Limina Blog

Investment Reconciliation [examples, processes & best practices]

Written by Andreas Holtz | August, 28 | 2024

What is Investment Reconciliation?

Investment management reconciliation ensures that your internal portfolio views are correct and that custodians, brokers and fund administrators have the correct information.

Ensuring internal portfolio views are correct

Orders raised within the Trade Order Management System (OMS) are obviously captured within internal views. But any externally generated data must be imported, such as:

  • Outsourced trading (can be as simple as FX hedges)
  • Any cash movements (at a very minimum subscriptions & redemptions, and sometimes also payable & receivables)
  • Any event that affects positions, such as corporate actions

After that data is imported and processed, a reconciliation ensures the result (positions & cash balances) matches with the fund administrator and custodian.

Effective reconciliation ensures that portfolio views are complete, accurate, and timely - critical for making informed investment decisions.

Ensuring external parties have the correct information

  • You send data to fund admin and custodian, such as trade files with allocations
  • Each party calculate cash flows from trades, such as fees and taxes
  • Corporate actions are processed based on different sources

The above are just 3 examples of things that reconciliation controls for. By comparing the results of these activities (e.g. the effect on cash), you ensure the accuracy of information recorded by external partners.

The Investment Reconciliation Process

There are two ways to define the reconciliation process:

  1. Through what to reconcile and in what order (trades, positions, NAV, etc.)
  2. Through the steps to execute each reconciliation (import data, transform it, compare it and resolve breaks)

We’ll cover both, starting with the first, i.e. the six things to reconcile.

By automating investment reconciliation, systems like Limina’s IMS can minimise manual intervention, allowing investment managers to focus more on enhancing processes than data verification tasks.

Investment Reconciliation Examples

Reconciliation in asset management is complex, and issues often arise for many reasons. Here are some examples of common challenges in investment management reconciliation:

Data handling issues

  1. Inconsistent rounding: one system might round to 4 decimals while another to 2.
  2. Incorrect identifier: Misclassifying a transaction or asset can lead to mismatches between accounts or systems. For example, the same stock but different exchanges.
  3. Currency conversions: variations in the exchange rates can cause mismatches, especially in global portfolios.

 

Asset class specific reconciliation

Reconciliation of OTC, alternatives, and digital assets is much more challenging than that of listed instruments. For example:
  1. OTCs don’t have identifiers, so an instrument must be identified through a combination of parameters
  2. Digital assets have more decimal points than some systems can handle
When evaluating reconciliation software, check the above even if you don’t have these assets today. It future-proofs your business and ensures you select a vendor at the forefront of functionality.

Timing differences

  1. Trade Date vs Settlement Date: For example, internal systems and fund administrators typically look at trade data for transactions and cash, while the custodian is concerned with the settlement date.
  2. Cut-off Times: If a fund isn’t valued end-of-day (EOD), then transactions filled around the cut-off time can appear on different days in the portfolio.

Data entry errors

Mistakes during manual data entry, such as incorrect amounts or transaction details, are a frequent source of fund reconciliation breaks. Minimising the required manual data entry is the only way to overcome some issues. We specifically designed Limina for this purpose; learn more about operational efficiency here

The 4 steps in the Asset Management Reconciliation Process

And now, let’s look at the 4 steps that each of the above 6 reconciliations goes through:

1. Import data

The first step is to gather data from different sources, such as internal systems and external partners. This data is typically imported into the investment reconciliation software by parsing CSV files dropped on an sFTP. Sometimes, the software must compare three data sets instead of just two, so it must be flexible enough to handle this.

2. Transform data

Once the data is imported, you must transform it into a table format – identical for each data set. Features you need for this include:

  1. Custom columns
  2. Filtering
  3. Aggregation
  4. Data type conversion

In our experience, data transformation features are where most investment reconciliation systems fall short, forcing you into manual steps in spreadsheets. If you have to transform data manually, that defeats the purpose of automation.

If you want to learn about how Limina approaches data transformation, check out a video here.

3. Reconcile data

After the data is transformed, the software matches it line-by-line according to your set rules, such as matching by instrument identifier and fund. It then compares values on each line (e.g. market value of a position) against predefined tolerances.

The best software allows for setting detailed tolerances to minimise false alerts, ensuring that only real discrepancies are flagged to your back or middle office operations team.

4. Resolve discrepancies

Finally, any errors or discrepancies need to be investigated and resolved. The breaks and their respective resolutions are typically recorded in an audit trail for internal control purposes.

Some fund reconciliation software goes a step further by helping you resolve the discrepancies (breaks). Potential features include:

  1. Allowing you to adjust data with a single click
  2. Suggesting the likely cause of a break based on past patterns
  3. Drafting an email to external parties to resolve the issue

While these features are helpful, the most significant time-saving potential lies in the earlier steps of importing and transforming data.