Data governance is not data management

April 17, 2013

I was on a panel at the recent TSAM UK 2013 conference in London – where the topic was “Good data governance – the challenges for the business“.

On the panel I was joined by Phil Tattersall (Simitas), Steve Clark (KPMG) and Andrew Barnett (Friends Life Investments), our moderator was Chris Johnson of HSBC Security Services.

One of the topics we discussed on the day was around governance frameworks, what had we seen in practice that worked and to what extent was governance being driven by business (as opposed to IT).

One of Phil’s comments still resonates with me today “Data governance is not data management” – why so? …unfortunately the perception that governance = management is something I come across too often. Data governance is what ensures that data management happens properly i.e. in a way that is aligned with the original goals and terms of reference for the initiative under way. Data management professionals need to clearly understand the difference between governance, stewardship and architecture!

Another of Phil’s points was also very salient  ”treat data as an asset”  any of you that read the recent Citisoft white paper “Data is the new oil” will see the connection – data is something we need to value, it can often be presented in a very raw form, and like oil, it requires careful refinement to extract maximum value. I am fan of the data and oil metaphor myself – from a slightly different angle though, I often refer to data being the oil in the distribution engine for investment managers – feed the engine with poor quality oil (data) and within a short space of time that engine will seize up.

Steve also had some good points in the above discussion, he stressed the importance of setting out the “policy and procedures in governance” and the criticality in “defining good data quality” and the measurement and feedback that should exist in your process management framework to drive improvement.

With respect to whether governance should be driven by business or IT, Andrew indicated that in his business “data teams are made up of business people” – myself and the rest of the panellists agreed that data governance initiatives should be driven by business, but that clearly IT have a role to play and their involvement will always help.

My own view was that frameworks for governance are important, in the sense a framework is anything that providers structure and guidance to the application of governance to any data management initiative. This ‘structure and guidance’ can take the form of technology that assists the empowering of the stewards to manage data in line with the stated strategies and principles as laid out by governance.  Technology can also assist in  driving ownership, accountability and transparency into the process. The key point though is not to overly rely on technology. Technology does not fix bad quality data – that is what good data management professionals do – we just need to enable them to do their job more effectively.

1 Comment | Data Quality, Technology, Event, Data management, Data Governance, distribution, asset management, transparency | Tagged: , , , | Permalink
Posted by Ronan Brennan

Setting up a governance program for effective management of investment product master data – Part 8 – Data Dictionary

March 6, 2013

This is part 8 of a series of blogs on setting up a governance program for the effective management of investment product data - in this blog I will explain why building and maintaining a data dictionary is probably one of the most important factors in the success of your program.

Like many business buzzwords, data dictionary means different things to different people. The common thread is that the dictionary is an inventory of the data items being consumed or produced within a specific defined business unit or process.

Why do we create them? Again, there are many reasons – but the most prevalent one is to bring a common understanding to play within a specific environment such that everyone is speaking the same language when it comes to data. Data management projects live and die by the quality of their data dictionaries because even within small teams you can have wildly different nomenclatures in existence for what seems at face value very simple, easily understood data items.

Before I get onto what makes up a data dictionary I would like to clear up a couple of misnomers I often come across:

- A data dictionary is not a document. Documents are two-dimensional, while data dictionaries work across many planes. They are best represented in a relational database, or if needs must, a set of interrelated Excel worksheets.

- A data dictionary is not a project resource – yes, every data management project needs a dictionary, but as a resource it has a life outside of the project. You do not create a dictionary to serve the needs of a project only – the dictionary is also required within the business-as-usual activities that come into play post a project delivery i.e. it is a resource that requires and demands constant attention, updating and refinement.

So what is commonly found in a data dictionary? As I mentioned earlier it is a centralised inventory of information on data items/fields that describes in detail the data items semantics, how the data relates to other data, where the data is consumed, where it is processed and from where it is sourced. The dictionary should also describe the correct format and syntax for each field.

So for each entry in the dictionary I would expect to find the following

- A specific unique name for the item

- A clear definition of the data items meaning, including references to other common/aka names for the item

- A list of all “consumer” entities and processes that consume/use this data item

- A list of all the “suppliers” or source systems that produce this data and deliver to processes downstream

- Specific mention of any master rules for choosing correct source system for specific situations

- A list of all business rules applied to the data item as part of any data quality management process that touches the data

- Reference to stewards or stewardship teams that are responsible for the management of the data

- Reference to subject matter expert(s) who can deal with questions about the data item

- Detailed syntax specification for the data item – including type, structure, format and example values

- Good dictionaries allow users enter and update specific notes and references à la a wiki

If you have constructed your data dictionary using a database then you can easily provide very helpful alternate views of the dictionary for example:

- Show all data items consumed by process X

- Show all business rules

- Show the data items touched by Rule Y

- For data item Z show all sources

- For data item R show all consumers

- and so on…

More advanced dictionary implementation have an integrated audit trail with the live system that can instantly show as-of  transactional views i.e. the dictionary and the real-world systems it relates to are integrated.

So how does one build the dictionary? In MoneyMate we build them out using a SIPOC process in reverse [COPIS]

- So we start off identifying all of the consumers of information

- From here working out what outputs are consumed by each consumer#

- From here working out which processes deliver the outputs

- From here working out which inputs are used in each of the processes

- Before finally identifying the source/supplier systems producing the inputs

A critical element of the COPIS/SIPOC analysis is identifying where certain data items have multiple source systems – in these cases we need to carefully specify the master data rules that indicate which source is correct for the variety of situations that dictate different usage of the data.

Examples of this problem would be:

- You could have multiple back-office providers which means your daily NAV could be flowing from multiple parties/systems

- You could also have different legal structures in play that have different statements of record for different data types e.g. for holdings you maybe using the accounting book of record for your mutual funds but for managed accounts you are taking data from your investment records.

- You could have standard source of performance for all in-house funds, but for sub-advised you take data from the sub-advisor

Clearly the dictionary needs to capture all of this information in a well structured manner and allow for specific notation of the master rules for each item which has more than one source.

So hopefully you have a better understanding of what a data dictionary is, what it contains and why it is needed.  If you have anything to add yourself – send me a PM or comment below.

Next up in the series is a review of the role technology should play….

4 Comments | asset management, client reporting, Data Quality, Technology | Tagged: , , , , , , , , , , , , , , , | Permalink
Posted by Ronan Brennan

Financial Technologies Forum LLC – FATCA Kills the Data Silo?

February 4, 2013

Interesting article on FTF about FATCA….Financial Technologies Forum LLC – FATCA Kills the Data Silo?.

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Posted by Ronan Brennan

Why should Asset Managers consider outsourcing some of their Data Management function?

November 21, 2012

I often wonder why many asset managers prefer to keep so many “non-core” functions in-house. I’ll stick to the area of data management because that’s my area of “expertise” … but I’m sure it’s true of a lot of other functions.

To me, the core business of an asset manager is to build and manage funds that identify with strategies that the investor community want exposure to… and to sell and market those funds to said community of investors. This is their core competency and it’s what they are best at. But many asset managers have lots of what I would call non-core activity going on in their organisations to the point where it is difficult to work out if they are an asset manager with a technology department or a technology department that does some asset management – so you will see why this seems a little odd to me.

Data management is a typical example of something that you could say lies outside the main day-to-day business of an asset manager. In my view, it is not their USP, nor should it be. On the other hand data is a core raw material in the build/manage process of a fund – so one can understand why an asset manager wants to keep certain business critical data management functions close to hand. On the other hand you have the sales/marketing and distribution side of the business, for whom data is not so much a raw material, rather an element of the communication, and it is here that the ‘core-ness’ of certain data management functions become less clear.

Getting your product data to market involves collating data from a myriad of internal and external sources… in a variety of formats. You have fund accountants, fund administrators, marketing departments, operations people, third parties  to name a few who each have a little bit of information to add to the overall picture – it may come in emails, spreadsheets, extracts from data warehouses, ftp sites ….. and it all has to be centralised, normalised and then validated before you can even think about publishing it externally.

I’ve seen large companies managing trillions of dollars on behalf of their clients and yet they often use interns/ junior marketing staff to collect all this information and validate it before the monthly fact sheet run or before it goes into a sales presentation or a client report. They use manual processes, for example, comparing excel spreadsheets with word documents and using highlighter pens to compare/ point out discrepancies. These are all great people … but all manual processes are prone to human error… especially if that human is facing a deadline or under pressure to get things done on time.

Obviously, there are big risks associated with manual processes…. the risk is that somebody gets it wrong and that inaccurate information gets into the public domain. This could become a major issue and ultimately lead to reputational and brand damage. My advice is – don’t rely on manual processes, ensure you have a data governance structure in place and that you are automating processes… this will mitigate the risks of inaccurate information about your funds being distributed to the market.

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Posted by Ronan Brennan

On Regulation: New KID in town (….soon)

August 23, 2012

This year we have witnessed the flood of Key Investor Information Documents for UCITS  in the marketplace, yet the bigwigs in the EU are already now proposing to broaden the initiative, and are proposing the production of a new KID (Key Investor Document) for all Packaged Retail Investment Products – or – PRIPS for short.

Since the definition of a PRIP encompasses UCITS funds, this new requirement will also apply to UCITS – although Brussels indicates a five year derogation will apply to UCITS to allow them get over the old KIID experience! The ultimate aim is, however, for all investment products to be accompanied by new KIDs in an attempt to make all investment products as comparable as possible.

The new KID will differ from the old KIID on a number of points, and really these differences will exist only to encompass the various  investment product flavours that fall under the PRIPS umbrella, hence the old KIID was deemed to be not fit for purpose.

The new KID documents will be expected to contain answers to a set of “standard” questions. The Commission says these include:

  • What is the investment?
  • Can I lose money?
  • What are the risks and what might I get back?
  • What are the costs?

The new KID, like the old document, will contain a risk indicator directly comparable with the synthetic risk and reward indicator for UCITS.

The new documents will also include information on the real costs of the various products – so that they can be compared in a neutral and objective way.

So the new documents will be broadly similar to existing KIID documents, but there will be specific changes to account for the fact that UCITS have properties that other investments do not have, and likewise there are other investment vehicles that have features and design elements not found in UCITS, such as insurance benefits or fixed investment terms.

Firms which have already gone through the mill with KIIDs for UCITS,  and have invested in their data management and document production infrastructure will be better positioned to deal with rolling out the new KIDs across all of their investment products, but those who have not…. well they are in for a rude awakening – as 2012 has been a really tough year for many on the KIID front!  So we can expect the data management impact of the new KID for PRIPS to be quite severe indeed.

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Posted by Ronan Brennan

On Regulation: AIFMD

August 15, 2012

The AIFM (Alternative Investment Fund Managers) Directive, which is focussed on improving transparency in the alternative investments market place, is coming soon.

ESMA published its final technical advice on the 16th of November 2011, with the deadline for transposition into national law happening in July 2013.

Getting ready for AIFM requires managers, and to a lesser extent depositories, to start taking action as soon as possible. Many of the key players in the market have already carried out high level impact assessments and operating model reviews, and although ESMA’s approach on reporting frequency was welcomed, specifically how they propose to relate reporting frequency to ‘fund and firm’ AUM, there was disappointment with the failure to change the substance of the reporting and the 1-month deadline for reporting  (note: fund of fund structures will have an extra weeks).

So what is the directive looking to achieve? Well, once registered with their national regulator, firms will be required to offer enhanced disclosure on their risk management program and open the lid on their investment strategies. The key element here is increasing transparency and oversight, so that the regulator can monitor exposure to systemic risk, and make sure investors in the alternatives space are being treated fairly.

In addition, the industry is going to be forced to provide more data to investors in advance of, and post any investment in the funds concerned. The disclosure to investor requirements relate to any change in liquidity requirement, risk profile, disclosure of risk management processes and disclosure of % of assets that are subject to special arrangements.

ESMA’s approach to leverage has attracted a lot of attention and public commentary. ESMA is proposing more regular disclosure requirements to investors which would cover changes to the maximum level of leverage, to the rights of re-use of the collateral, to the nature of guarantees granted and of the total leverage employed in the portfolio and their business as a whole.

The directive also requires firms to maintain up to date data on the securities they are trading, including standards based support for security identification, with additional details required on principle exposures and risk concentration.

Depositories will be required to monitor and request data from funds, and to perform additional due diligence on the custodian and prime brokers.  All players in these markets will therefore be compelled to invest in their risk and data management infrastructures, and product data (holdings, classifications, portfolio allocation views)  must be quickly accessible for reporting purposes. This activity is driving many firms to re-assess their data management strategies, infrastructure and operating models so that they are positioned to react when the regulation comes into full force in less than a years time.

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Posted by Ronan Brennan

Buy or Build?

August 22, 2011

In the world where asset management technology and data quality management departments intersect, a perennial question is raised vis-a-vis implementing technology frameworks that support the data quality management process, build and manage various master data systems (e.g. security master or product master) – should we partner with a technology vendor with a best of breed solution, or should we just build it ourselves?

Like many such perennials there is no right or wrong answer. As a technology vendor, I often argue that something like data quality management is not actually the core competency of an asset manager and rather than figuring out how to manage their data, they should focus on their investment product strategies, growing their customers etc. I do sometimes wonder though if some of the asset managers out there are financial technology companies with an asset management firm bolted on or just plain vanilla asset managers. There are some managers that have actually spun off technology companies themselves based on internal developments.

My own experience is that there really are just three camps:

 1. Build it ourselves unless there is an ultra compelling reason not to;

 2. Apply a balanced decision-making process to weigh up the pros/cons of doing an internal build versus finding a vendor to work with;

 3. Use a vendor unless there is an ultra compelling reason not to.

Are any of the camps more correct than the other? Not really – they have their reasons for the strategies they employ. There are ultra successful examples of all 3 company types – so adopting one or the other strategy does not seem to have held anyone back, but that all being said – you would have to perceive that those in camp #2 have a more pragmatic view on life.

Camp #1 companies tend to be IT-led organizations, where technology is a key driver in all aspects of what the company does and so is at the forefront of all strategic decisions – hence the need to retain internal (and full) control of all technology in use. They would normally be fundamentally opposed to outsourcing any aspect of their business.

Camp #3 companies tend to be “IT-deniers” – they are obviously the complete polar opposite of camp #1 companies and tend to be 100% led by business. The IT department is there to support and maintain systems and does not form part of the strategic fabric of the organization. One of the goals will be to maintain a low IT footprint and outsource wherever possible.

Camp #2 is the hybrid – they recognize that technology is important, but are not beholden to their own IT department. They are of the view that if there is a specialist vendor out there that has specific domain expertise and has built the same solution/product over and over again for many of their competitors, then this company will deliver a best in class solution – they retain their own IT resources for delivery of standard solutions for which an external vendor adds no specific value, or  for areas where they believe they have unique USP.

In my opinion, Camp #1 is made up of about 30% of the market, Camp #2 would account for 50% and Camp #3 would account for 20%.

The pragmatists amongst us recognize that camp #2 are probably the most balanced of organizations, but these companies really do struggle with the challenge of identifying what they should and should not outsource… it may depend on the size of the potential project or the expertise required.. or the business may influence a final decision.

Of course once a decision is made to use an external vendor, next choice is “local-install or cloud”?

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Posted by Ronan Brennan

Recent Panel Discussion at TSAM USA

July 29, 2011

July has been a busy month with client engagements and travel but I wanted to add a blog about the event I attended in New York in mid July.

Many people will be familiar with TSAM, the annual buy-side technology and operations event, which is usually attended by senior operations, marketing and IT executives. I always enjoy these industry events as they offer a great opportunity to network and catch up with people in the industry as well as finding out about the latest trends and developments.

I had the pleasure of participating in a panel discussion on “Critical issues in data management” together with industry veterans: Regina Trach, VP Marketing Services at J.P. Morgan Asset Management, Gerard Walsh, Head of Delivery, Global Strategic Solutions at Schroder Investment Management, and David Bates, Principal at Citisoft. The discussion was moderated by Uday Singh, CEO of Osney Media. It was only supposed to go on for 30 minutes but ended up stretching into an hour as there were so many questions and such a lot to talk about.

Initially, we focused on what the key issues were in the data management area, with most of the panel agreeing that drivers for data management projects centred around managing risk, complying with regulation and also managing the data “overload” – what to push out, when, and to whom. Gerard from Schroders said that as clients became ever more demanding, they needed to get timely and accurate data as fast as possible in whatever way they wanted it whether in person, in a report, on a web page or as an app on an iPad. J.P. Morgan recently launched an iPad app for advisers and feedback has been phenomenal. But, getting information to devices is a major data and integration challenge.

In terms of regulation, one of the concerns is that asset managers know there will be demands for transparency but don’t know what they will be. They are wary of the SEC and FINRA and what they will actually be looking for. The SEC is likely to take information and fact sheets from an organization’s website and compare it – and will want to ensure it’s all accurate. They will also want to know historical information e.g.”can you show me what your website looked like on April 11th, 2009″? Asset managers still have a business to run and the wall of regulation can be a challenge – but they must be compliant.

We then went on to talk about the amount of data that is available and how accessible it needs to be… With large global asset managers averaging 4.5 million items of data each month, it’s hard to answer the question “Do you know how good the quality of your data is?”  You really need to work out what to push out to your various audiences… this is where using segmentation/ audience management is very powerful. If you have a contact strategy where you test email open and click thru rates, track website visitors and monitor Twitter, you will know who is listening to you and find out what they want to hear. 

We then went on to talk about what is the right material to push out? Should we be reviewing what we need to report on. What do customers need?  We also need to focus on the consistency of information across the organisation e.g. surveys, web presentations. Separate areas of the business are generating data and enabling it to get out. I talked here about how marketing ops have not been well served by IT and there are lots of manual processes involved in getting data to market. If data points are managed on spreadsheets, you have to have proof readers coming in to get material out to market and you have a much higher risk of error. Setting up a data governance process and ensuring that data is corrected at source will help greatly and you won’t end up with marketing teams chasing, checking and keying data at the last minute.  Also, if you automate the process, you will significantly reduce your fact sheet production time.

Then we talked about actually getting data management projects off the ground. It can be quite difficult as often times C level doesn’t realise there is anything wrong with the data. It might be easier to focus on a smaller project first and try building it out from there. For example, for Schroders, the web was a big driver and they wanted to provide their sales force with tools that can help people make investment decisions – having timely, accurate and consistent data available on the web was a key influencer.

The other key influencer will be cloud computing– not just on the entire IT area but on other areas within the organisation e.g. Salesforce.com.  Asset managers are more likely to outsource if it’s not a strategic advantage to do it themselves.

 

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Posted by Ronan Brennan

Data Management in the Cloud..

May 27, 2011

To date there has been some reluctance amongst asset managers with respect to managing their security and product master data in the cloud, yet the same organizations are actively pushing their CRM data into the cloud. Why is this? Why does the sales side of the organization readily embrace such change when the investment operations teams are more cautious?

Security concerns cannot be the reason, even if they are the reason most often cited by investment operations teams who are not willing to embrace the cloud. For a financial services organization, there is nothing more sensitive than their clients’ personal details – so if you consider the number of firms actively using cloud-based CRM systems like Salesforce.com – this negates the security argument.

 But positioning of security and product master data in the cloud is just as sensitive. Of course, the security and product masters contain commercially sensitive data, but no more sensitive than client data found in many CRM cloud implementations. So we should agree that security concerns, while valid, are not the core reason we do not see the same level of enthusiasm.

Some would argue that the sales side of the organization are by their very nature risk takers, but the technology side of the business might argue that it is the quality of the offerings that is the only impediment to such decisions.

Cloud service providers, whether they are CRM or data management vendors, are all massively aware of the security risks posed by hosting sensitive third-party data – the fact is your data is probably more secure in a cloud provider’s environment than in your own, such is the focus on security.

Some believe that it is the complex relationship that often exists between IT and the sales and marketing units that is the root cause for so many sales units engaging the cloud. In the asset management world, the sales and marketing teams are often at the end of a long line of business units looking for strategic IT initiatives to be acted upon. To this end, sales and marketing teams have learned to become self-sufficient, which as an aside is probably also the root cause for the creation of the myriad of manual processes and Excel / Access-based data management initiatives found in the marketing and sales departments.

Since the investment operations units in asset management organizations have traditionally had a much closer relationship with the IT department, they have never felt the same need to explore alternative solutions. This is not to say that investment managers are not exploring data management in the cloud, just that they require a greater level of understanding of the advantages and disadvantages of such a venture. The providers of cloud-based technology and services themselves  have also had to up their game to sell the benefits.

So what merits does the cloud bring to an investment operations team? First of all, let’s debunk a myth – putting your data management solution in the cloud is not outsourcing, nor is it off-shoring. Cloud data management service providers generally engage in partnership-led operating models where they work hand-in-hand with the client towards a common goal, or they simply use the cloud provider as a technology platform in the same way they would engage with their own internal IT department.

 Working in the cloud means:

 1. Not having to worry about where you currently fit into your IT department’s strategic roadmap

 2.Your environment is managed by a team of professionals whose only goal is to ensure that  your environment is working and secure

 3. You are always on your vendor’s latest released platform version

 4. You have one less system to worry about in your BCP plans

 So what about the disadvantages? And how do you mitigate against any risks? What  should you be worried about?

1. What happens if you want to disengage from your cloud provider and take your process and data back in-house, or indeed have it managed by a different provider?

  •  This is something that needs to be considered carefully before engaging with any solution in the cloud. Before you engage, ensure that your contract and your SLA are watertight and replicate data back to your own data center so you always have a local copy at arms reach.

 2. How do you integrate the solution into your organization’s broader BCP plans?

  •  Ensure the vendor you choose to partner with has a fully documented and regularly tested business continuity plan that ensures your data is available according to your own stated ‘Recovery Time Objective’ and ‘Recovery Point Objective’ – then ensure your vendor runs the BCP tests with your involvement.

 3. How do you know your data is secure?

  •  You absolutely must do your full security due diligence – including externally-commissioned penetration testing.

 4. What about latency between your site and the cloud?

  •  Run full latency checks before the engagement and ensure latency is captured as a KPI for SLA measurement. Cloud providers are generally located at key Internet hub data centers to reduce latency concerns

5. How do you know the vendor will provide a good service?

  •  If you go down the partnership route, ensure you have an SLA that is considered an evolving document which is regularly reviewed and enhanced as your relationship develops. The SLA should set out the expected minimum service levels and the target service levels – with appropriate KPI measures identified for regular reporting.

 6. What if your vendor goes bust?

  •  Before any engagement, ensure your due diligence process includes a full financial review. In addition, insist on an escrow agreement to ensure you have access to the technology software in the event that the vendor is no longer financially viable.

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Posted by Ronan Brennan

Regulation Survey results…

April 29, 2011

I think that surveys are a fascinating insight into people’s views on what’s happening in the marketplace. We try to conduct a survey at least once a year on current trends in data management. Last year, our survey focused on what people’s challenges around data management were and this year, it was all about regulation. We decided to focus on regulation because as far as I’m concerned it seems to be all people are talking about – they’re talking about KIID, Dodd Frank, FINRA, fines, compliance and many are not really sure about how new regulation is going to impact them or what lies ahead.

 The global regulatory community has come under a lot of flak since the 2008 market implosion. In many regions, the regulator has been disbanded, restructured or at the very least forced to report to government led investigative committees. The charge levelled is that they failed to maintain a stable market by not having a clear view of the systematic market risks that were at play. The industry itself also had a role to play in the demise of the previous boom – as employees were incentivized to take on risk without the appropriate checks and balances to measure and mitigate exposures. Additionally, operating models did not keep up with the rapid change of the industry landscape – leaving behind a legacy of manual error prone processes and key knowledge data sets that were poorly maintained. In doing so, the industry and regulators to a large extent left the public to carry the can. So it is not without reason that the media and investment community alike are keenly interested in the regulatory backlash that can be expected in response to the financial crisis. Regulation was always a driver within the industry, but more recently its prominence has increased because the fines are getting bigger, and the reputational damage is all the greater, for the increased coverage being delivered by the media. Understandably, the regulators are now focused very firmly on managing market stability and ensuring the industry is treating investors fairly. From the “Know your product and client” perspective – the key focus here is that investors should be sold the most suitable product for their particular situation. The regulator (and I refer to them in general terms here) – is looking for accuracy and timeliness – and they are looking for consistency across all public communication of data – be that – printed fact-sheets, micro-sites, or institutional client reports. Sales and marketing material for investment products is coming under increased scrutiny – the regulators are increasingly treating such material as disclosure of material fact, where as in times gone by, firms were not being held to account to the levels they are today, vis-a-vis the information disclosed in such documents. Anyway, that’s some background … and I will post a blog on what the individual regulations are about in each region but on to a little more about our survey. We usually conduct our surveys at industry events such as NICSA, ICI General Membership Meeting, TSAM in Europe and also online. We presented the results in a webcast on April 13th and also in a press release which you can access here.

The objectives of the survey were:

•  to gauge industry insight on regulation

• to learn how prepared these organizations are for the impending changes

• and how will it affect firms data management processes and strategies into the future.

 The drivers for the survey should be obvious to us all – many organizations are actively assessing their target operating model with a view to adapting themselves for upcoming regulation, on top of this you have the rising spectrum of reputational damage due to increased media scrutiny and the fact that data management is now a standard item on the agenda for corporate risk assessment.

66% of the survey respondents were from North America (primarily USA) and 33% from Europe.

The first question on the survey was: “Would you say that the product data you distribute to the market is; always accurate and timely, usually accurate & timely, rarely accurate & timely, or, you don’t know” and I’ve put together a quick pie-chart of the results below:

 

What was interesting from the response was that just less than one quarter of respondents indicated that their product data was always accurate and timely, although nearly two-thirds indicated their data was only, usually accurate and timely. What can we take from this? Well it seems that most of the time asset managers product data in the public domain, is in the main accurate and timely, but, for two-thirds of asset managers, there are periodic issues with either getting their data to market in a timely or accurate manner. This is really highlighting something we already know – getting your product data into the public domain so that you have a high degree of confidence in its accuracy is not a simple solution to solve – even though this is your own information? The predominance of manual processes that deliver data from back and middle to front office is probably the core reason we see this lack of confidence. Anywhere that you have manual processes, it leads to a lack of repeatability, inability to create a systematic audit trail and a breakdown in confidence in the ability of the machine to operate under full load. What is clear is that regulators do not want to see such environments – specifically we have heard from some of our own clients that recent SEC exams focussed heavily on the ability to demonstrate repeatable and auditable processes where data was being pushed into the public domain and facing off to client investors.

The next question was “in the US and North America, which of the following regulatory discussions is your firm most concerned with? The Dodd-Frank act, the Point of Sale fund fact regulation in Canada, the reforms of the Money Markets, the 12b-1 reforms or recent FINRA interjections”

The response was hardly surprising – just under three-quarters of all respondents indicated that Dodd-Frank was at the forefront of their firms concerns when it came to discussions on regulation. It would have been surprising if the result were any less – Dodd Frank is a behemoth act, the impacts and true force of which are not even fully realized yet. I was surprised that FINRA did not feature higher than a fifth of respondents’ concerns – in particular when you consider the amount of cases they have taken recently. Even though the SEC reforms of the US money markets is to an extent yesterday’s news, it was interesting to note that nearly a quarter of all respondents indicated that these reforms were still a discussion point of concern within their firm. While the fact that a third of respondents are concerned with the ongoing trials and tribulations connected to the 12b-1 fees is not a surprise either – anything that impacts the commercial model that impacts distribution and compensation of brokers means a lot of upheaval in existing operating models. Finally the fact that only 8% of respondents are concerned with the POS Fund Facts regulation in Canada should be balanced with the knowledge that the majority of respondents were US firms which had limited exposure to Canadian investors.

This blog is getting very long…. so I will keep the results of the rest of the survey for the next post!

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Posted by Ronan Brennan

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