A leading investment bank has decided to leverage its 100 years of wealth management expertise and world-renowned brand to launch a major effort to reach a much broader group of affluent individuals in the United States. This market has doubled in the last five years and now exceeds seven million households.
Research has shown that the service that clients seek most is a trusted advisor who integrates a full range of investment, tax planning, brokerage, banking, and generational planning services. The firm intends to deliver these through a choice of channels, including the Internet and telephone contact as well as face-to-face interaction with private bankers.
With its arsenal of mathematical engines, delivering mathematical analysis over the Web is a piece of cake. The bank is intent, however, to exceed its clients’ expectations by bringing online the same level of subtle sophistication that has been its hallmark for generations.
To lead the project, the bank assembles a task force of its best and brightest. As the task- force delves into the problem, the magnitude of the challenge begins to emerge. It quickly becomes apparent that the planned system must deal with a dynamic environment in which client, market, and bank are continuously evolving and changing. Consequently, in its interaction with the market and its clients, the bank must continuously adjust its actions based on the client’s current needs, the bank’s current objectives, and available alternatives.
In providing wealth management advice, many competing influences must be taken into account. Many of the decisions going into the advice will never be verbalized since the client expects the adviser to know what to do without having to ask unsettling questions. Realizing that the rules of the game are continuously in flux, the bank wishes to implement a system that will continuously monitor the market’s and the client’s behavior, integrate its findings with the bank’s practices and policies, identify possible alternatives, and rank them according to their ability to delight the client (and perhaps advance the bank’s interests as well).
In the following description we focus on the elements involved in building a system for wealth management. Our intent here is to highlight the fact that providing wealth-management advice requires the integration of knowledge from multiple areas and multiple types. As we mentioned earlier, this ability to integrate the knowledge process is a cornerstone of Tupai’s technology.
While Tupai’s technology, eCognition, includes numerous forms of sophisticated automation for the continuous extraction and deployment of knowledge, we left the more technical aspects of the technology for later discussions.
eCognition, addresses the fluid interaction of client needs, market behavior, and current portfolio holdings by constructing a representation (or model) of the situation at hand, and then performing situational analysis on it. In conducting its analysis, the wealth management system is able to research dealings with people in similar positions in the past, and use the knowledge to guide its actions. The bank then decides on the makeup of the portfolio, and under some circumstances, may suggest other actions, such as recommending a change in the client’s drawdown rate.
An eCognition model for wealth management comprises of a number of interacting components – the client, their portfolio(s), and the market. Each of these components is modeled initially, as well as the effects of their interactions.
The client is a complex amalgam of psychology and financial need. Some parts we can analyze precisely, some parts we can analyze using probability, some parts we can only estimate using influences.
Some of the elements of the client’s life position:
| Familiarity with wealth |
| Lifestyle |
| Age |
| Dependants |
| Societal obligation |
| Self generation |
| Tax position |
| Drawdown rate |
Some investors build up a fortune from nothing and know what it cost them, others inherited and know no other life, still others have became millionaires overnight from some dot.com. Each of these people will have a very different outlook on how their money should be invested:
| wisely for the future |
| as long as it pays the bills and covers inflation, or |
| who cares, I can do it again. |
Some clients will have little knowledge of investments, leaving even the decision of what to do to an attorney, while others will want chapter and verse on each proposed investment. A high level of volatility in their wealth will horrify some clients, while others will be happy to ride a roller coaster in order to maximize gains.
In determining what decisions the system should make on behalf of the client, he system must determine the client’s desired level of involvement in the decision making process and their level of sophistication.
Some clients will be modest and reclusive, some will have a giddy lifestyle, and some will literally not know how to spend their health, being too busy making more. Taking over a poorly performing portfolio and greatly increasing the returns in the good times may lead to an increase in lifestyle which is unsupportable in bad times.
The wealth effect from rapid stock market gains over the last few years, may have ratcheted up the client’s lifestyle, or led them to acquire overpriced non-income bearing assets. The client may be loath to change their lifestyle, even as speculative gains disappear. Here is a difficult choice for the bank to make – propose a reduction in the budgeted rate of outflow and lose their business, or keep the outflow and expect to eat into the assets, or increase the risk level on the liquid investments while leaving the illiquid investments in reserve – investments which may be near worthless in a downturn.
Age usually carries with it a decreasing appetite for investment risk, almost inversely with the risk the portfolio could tolerate. Age can also carry with it a required change in who the portfolio should be managed for, from the client to the client’s intended heirs.
The number of dependants, their positions in their life cycles, and any special considerations – education, travel, or wedding plans – leads to the need for modeling of the cashflows of dependants and potential future dependants.
Old money often puts something back into society by way of college endowments or gifts to museums. Some clients will want every drop of publicity from a high profile bequest, while others may prefer to be anonymous, modulating the investment strategy deliberately into under-performing investments to achieve a similar beneficial result with no publicity.
New money may feel the need to be in hot new technologies, support green issues, or give new entrepreneurs a helping hand through Venture Capital trusts. In providing wealth management advise, the system has to anticipate these requirements as part of the service.
Tastes for societal obligation change over time, and the wealth management package builder needs to be just as sensitive to how the client feels about their wealth as to how much the wealth can grow over time.
An eye needs to be kept on potential publicity exposures - an investment in a company using Asian sweatshops may be good financially, but extremely bad in terms of the negative publicity it could generate for a client with a high public profile.
The client may be on a high salary, or have a large options package from the current employer. The bank may need to estimate the continuance of the salary or the viability of the options, based on its understanding of market conditions.
The rate at which the client is able to generate wealth by their own efforts will change the risk appetite for the wealth management package – not just that a higher risk can be tolerated, but it becomes necessary to keep the business by showing that the assets are performing adequately in the shadow of the client’s own capacity for wealth generation.
Wealthy clients will usually have a complex tax position, which will require significant modeling in its own right. The combination of the tax position and likely variation in drawdown rate over time may require considerable shaping of the income stream.
We need to assemble a model of the client’s particular financial circumstances – their other income producing assets, their rate of expenditure, their future liabilities, their tax position. The model is automatically assembled from components that interact with each other – an existing dependent child suggests a heavy education cost in the future.
The model needs to be run into the future, against the potential of different investment strategies. To successfully manage wealth requires at least a five or ten-year outlook, during which the market may change considerably, as well as the client’s position and needs. A ten-year outlook will almost certainly cross a downturn in the business cycle, with critical effect on some investment returns.
The above hardly exhaust the factors involved, but they do emphasize the difficulty of obtaining a simple financial analysis of all of the factors. The task is much more than shunning certain sorts of investments, then optimizing an investment strategy within the perceived risk tolerance of the client. The risk tolerance needs to be understood more broadly, and in most cases a broader risk strategy will be decided by the bank, after considering the other influences on the package.
Sometimes providing financial advice is straightforward; sometimes it is more like walking several tightropes at once. The respected investment name comes from handling the difficult cases without fuss.
Understanding the client requires a mixture of analysis and experience operating smoothly over a number of dimensions and combining into an integrated picture. Client feedback needs to also be incorporated into the model.
When a new client presents their portfolio of assets, valuable information can be gleaned from it as to their sophistication. Once the bank has the portfolio under its control, the portfolio needs to be monitored to see that it is meeting the goals set for it.
The bank maintains a large research team to give it sensitivity to the various asset classes. The market information being passed to the Wealth Management system is dense and complex, and may need to be analyzed by the system for consistency. Other information is required about the costs of changing assets within classes and across classes.
The Bank component of the model acts as the decision-making element. The information coming from the research area needs to be transformed into a form that is relevant to Wealth Management – the returns from the various asset classes need to be seen from the viewpoint of the specific client, with their particular tax and income shaping requirements. The bank is matching the client’s needs against the assets available in the market. Optimization of the portfolio is possible once all the relevant influences have been identified. There may be no acceptable solution, so the decision element would need to search for alternative strategies that would permit a solution.
A Wealth Management package stands in for a Financial Adviser, so if it is accepted by the client, its successful operation carries considerable responsibility for the bank. Wealthy clients can afford litigation over any perceived lack of care, so an opaque "black box" approach to computerized investment management may be hard to defend.
The behavior of the competition will influence the bank directly, as well as through the behavior of the client. Competition may be through return on portfolio, level of fees or quality of service. The larger the differential on investment returns, the more the bank must show that its strategy for the client is based on a sound knowledge of the client’s life position. Loss of clients to the competition can be analyzed by the system and used in modifying its behavior to other clients at risk.
This is the main interaction. Mostly it is one way, with the client providing information about their assets, needs and expectations. Occasionally the bank will attempt to influence the behavior of the client by suggesting a reduction in the rate of drawdown, or by requiring agreement before increasing risk.
The client may feel a strong "wealth effect" as the market goes up, and considerable fear and loathing as the market goes down. It is easy to insulate a client from the inevitable downturns, much harder to convince them of the wisdom of it in a long bull run. Successfully managing the market influence requires some estimate of the client’s psychology.
The elements of model machinery needed to implement the Wealth Management system are:
The model for a particular client needs to be constructed from components that are relevant to the wide variety of individual circumstances with which it must deal. These components are not stored as static templates or profiles, but as sub-models which, when connected together, form an active model. Machinery to construct the individual client model is part of the model, not an outside process.
The system must analyze a wide range of situations. It has available to it all of the elements of numerical and logical analysis. The analytic operators in the model can operate directly on probabilistic values.
Some of the decision-making requires simulation of financial aspects over time, with different influences being active over different time periods.
The knowledge about the future behavior of the market, and of the future needs of the client, are only known probabilistically. This knowledge is easily captured in distributions and relations, basic components of the model.
Much of the ability to estimate the needs and behavior of the client will come from experiential knowledge, also held in relations in the model. This knowledge can be automatically extracted from the client database or quickly introduced to the model on an ad hoc basis.
The model can create a local area where optimization is possible. It then uses forward cutting to obtain an optimum result. The process of optimization can include any other analysis, as optimization is part of the system’s normal operation. If there is no solution, it can move to a new local area by changing elements within the model.
The market can change its behavior rapidly over time, and new asset classes emerge. Client behavior changes over time, and tax law can acquire special cases rapidly. The system has to be easily modifiable. The eCognition model can modify its own structure, and can accept new pieces of knowledge that extend or modify its network. Its experiential knowledge can be automatically mined from transactions. The network structure allows extension in any direction at any time.
The model network represents all the data and processing of the system. Influences can be followed from where they arise to their point of application.
The Wealth Management system is intended for support of a financial adviser or for interaction directly over the web where the involvement of a human adviser would not be cost effective.
The description of the system has talked about wealthy individuals, but the system is equally applicable to investment management for small and medium sized companies. There are many companies where the wealth of the company is indistinguishable from that of the owner, except that taxation considerations may become more complex. There are also many manufacturing companies where the income from investments has long since overtaken the income from their core business.
The Wealth Management system will have an excellent model of the client. This means that the bank can provide a service over the web for the client to view the behavior of their portfolio at any time filtered through a lens representing their own needs and expectations. Without this filtering, the client may become confused about why they have their current portfolio, and where it is headed.
The good model of the client is also of advantage if some personal catastrophe should overtake them, and rapid re-planning of their finances is required.