes are as consistent as expected.

If you would like to discuss any of the points raised here, please contact us at or see more information on our solution here.