5 Reasons Why Asset Managers Should Make Machine Learning Part of Their Daily Routine…and Why Their CRM Software Should Help (Part 2 of a 3-Part Series)

Asset Management Transformation Series: How Firms are Rebooting Sales and Service (HINT: It’s Much More than CRM)

The challenges faced by asset management firms on both the institutional and wholesale sides are consistent. The technology to support it, however, falls short. Regardless of whether you use a “horizontal” CRM solution (e.g., Salesforce) or a point solution (e.g., SalesPage), you are missing opportunities. The right CRM software can do so much more than what you have come to expect, and it plays an important role in a bigger picture that includes technologies like predictive analytics and machine learning.

In this 3-part series, we discuss how CRM as an operational platform can fill the gaps you’ve been dealing with for too long. Part 1, Does Your System Measure Up? What Asset Management Firms Need in CRM Software, discussed the critical components a CRM software solution for Asset Management should provide. In this blog, part 2 , I discuss the role machine learning and predictive analytics play in keeping you ahead of the curve. Part 3 covers tools that extend CRM —tools that you probably already have—that will help you drive more productivity and drive even higher performance.

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Part 1 acknowledged that, while traditional CRM systems help asset managers to a certain extent, they are not equipped to help with efforts to determine which relationships and opportunities are, or have, the potential to be the most profitable. So, how do you determine if your CRM system has the ability to fill this vital role?

The key is helping you organize your data and your day to get the most value possible, which means ensuring your CRM not only talks to, but more importantly, collaborates with the other applications you depend on. More than an application, CRM is a platform—a foundation that supports ALL your business-critical applications.

This next blog in the series shifts gears a bit…to machine learning.

Before you stop reading, understand that this blog is not science fiction. It’s not written for technology geeks or conspiracy theorists. This is about how machine learning is a very real technology and vitally important to asset managers who are trying to capitalize on every relationship and opportunity…and so it should be a capability offered by your asset management software solution.

There is certainly a lot of buzz—and buzz words—around machine learning and artificial intelligence. Things are advancing quickly, and so is the potential of this technology for every industry, including asset management.

But it can get overwhelming, and with all the hype, asset management firms might be asking, “Why do we care?” The bottom line is this: Machine learning can take massive amounts of information and process it in ways a human simply cannot. Used appropriately, machine learning can significantly enhance the experience for a seller and increase the likelihood of winning.

By the end of this blog, the hope is that you will see machine learning as we do: a usable, practical tool you should be using every day. In fact, you shouldn’t even think about it, because it’s an integral part of your routine. The following are 5 reasons you can make machine learning a powerful part of your daily routine…and why the right CRM software solution absolutely must give you that ability.

Reason #1: You can focus on the opportunities you’re more likely to win

Asset management firms are constantly responding to RFPs, which are difficult and time-consuming. They take a great deal of time to complete, and there is no guarantee you’ll win. Wouldn’t it be great if you knew which RFPs to focus on and which to pass on?

In a traditional world, it’s more of a shotgun approach. You received the RFP, read it, assign what attributes you can to sort it, and manage it from there. You will likely communicate with the client, and you might have a good relationship with the consultant who brought the RFP to you, which might get your proposal put on the top of the stack the client is reviewing. In general, however, you will end up going after every RFP in much the same way.

Enter machine learning. By plugging specific pieces of data into a decision model—including the characteristics of the RFP, the consultant that brought the RFP and your relationship with that consultant, the typical strategy used for that type of RFP—you arm your system with enough information to use machine learning to determine the likelihood of winning that RFP. The machine learning algorithms apply all these facts to past success rates as well as factors that play into those success rates. The system then recommends which RFPs you should focus on. The result: a higher win rate and a better use of everyone’s time.

Reason #2: You can identify whom you should call first…

Every morning, asset managers sit down at their desks and make a decision: Who they will contact and in what order. Traditionally, they make this decision based partly on relationships, partly on market events—but there is no hard and fast method for prioritizing how you stack-rank your day.

With machine learning, you plug in every factor you are aware of, which is combined with what the system knows about past performance, market events, and so forth—and the result is a very carefully calculated ranking that is optimized for the highest success rate. Again, the system is able to take volumes of information and boil it down to a dependable recommendation.

Reason #3: …And whom you should call on first (i.e., trip planning)

If you’re on the road, you have the same decisions to make: Who do you focus on? The difference is that you have geography to contend with. For you, trip planning is critical. Prioritizing who you’re going to see first and making sure you’re seeing the right people in a particular location can mean the difference between a successful day and a day of frustration.

There are actually many different technologies and technology companies, like Introhive, that support this function, but it’s important that they interact appropriately with your CRM system so machine learning can contribute to route planning. NOTE: This illustrates the true power of CRM as a platform—the ability to connect and fully integrate with tools like those mentioned above to create not a piecemeal grouping of disparate applications, but a cohesive, seamless solution that fits the needs of your firm perfectly. This will be discussed more in depth in Part 3 of this series.

Reason #4 Your intuition and experience will be backed by solid data

Every great asset manager attributes his or her success at least in part to intuition. We are not taking that away—but intuition will only take you so far. The hard fact is this: Intuition is based only partly on facts, and it can be influenced by emotions and other human factors. In fact, according to On Course Advisors, most professionals—even those who are considered senior and have decades of experience—who make business decisions without the appropriate segmentation of the data actually make the wrong decisions the majority of the time. Like any human, they often use qualitative criteria, which is not dependable. Let’s be honest: We all know this, but until now, there hasn’t been much we could do about it.

However, once they start segmenting the data, even at the simplest level (typically only a few variables) and even without machine learning, the results improve significantly. So, it’s proven that using quantitative methods works. Imagine the results if you add machine learning. By dialing up the quantitative level, using more, multi-variate statistics (machine learning typically uses 100+ variables) that you define, you’re augmenting your intuition with technology and blending in your great relationships, creating the perfect recipe for predictive analysis—and success.

Machine learning also helps you avoid the pitfall of some of our less helpful human characteristics. Emotions can also impact your decision-making in a negative way. Say, for example, you have a long, established relationship with a consultant, but the consultant hasn’t been producing lately. You might be tempted to go with your faith in that relationship, which could backfire. Machine learning keeps you “honest”—it’s that little voice that says, “Are you sure you want to do that? Because the statistics say you should do this instead.” It might be an uncomfortable conversation, but it’s almost sure to be one you won’t regret having.

Reason #5: It’s much simpler and less expensive than you think…really

So, here is the part where we tell you it’s simple. Based on past experience with technology, you might be dubious. Based on what others might have told you, it will be a huge, costly project. The former is true; the latter is false…IF you have the right solution. Returning to the RFP example from earlier: You’ve read through the RFP and identified the characteristics that go into the attributes you track for RFPs and enter that data into CRM.

Based on your experimental model that has been “trained” based on history and the data you entered, the system can provide you with the percentage of likelihood you will win the business. It’s that simple, and it’s something you’re already doing—entering data. No learning a new application; no complex manipulation of data. The system does the heavy lifting, you get the benefits, and the system continues to learn every time you use it. As the data sets grow, your system gets smarter and smarter, narrowing the results and increasing the likelihood of a win.

Still don’t believe it? Let us show you.

The purpose of technology is to make what you already do easier and better. We understand that successful asset managers are doing things right. We’re not saying you should quit everything you’re doing or have ever done. What we are proposing is to let the right technology put what you’re doing on steroids…in a way the human brain simply cannot.

Of the many abilities CRM as a platform like Microsoft Dynamics 365 offers, one of the most powerful is machine learning. Far from science fiction, machine learning as a real, applicable ability that can elevate your business far beyond what you can imagine. To see machine learning in action, talk to the Financial Services experts at AKA Enterprise Solutions.

Continue to Part 3 of this blog series, which digs into all kinds of exciting tools that work to connect your world and extend CRM for even higher performance in Asset Management.

By | 2018-11-05T21:09:09+00:00 June 7th, 2018|Machine Learning/AI, Sales & Service (CRM)|0 Comments
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Contributor: Michael Quattlebaum

As a Senior Functional Solution Architect, Michael has 20+ years of experience in technology and financial services, focusing on a business-centric approach to problem solving. His expertise in functional and technical design enables him to convey confidence to end users as well as C-level executives.

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