The DOL Fiduciary Rule adds pressure on asset managers and financial advisors already encumbered by increasing competition and ongoing regulatory change. That’s why factor-based analysis is so valuable. Analyzing funds based on individual factor exposures provides the level of insight, detail, and transparency that enables managers to respond not only to the new rule but to demonstrate greater product differentiation and deliver better customer service.
Evaluating, grouping and recommending a specific product is now a statutory requirement but of course this must be done in the best interests of the investing client and with an eye towards compliance. And with the increasing range of product innovation across investment strategies, advisors must deploy processes that are equally effective and efficient across passive, smart beta, and actively-managed products. Firms providing investment advice and those who are offering products for them to sell now face the highest level of scrutiny when individual retirement savings are involved. There is much at stake with an estimated US$14.9 Trillion in IRA and Defined Contribution assets*. Asset managers must also explicitly disclose all fees and commissions. All this places greater pressure on their ability to justify costs and clearly communicate performance and its drivers.
It is a certainty that the processes and methodologies standing behind the recommendations made by advisors will receive significant scrutiny from multiple angles, not the least of which will be internal compliance and legal reviews. Articulating their firm’s position is critical, otherwise, they risk a legal vulnerability of non-compliance and losing business. This takes putting a new roadmap in place.
The Roadmap for DOL Fiduciary Rule Compliance
Complying with the DOL Fiduciary Rule can be confidently met with an objective, factor-based analytical framework – a method of analyzing funds based on their individual factor exposures – as well as other objective criteria (including fees, performance, and risk). Evaluating products using commonly understood and accepted factors within style categories – such as Value, Quality, Growth, and Momentum – achieves transparent and granular insight, along with the underlying details and metrics, to support compliant recommendations. It is equally applicable across any investment strategy (passive, smart beta, quant, etc.) and any approach to recommending products, including self-service or robo-based paths.
A factor-based approach will effectively drive the continual cycle of monitoring, reviews and refinement of product recommendations and reporting for clients. This framework evaluates individual funds as well as narrowing the research process by forming groups or categories of products.
Creating a recommended list of products
The benefit of factor analytics when assessing products is the ability to put them on a level playing field. Without transparent factors, identifying any fund’s overall exposures – such as to sectors, regions/countries, or styles – might easily be missed. Furthermore, objective factor-by-factor assessment enables deep comparisons between products to understand their respective performance drivers or which ones might be bearing greater risk. Knowing various products’ underlying factor exposures can determine if they meet the selection criteria to recommend them based on how well they match clients’ investment goals.
Grouping products to focus recommendations
In many cases firms will reduce large sets of possible investment options into smaller groupings to narrow the universe of products. This requires that the advisor communicate how the grouping was determined. It is also important to incorporate a full spectrum of products into each group. For example, there is a tendency for individual investors to think about index and passive products as a group or investment category unto themselves. This is not in their best interest. To make the best investment decisions, there should be an array of different offerings considered within a group.
Groups also need to be much more specific to allow for more relevant comparisons and to support recommendations. As an example, categories such as “U.S. Large Value” and “U.S. Low Volatility” are too broad and not well defined. Defining groups more specifically, such as “U.S. Large Value – Quality & Momentum” and “U.S. Mid Cap Low Volatility – Value” would be much more practical. And transparency into specific factors within these style categories can often highlight key differences between funds. We should expect to see products in every group representing the full spectrum of product options – from index/passive, smart beta, smart alpha and actively managed products.
Fee compression and competition
With tighter groups of products offering transparency and better decision-making, the question of fees becomes less of an issue. Products will have to sharpen their competitive edge in demonstrating performance for the fees they charge. This will lead to fee compression within the categories. People also might look at the DOL Fiduciary Rule as accelerating the shift to more passive products. However, with the expected move to more defined groupings that include a wide spectrum of products, combined with fee compression, the opposite could actually be true.
A Solution for a Changing Landscape
With a framework to objectively evaluate equity funds at the factor level, asset managers can ensure compliance, differentiate their products, and meet the requirement of clear and transparent client communications. Adopting an objective, factor-based analytical method enables them to confidently fulfill their new responsibility to act as fiduciaries, satisfy new client expectations and embrace an evolving investment landscape. Firms can meet the DOL rules, and be ready to take on the compounding challenges of asset management.
* Source: Investment Company Institute, Defined Contribution Plan Participants’ Activities, 2016