Posts categorized "Events"

A-Team event – Data Management for Risk, Analytics and Valuations

My colleagues Joanna Tydeman and Matthew Skinner attended the A-Team Group's Data Management for Risk, Analytics and Valuations event today in London. Here are some of Joanna's notes from the day:

Introductory discussion

Andrew Delaney, Amir Halton (Oracle)

Drivers of the data management problem – regulation and performance.

Key challenges that are faced – the complexity of the instruments is growing, managing data across different geographies, increase in M&As because of volatile market, broader distribution of data and analytics required etc. It’s a work in progress but there is appetite for change. A lot of emphasis is now on OTC derivatives (this was echoed at a CityIQ event earlier this month as well).

Having an LEI is becoming standard, but has its problems (e.g. China has already said it wants its own LEI which defeats the object). This was picked up as one of the main topics by a number of people in discussions after the event, seeming to justify some of the journalistic over-exposure to LEI as the "silver bullet" to solve everyone's counterparty risk problems.

Expressed the need for real time data warehousing and integrated analytics (a familiar topic for Xenomorph!) – analytics now need to reflect reality and to be updated as the data is running - coined as ‘analytics at the speed of thought’ by Amir. Hadoop was mentioned quite a lot during the conference, also NoSQL which is unsurprising from Oracle given their recent move into this tech (see post - a very interesting move given Oracle's relational foundations and history)

Impact of regulations on Enterprise Data Management requirements

Virginie O’Shea, Selwyn Blair-Ford (FRS Global), Matthew Cox (BNY Melon), Irving Henry (BBA), Chris Johnson (HSBC SS)

Discussed the new regulations, how there is now a need to change practice as regulators want to see your positions immediately. Pricing accuracy was mentioned as very important so that valuations are accurate.

Again, said how important it is to establish which areas need to be worked on and make the changes. Firms are still working on a micro level, need a macro level. It was discussed that good reasons are required to persuade management to allocate a budget for infrastructure change. This takes preparation and involving the right people.

Items that panellists considered should be on the priority list for next year were:

· Reporting – needs to be reliable and meaningful

· Long term forecasts – organisations should look ahead and anticipate where future problems could crop up.

· Engage more closely with Europe (I guess we all want the sovereign crisis behind us!)

· Commitment of firm to put enough resource into data access and reporting including on an ad hoc basis (the need for ad hoc was mentioned in another session as well).

Technology challenges of building an enterprise management infrastructure

Virginie O’Shea, Colin Gibson (RBS), Sally Hinds (Reuters), Chris Thompson (Mizuho), Victoria Stahley (RBC)

Coverage and reporting were mentioned as the biggest challenges.

Front office used to be more real time, back office used to handle the reference data, now the two must meet. There is a real requirement for consistency, front office and risk need the same data so that they arrive to the same conclusions.

Money needs to be spent in the right way and fims need to build for the future. There is real pressure for cost efficiency and for doing more for less. Discussed that timelines should perhaps be longer so that a good job can be done, but there should be shorter milestones to keep business happy.

Panellists described the next pain points/challenges that firms are likely to face as:

· Consistency of data including transaction data.

· Data coverage.

· Bringing together data silos, knowing where data is from and how to fix it.

· Getting someone to manage the project and uncover problems (which may be a bit scary, but problems are required in order to get funding).

· Don’t underestimate the challenges of using new systems.

Better business agility through data-driven analytics

Stuart Grant, Sybase

Discussed Event Stream Processing, that now analytics need to be carried out whilst data is running, not when it is standing still. This was also mentioned during other sessions, so seems to be a hot topic.

Mentioned that the buy side’s challenge is that their core competency is not IT. Now with cloud computing they are more easily able to outsource. He mentioned that buy side shouldn’t necessarily build in order to come up with a different, original solution.

Data collection, normalisation and orchestration for risk management

Andrew Delaney, Valerie Bannert-Thurner (FTEN), Michael Coleman (Hyper Rig), David Priestley (CubeLogic), Simon Tweddle (Mizuho)

Complexity of the problem is the main hindrance. When problems are small, it is hard for them to get budget so they have to wait for problems to get big – which is obviously not the best place to start from.

There is now a change in behaviour of senior front office management – now they want reports, they want a global view. Front office do in fact care about risk because they don’t want to lose money. Now we need an open dialogue between front office and risk as to what is required.

Integrating data for high compute enterprise analytics

Andrew Delaney, Stuart Grant (Sybase), Paul Johnstone (independent), Colin Rickard (DataFlux)

The need for granularity and transparency are only just being recognised by regulators. The amount of data is an overwhelming problem for regulators, not just financial institutions.

Discussed how OTCs should be treated more like exchange-traded instruments – need to look at them as structured data.

Posted by Brian Sentance | 17 October 2011 | 11:44 pm

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PRMIA on Data and Analytics

Final presentation at the PRMIA event yesterday was by Clifford Rossi and was entitled "The Brave New World of Data & Analytics Following the Crisis: A Risk Manager's Perspective".

Clifford got his presentation going with a humorous and self-depricating start by suggesting that his past employment history could in fact be the missing "leading indicator" for predicting orgnisations in crisis, having worked at CitiGroup, WaMu, Countrywide, Freddie Mac and Fannie Mae. One of the other professors present said that he didn't do the same to academia (University of Maryland beware maybe!).

Clifford said that the crisis had laid bare the inadequacy and underinvestment in data and risk technology in the financial services sector. He suggested that the OFR had the potential to be a game changer in correcting this issue and in helping the role of CRO to gain in stature.

He gave an example of a project at one of the GSEs he had worked at called "Project Enterprise" which was to replace 40 year old mainframe based systems (systems that for instance only had 3 digits to identify a transaction). He said that he noted that this project had recently been killed, having cost around $500M. With history like this, it is not surprising that enterpring risk data warehousing capabilities were viewed as black holes without much payoff prior to the crisis. In fact it was only due to Basel that data management projects in risk received any attention from senior management in his view.

During the recent stress test process (SCAP) the regulators found just how woeful these systems were as the banks struggled to produce the scenario results in a timely manner. Clifford said that many banks struggled to produce a consistent view of risk even for one asset type, and that in many cases, corporate acquisitions had exascerbated this lack of consistency in obtaining accurate, timely exposure data. He said that the mortgage processing fiasco showed the inadequacy of these types of systems (echoing something I heard at another event about mortgage tagging information being completely "free-fromat", without even designated fields for "City" and "State" for instance)

Data integrity was another key issue that Clifford discussed, here talking about the lack of historical performance data leading to myopia in dealing with new products and poor defintions of product leading to risk assessments based on the originator rather than on the characteristics of the product. (side note: I remember prior to the crisis the credit derivatives department at one UK bank requisitioning all new server hardware to price new CDO squared deals given it was supposedly so profitable, it was at that point that maybe I should have known something was brewing...) Clifford also outlined some further data challenges, such as the changing statistical relationship between Debt to Income ratio and mortgage defaults once incomes were self-declared on mortgages.

Moving on to consider analytics and models, Clifford outlined a lot of the concerns covered by the Modeller's Manifesto, such as the lack of qualitative judgement and over-reliance on the quantitative, efficiency and automation superceding risk management, limited capability to stress test on a regular basis, regime change, poor model validation, and cognitive biases reinforced by backward-looking statistical analysis. He made the additional point that in relation to the OFR, they should concentrate on getting good data in place before spending resource on building models.

In terms of focus going forward, Clifford said the liquidity, counterparty and credit risk management were not well understood. Possibly echoing Ricardo Rebonato's ideas, he suggested that leading indicators need to be integrated into risk modelling to provide the early warning systems we need. He advocated that the was more to do on integrating risk views across lines of business, counterparties and between the banking and trading book.

Whilst being a proponent of the OFRs potential to mandate better Analytics and data management, he warned (sensibly in my view) that we should not think that the solution to future crises is simply to set up a massive data collection and Modelling entity (see earlier post on the proposed ECB data utility)

Clifford thinks that Dodd-Frank has the potential to do for the CRO role what Sarbanes-Oxley did in elevating the CFO role. He wants risk managers to take the opportunity presented in this post-crisis period to lead the way in promoting good judgement based on sound management of data and Analytics. He warned that senior management buy-in to risk management was essential and could be forced through by regulatory edict.

This last and closing point is where I think where the role of risk management (as opposed to risk reporting) faces it's biggest challenge, in that how can a risk manager be supported in preventing a senior business manager from seeking a overly risky new business opportunity based on what "might" happen in the future - we human beings don't think about uncertainty very clearly and the lack of a resulting negative outcome will be seen by many to invalidate the concerns put forward before a decision was made. Risk management will become known as the "business prevention" department and not regarded as the key role it should be.

Posted by Brian Sentance | 24 June 2011 | 3:26 pm

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A French Slant on Valuation

Last Thursday, I went along to an event organized by the Club Finance Innovation on the topic of “Independent valuations for the buy-side: expectations, challenges and solutions”.

The event was held at the Palais Brongniart in Paris, which, for those who don’t know (like me till Thursday), was built in the years 1807-1826 by the architect Brongniart by order of Napoleone Bonaparte, who wanted the building to permanently host the Paris stock exchange.

Speakers at the roundtable were:

• Eric Benhamou, CEO  Pricing Partners
• Francis Cornut, Président  DeriveXperts
• Jean-Marc Eber, Président LexiFi
• Patrick Hénaff, Associated Professor at the University of Bretagne (see model validation paper for additional background)
• Claude Martini, CEO  Zeliade Systems

The event focussed on the role of the buy-side in financial markets, looking in particular at the concept of independent valuations and how this has taken an important role after the financial downturn.  However, all the speakers agreed that remains a large gap between the sell-side and buy-side in terms of competences and expertise in the field of independent valuations. The buy-side lacks the systems for a better understanding of financial products and should align itself to the best practices of the sell-side and bigger hedge funds.

The roundtable was started by Francis Cornut of DeriveXperts, who gave the audience a definition of independent valuation. Whilst valuation could be defined as the “set of data and models used to explain the result of a valuation”, Cornut highlighted how the difficulty is in saying what independent means; there is in fact a general confusion on what this concept represents: internal confusion, for example between the front office and risk control department of an institution, but also external confusion, when valuations are done by third-parties.

Cornut provided three criteria that an independent valuation should respect:

• Autonomy, which should be both technical and financial;
• Credibility and transparency;
• Ethics, i.e.: being able to resist to market/commercial pressure and deliver a valuation which is free from external influences/opinions.

Independent valuations are the way forward for a better understanding of complex, structured financial products. Cornut advocated the need for financial parties (clients, regulators, users and providers) to invest more and understand the importance of independent valuations, which will ultimately improve risk management.

Jean-Marc Eber, President LexiFi, agreed that the ultimate objective of independent valuations is to allow financial institutions to better understand the market. To accomplish this, Eber pointed to the fact that when we speak about services to clients, we should first think of what are their real needs. The bigger umbrella of “buy-side” implies in fact different needs and there is often a contradiction on what regulators want: on one side, having independent valuations provided by independent third parties; on the other side, independent valuations really mean that internal users/staff do understand what there is underline the products that a company have.In the same way, we don’t just need to value products but also measure their risk and periodically  re-value them.It is important, in fact, to have the whole picture of the product being evaluated in order to make the buy-side more competitive.

Another point on which the speakers agreed is traceability: as Eber said, financial products don’t exist just as they are, but they go under transformation and change several times. Therefore, the market needs to follow the products across its life cycle till its maturity stage and this pose a technology challenge, in providing scenario analysis for compliance and keeping track of the audit trail.

At the question, ‘what has the crisis changed’ panellists answered:

Eber: the crisis showed the need to be more competent and technical to avoid risk. He highlighted the need to understand the product and its underlying. Many speak of having a central repository for OTCs, obligations, etc but this needs more thinking from the regulators and the financial markets. Moreover, the markets should focus more on quality data and transparency.

Eric Benhamou, CEO pricing Partners, sees an evolution of the market as the crisis showed underestimated risks which are now being taken in consideration.

Claude Martini, CEO Zeliade, advocated the need for financial markets to implement best practices for product valuations: buy-side should apply the same practices already adopted by the sell-side and verify the hypotheses, price and risk related to a financial product.  

Cornut admitted  things have changed since 2005, when they launched DerivExperts and nobody seemed to be interested in independent valuations. People would ask what value they would get from an investment in independent valuations: yes, regulators are happy but what’s the benefit for me?

This is changing now that financial institutions know that a deeper understanding of financial products increases their ability to push the products to their clients. The speech I enjoyed the most was from Patrick Hénaff, associated professor at the University of Bretagne and formerly Global Head of Quantitative Analysis - Commodites at Merrill Lynch / Bank of America.

He took a more academic approach and contested the fact that having two prices to confront is thought to reduce the incertitude on the product but highlighting as this is not always the case. I found interesting his idea of giving a product price with a confidence interval or a ‘toxic index’ which would represent the incertitude about the product and reproduce the model risk which may originate from it.

We speak too often about the risk associated to complex products but Hénaff, explained how the risk exists even on simpler products, for example the calculation of VAR on a given stock positioning. A stock is extremely volatile and we can’t know its trend; providing a confidence interval is therefore crucial. What is new instead, it is the interest that many are showing in assigning a price to a determinate risk, whilst before model risk was considered a mere operational risk coming out from the calculation process. Today, a good valuation of the risk associated to a product can result in less regulatory capital used to cover the risk and as such it is gaining much more interest from the market.

Henaff describes two approaches currently taken from academic research on valuations:

1) Adoption of statistic simulation in order to identify the risk deriving from an incorrect calibration of the model. This consists in taking historical data and test the model, through simulations and scenarios, in order to measure the risk associated in choosing a model instead of another;)

2) Have more quality data. Lack of quality data implies that models chosen are inaccurate as it is difficult to identify exactly what model we should be using to price a product.

 

Model risk, which as said above was before considered  an operational risk, now becomes of extremely importance as it can free up capital. Hénaff suggested that is key to find for model risk the equivalent of the VAR for market risk, a normalized measure. He also spoke about the concept of a “Model validation protocol”, giving the example of what happens in the pharmaceutical and biologic sectors: before launching a new pill into the market, this is tested several times.

Whilst in finance products are just given with their final valuation, the pharmaceutical sector provides a “protocol” which describes the calculations, analysis and processes used in order to get to the final value and their systems are organized to provide a report which would show all the deeper detail. To reduce risk, valuations should be a pre-trade process and not a post-trade.

This week, the A-Team group published a valuations benchmarking study which shows how buy-side institutions are turning more and more often to third-parties valuations, driven mainly by risk management, regulations and client needs. Many of the institutions interviewed also admitted that they will increase their spending in technology to automate and improve the pricing process, as well as the data source integration and the workflow.

This is in line on what has been said at the event I attended and confirmed by the technology representatives speaking at the roundtable.

I would like to end with what Hénaff said: there can’t be a truly independent valuation without transparency of the protocols used to get to that value.

Well, Rome wasn’t built in a day (and as it is my city we’re speaking about, I can say there is still much to build, but let’s not get into this!) but there is a great debate going on, meaning that financial institutions are aware of the necessity to take a step forward. Much is being said about the need for more transparency and a better understanding of complex, structured financial products and still there is a lot to debate.  Easier said than done I guess but, as Napoleon would say, victory belongs to the most persevering!

Posted by Sara Verri | 28 October 2010 | 4:50 pm

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Analytics Management by Sybase and Platform

I went along to a good event at Sybase New York this morning, put on by Sybase and Platform Computing (the grid/cluster/HPC people, see an old article for some background). As much as some of Sybase's ideas in this space are competitive to Xenomorph's, some are very complimentary and I like their overall technical and marketing direction in focussing on the issue of managing of data and analytics within financial markets (given that direction I would, wouldn't I?...). Specifically, I think their marketing pitch based on moving away from batch to intraday risk management is a good one, but one that many financial institutions are unfortunately (?) a long way away from.

The event started with a decent breakfast, a wonderful sunny window view of Manhattan and then proceeded with the expected corporate marketing pitch for Sybase and Platform - this was ok but to be critical (even of some of my own speeches) there is only so much you can say about the financial crisis. The presenters described two reference architectures that combined Platform's grid computing technology with Sybase RAP and the Aleri CEP Engine, and from these two architectures they outlined four usage cases.

The first use case was for strategy back testing. The architecture for this looked fine but some questions were raised from the audience about the need for distributed data cacheing within the proposed architecture to ensure that data did not become the bottleneck. One of the presenters said that distributed cacheing was one option, although data cacheing (involving "binning" of data) can limit the computational flexibility of a grid solution. The audience member also added that when market data changes, this can cause temporary but significant issues of cache consistency across a grid as the change cascades from one node to another.

Apparently a cache could be implemented in the Aleri CEP engine on each grid node, or the Platform guy said that it was also possible to hook in a client's own C/C++ solution into Platform to achieve this, and that their "Data Affinity" offering was designed to assist with this type of issue. In summary their presentation would have looked better with the distributed cacheing illustrated in my view, and it begged the question as to why they did not have an offering or partner in this technical space. To be fair, when asked whether the architecture had any performance issues in this way, they said for the usage case they had then no it didn't - so on that simple and fundamental aspect they were covered.

They had three usage cases for the second architecture, one was intraday market risk, one was counterparty risk exposure and one was intraday option pricing. On the option pricing case, there was some debated about whether the architecture could "share" real-time objects such as zero curves, volatility surfaces etc. Apparently this is possible, but again would have benefitted by being illustrated first as an explicit part of the architecture.

There was one question about the usage of the architecture applied to transactional problems, and as usual for an event full of database specialists there was some confusion as to whether we were talking about database "transactions" or financial transactions. I think it was the latter, but this wasn't answered too clearly but neither was the question asked clearly I guess - maybe they could have explained the counterparty exposure usage case a bit more to see if this met some of the audience member's needs.

The latter question on transactions above got a conversation going on about resilliancy within the architecture, given that the Sybase ASE database engine is held in-memory for real-time updates whilst the historic data resides on shared disk in Sybase IQ, their column-based database offering. Again full resilience is possible across the whole architecture (Sybase ASE, IQ, Aleri and the Symphony Grid from Platform) but this was not illustrated this time round.

Overall good event with some decent questions and interaction.

Posted by Brian Sentance | 20 October 2010 | 7:40 pm

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Counterparty Event

I went along to a morning panel on counterparty data management on Tuesday, sponsored by GoldenSource, Avox and Interactive Data, and hosted by Virginie O'Shea of the A-Team. Counterparty data obviously has a very high profile currently in light of recent events, however the advice from the panel fundamentally seemed to be get the basics of data management right (ownership, control, consistency, quality, transparency), rather than anything radically new.

There was some debate about the possible extension of BIC (Bank Identifier Code) to be used more generally as a standard for a unique business entity identifier - this seemed to be received well but there were concerns that such an initiative would not solve the problem but rather become an addition to the already complex entity-mapping process.

The "Data Utility" from the ECB was also debated, and it was refreshing to here some negative (realistic?) things said about it, such as the concern raised by Interactive that this might involve huge public spend without necessarily understanding why a new government sponsored entity would be able to do better than existing data providers. Obviously a data provider would say that, but I have to agree, it seems there is too much focus on having a data utility and not looking at the different options for solving industry data issues (one option obviously being a data utility, but lets not pre-package the problem with a solution but more of that in later posts...).

For more detail on the event, then take a look at Virginie's blog post.

Posted by Brian Sentance | 21 May 2010 | 9:56 am

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