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Building bridges between data islands

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Ben GossPublished: 07 November 2016

We drove out to countryside and parked outside the anonymous grey, 1950’s breeze block building. We were welcomed inside and offered coffee. While we waited we took in our surroundings; wall upon wall of beige hanging files all with private client fact finds, illustrations, application forms, correspondence and paperwork and an army of administrators photocopying, stapling, scanning and on the phone. There were several fax machines.

That morning we were given a tour of the systems used;

  • Customer relationship management
  • Back office
  • Risk profiling
  • Cash-flow planning
  • Pension comparison
  • Investment research
  • Customer reporting
  • Investment platforms
  • Providers extranets and
  • Portfolio management

Each one required a separate process and careful training and no system talked to another – an island. Re-keying client data from one to another was the norm. Welcome to the back office of one of the country’s largest private client IFAs in the first decade of the 21st century.

Retail financial services is a complex, highly regulated and rapidly changing market with a significant number of niches and variations in advice models. From an IT point of view the result is lots of systems with lots of different specialisations. This is not helpful when it comes to digitising some or all of the financial planning process because each system can be an island of data and each will use different data definitions.

The pain caused by data islands is twofold;

  1. Cost, risk and loss of profit

It’s difficult to automate a process when data sits in different systems. The most common workaround to date has been to re-key from one to another. Needless to say this is labour intensive and runs the risk of errors being introduced. We worked with a wealth manager who had reached the point of accruing for the financial redress it expected to have to make as a result of errors generated during the portfolio rebalancing process almost every quarter. Regardless of the checks it put in place, the precision required to review and rebalance large numbers of portfolios was too difficult for the administrators to get right.

An independent study by F&TRC estimated the average time taken as 7.5 hours to complete an investment review. 7.5 hours of a professional’s time at £150 per hour, means that each review would cost £1,125. Realistically if all the customer received was one review a year then the portfolio would need to be between £100,000 and £200,000 assuming the firm charged between 0.5% and 1% a year. With smaller portfolios profit is lost.

  1. Loss of asset and risk model integrity

Building an investment recommendation based on data held in a back office, platform or portfolio management system becomes challenging because of the different data definitions and accuracy of these systems. Asset model integrity, the backbone of suitability, relies on consistent definitions of asset classes, their risk and return parameters, risk profiles and so on.  It also makes servicing the customer more challenging because assessment of portfolio drift or performance in relation to the customer’s plan needs to accurately reflect the definitions used with the customer to create their plan in the first place. The more automated the service the more consistency of planning reference data matters.

It is worth noting that some systems grew up prior to the Retail Distribution Review and the banning of commission. Their data architectures (the entities or ‘things’ that the system recognises) often therefore revolve around the commission or product plan rather than the customer and their financial plan. This makes producing a financial plan and set of recommendations which reflect known information on the customer more difficult and again prevents asset model integrity.

Why best of breed wins – every time

Financial institutions and vendors have tried to deliver good end-to-end applications and have spent many millions of pounds doing so, however in a rapidly evolving market the cost and specialist skills required to have a strong waterfront application have proven too challenging.

Even in much larger markets such as US the same fragmented pattern exists because of the specialist skills and technology required in each part of the planning process, front to back office. 

For example to deliver risk profiling and financial planning services you need qualified financial planning, CFA investment analysis, investment research, actuarial and mathematical resources as well as core usability and software development skills. These are not needed in a CRM team for example.

The best answer is the integration of best-of-breed systems each of which is strong in their own domain with clarity around which set of data is owned or mastered where and an agreed set of reference data.

The best examples we see are where 3 or 4 core system types support a joined-up service with:

  1. CRM owning basic details around the customer, their marketing and communications
  2. Back office owning financials, fees and compliance (1. and 2. may be the same in an IFA practice)
  3. A smaller number of platforms or a portfolio management system mastering portfolio information, and
  4. A specialist risk profiling and financial planning system pulling data for the profiling, planning, portfolio construction and monitoring process. Enriched data from the planning process is then pushed back to the CRM/back office.

A joined-up approach which removes re-keying and ensures asset model integrity raidcally reduces the time, cost and risk of planning and servicing customers. The study from the Financial & Technology Research Centre showed a 700% improvement in productivity reducing the 7.5 hours of financial planner time for an investment review, to 47 minutes!

It also helps ensure asset model integrity and ongoing suitability and forms the basis of an efficient data flow which can be accessed by more automated, customer-facing digital services.

Best practice learnings:

  • Best of breed. The complexity of retail financial services drives system specialisation with firms which excel in each. The best strategy is to work with best of breed and bridge data islands through 2-way integration.
  • Consistent reference data. Ensure asset model integrity by using reference data from your financial planning process throughout the customer journey. Think customer plan, not product plan.
  • Use financial planning to build bridges between data islands for the profiling, planning and portfolio construction and monitoring process will set the reference data, while pulling and pushing data to the other systems. These services may be planner or customer facing.

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