Marketing Darwinism - by Paul Dunay
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Marketing Darwinism - by Paul Dunay
Artificial Intelligence, Asset Management, Innovation, Risk

Managing Risk in Asset Management

Romi Mahajan President Pepper
Pulak Sinha CEO Pepper

Well, that’s why we build warning systems and endow people with the intelligence to act on them. And that’s why we have regulations and ask organizations to comply. It is worthwhile pausing for a moment to consider what’s at stake. When we look at the Asset Management industry as a whole, we see that it manages in excess of $120 trillion world-wide. Such sums are staggering and remind us of the famous, though apocryphal Willie Sutton story- “that’s where the money is.” The largest individual firms manage $3+ trillion. Put simply, even small failures in this industry have cross-sectoral, and fundamental effects on the economy as a whole and, ultimately, lives. We cannot afford that. Ever.

This industry cannot afford to meet the challenges of complexity, growth, regulation, compliance, and risk management with technologies that are built for other industries and ported to Asset Management after-the-fact. This industry cannot afford to meet these challenges as a technology laggard, as one so occupied with costs that it loses sight of the big picture.

Whatever the difficulties and stresses of day-to-day life in the industry, we must reject the idea that “it’s good enough.” Firms that manage hundreds of billions of dollars and dazzle investors with talk of AI, modernity, and innovation that they turn around and manage assets, dollars, and decisions on Excel are on the precipice. It is not a matter of if but when. Even the most venerable names have their “Kodak” moments when they stop paying attention to systems and cultivate a culture of dismissal.

It’s not simply a matter of efficiency, security, error management, or expedience. It’s not simply a matter of maximizing ROI by a basis point or two. What’s at stake here are “company extinction” events.

Modern business and technology have converged into a singularity. The stakes to get it right are high. Therefore it is high-time the Asset Management industry faces reality squarely.

Let’s be smart. Don’t settle for “good enough” because one day it will fail. Invest in the right systems and don’t run your business on Excel. Think of reporting requirements not as onerous but as good gut-checks. Together, united, we can build a culture of success.

March 20, 2023by Paul Dunay
AI, Artificial Intelligence, Asset Management, AssetTech, Fintech

The Private Credit Data Opportunity

Second in our “AssetTech” Series

By Romi Mahajan President Pepper
and Pulak Sinha, CEO Pepper

The Financial Services sector is every-changing and frenetic. As conditions change, markets change, as consumer behavior changes, markets change, and as new paths for ROI are created, markets change. That’s the name of the game in FinServ.

Couple this rapidity of change with the sheer size of the market and the results are epochal. One sliver of the market- the world of professional Asset Management- breaks the tape at $120 trillion AUM world-wide, a staggering number that exceeds global GDP. With a $120 trillion river running its course, even tributaries can be huge and powerful.

Enter the world of “private credit,” a fast-growing marketplace that now exceeds $1.5 trillion in investment with annualized deal-size in excess of $35 billion. As companies and other entities seek new sources of funding and as investors seek new forms of ROI generation and liquidity, the private credit market has burgeoned. New funds are minted daily.

For all investment types and asset classes, data is central to the story, but even more so with regard to non-public assets. Here, data and its connection to proprietary methodologies, valuation methods, and calculation is paramount. Further, ensuring that all parts of the organization are using the same data and the same methods to evaluate, value, invest, track, and report on deals is key to success. The lack of the proper platforms and controls is a sure-fire way to create internal friction and to slip-up in the marketplace. In private credit, data is the watchword.

As we mentioned before, private credit is a huge asset class, but very few companies build technology platforms and solutions specifically for this –and adjacent- industries. This is a huge miss in the technology industry as a whole. The private credit industry deserves better.

The data opportunity in this space is enormous. Even industry-watchers would have been challenged to notice the space even two years ago. Now it has emerged as a colossus. That’s why “AssetTech” – technology platforms that are innately and natively responsive to the needs of Asset Management- matters; the size and importance of the marketplace is unmatched.

The private credit data opportunity is real. We are eager to discuss it with you.

February 24, 2023by Paul Dunay
Artificial Intelligence

What does Computer Vision have to do with the Price of a House?

A guest post by: Romi Mahajan, CMO Quantarium

Residential real estate – peoples’ homes – is the world’s largest asset class, tipping the scales at almost $200 trillion worldwide.  This number is staggering to many, including those in the housing industry.  Larger even than the sums involved are the emotions – a family’s residence is likely its largest investment and one from which, so many other life-factors radiate:  Who are your neighbors, what schools do your kids attend, are you safe, how close are you to good medical care, and so on.  Insofar as this is true, the housing sector can never be given too much attention by Economists, Sociologists and even Technologists.  Still, in many ways the sector has been given short shrift.

Consider a matter at the heart of the industry – the value of a particular house.  What appears to be a simple question with a simple answer is not.  Sure, one can look at the basics – how big it is, the year built, comparable houses in the neighborhood and so on.  One can even attempt to factor in other variables – school district, crime statistics, proximity to the beach, and a host of other things.  All said and done, all of these factors are “external” and in many ways “non-specific.”

Let’s pause for a moment.  While these factors are indeed external, we have to ask ourselves a basic question – how do I get specific?  How do I assess the value of a particular house, looking beyond these basic factors and in the process taking into account the condition of the house and the nature of its interior landscape?

For most of us this is an obvious question.  After all, if you put in a lot of money to modernize or refurbish a house, you would expect that its value rises, even if your work and effort is not recognized in the external statistics being looked at for valuation.  If you, on the other hand, paid no attention to the house and allowed it to atrophy, you’d likely expect the value to diminish.

This issue is often “solved” by Appraisers, who theoretically take into consideration all of these interior and condition-based factors when assessing the value of a house.

Now, we enter a world fraught with problems.

For the purposes of this short piece, we won’t get into the debates about the objectivity of Appraisers or even about the shortage of talent that is delaying closings in many large markets (in the US for sure.)  These issues are fertile grounds for discussion, elsewhere.

No, the main issues we intend to dissect here are the issues of scale, speed, and customer experience.

In the US, there are over 100 million residential units.  Now imagine you work at a bank or other institution that originates and/or “owns” millions of mortgages and wants to determine the value of your portfolio in toto?  Imagine, further, that you need to do so every month.  After all, you need to keep track of your assets, make decisions about where to keep houses and where to sell houses, and assess your risk in holding these mortgages.  The issues of scale and cost are enormous.  You certainly can’t send an appraiser to each house.

Imagine a different scenario.  A consumer lives in a city with a very fast market and needs to make decisions on the spot whether to buy a house.  Waiting even a few hours, not to mention days, can mean losing a house.  In this cauldron, determining the true “value” of a home has to be done instantaneously.  Here, the issues of speed are paramount.

Finally, imagine you are a real estate agent with a demanding (and rightfully so) customer who wants to buy a house.  You have visited 10 houses to determine fit and have been disappointed by their dilapidated interiors.  You are not paid for your time, only for results.  If only, there were ways to determine condition and value based on condition in a way that was easy for the customer (in this case, you.)

Enter technology, specifically AI and its offshoot, Computer Vision.  Artificial Intelligence yields a potent set of tools for real estate, starting with valuations.  First of all, AI is “better at the basics” than non AI methodologies.  To get even a basic valuation of 100+ million properties every month is not trivial; with AI, the entire US footprint can be run in hours not weeks.  The idea is simple:  Computers can learn from data sets of a critical mass, then keep improving their outputs as more data comes in.  Machine-learning is just that- machines that actually “learn” and thus can offer results and outputs that are neither obvious nor simply the result of brute-force methods.  AI can thus help with the scale and speed components.

Computer Vision comes in here in a delightful way.  If you look at house-listings, they often come with a multitude of pictures.  Computer Vision can analyze and categorize these pictures- with speed and fidelity- thereby assigning “condition” scores to kitchens, bathrooms, and other hotspots in the house.  In this way, they can help offer a “condition-adjusted” value.

Put all of this together and you get a powerful mix.  Automated Valuation Models (AVMs), powered by AI can provide accurate valuations at scale and with enormous breadth.  Add condition-adjustment, powered by Computer Vision, and you start to see technology giving its due to the vexing problems and incredible opportunities in the real estate industry.

May 2, 2021by Paul Dunay
Advertising, Big Data, Business Intelligence, Cloud, Data, Data Analytics, Data Mining, Innovation, Strategy

Real Estate, Real AI, Real Value

Submitted article by Romi Mahajan

Chief Commercial Officer, Quantarium

The world of technology is known as much for its hype as it is for its legitimate innovations.  Atone level, this is understandable. Dreamers can only accomplish big things when they dream big and followup on those dreams with supporting rhetoric. At a different level, however, it serves to dupe consumers, customers,and investors into alchemist fantasies that often defy the laws of physics.  What we need, naturally, is a balance.

With AI, and claims about it, we as a community have come to the point where we have to decide if we are okay with “fact-checking.”  Are all claims about AI fair and accurate?  Do all companies that claim to be “doing AI” pass muster in that regard? After all, haven’t many organizations referred to any and all of their “data”initiatives as AI? Have we diluted the term so as to make it meaningless?

Discerning investors have started to kick the AI tires.  Highly skilled Scientists and Engineers increasingly refuse to be beguiled by marketing claims, choosing instead to dig deeply into the code and methodologies surrounding its production before allowing themselves to be recruited by the countless organizations that seek the limited supply of talent. 

Perhaps more relevant, still, is that people in all roles ask one fundamental question:  “Is there any relevant and practical application to the AI work you are doing?”

On all these matters, Quantarium can hold its head high.  From “Real AI” to “Real Applications of AI,”Quantarium is altering and enhancing our notions of what is possible in residential real estate, the world’s single largest asset class.

Take for instance an important but mundane question, likely asked by millions of people every day.  “What is my house worth?”  Several pundits will offer several answers to this question, no doubt.  But, will the answers be accurate and in this case, what does accuracy even mean?  What data goes into the answer?  Do we have all the data we need?  Is it all available? Do the data we collect account for every single aspect of the house that could or should go into the valuation? 

Now take an extrapolation of this question with magnified scale.  Imagine you are the CEO of a large bank that “owns” half-a-million residential mortgages. What is your portfolio worth?  How much risk are you holding in the portfolio?  Are you too exposed in a particular geography or demographic?  Do you have sufficient data and the ability to process and make sense out of it?  Can you do this all with the speed that is called for by regulation and market conditions?

These questions are easy to pose but hard to answer.  Further, while these questions may not seem “sexy,” they underscore the reality of the single biggest source of economic value and for most families the single largest source of equity.  Using AI to drive accuracy, speed, and scale in this market is complex, genuine and incredibly important.Indeed, real AI applied to real industries with real outcomes is the name of the game. Therein lies the balance we seek, the convergence of both the hype and of the reality.

December 18, 2018by Paul Dunay
Artificial Intelligence, Big Data, Business Intelligence, Cloud, Data, Data Analytics, Data Mining, Innovation, Strategy

Interview with Clement Ifrim, CEO and Co-Founder, Quantarium

Marketing Darwinism: Clement, tell us about Quantarium.

Clement: The company is inspired by insights from Quantum Physics and the potential inherent in applying them to Machine Learning approaches within an A.I. framework. We have organically gathered the analytical methods of fields as far reaching as Quantitative Genetics to build a leading Artificial Intelligence company that enables competitive advantage in vertical industries via advanced predictive and propensity models along with smart decision-engines. To be sure, there remains a lot for Quantarium to accomplish and indeed we have the ambition to match, though we are quite proud of our synthesis to date and the benefits our customers are enjoying each day.

Marketing Darwinism: Can you tell us which verticals you focus on mostly?

Clement: The beauty and peril of A.I. is that it can seemingly apply to everything and that can be intoxicating, thus both market and organizational focus to execute become paramount. Our first salvo is residential Real Estate, a $20 Trillion asset class that represents in a meaningful personal perspective, the most important of all sectors because it constitutes the largest purchase a family ever makes. Quantarium looks at Real Estate from a perspective not only of Data (and there is a lot of Data!) but also of modeling scenarios of what “could” be. For both financial institutions that “own” and service mortgages and for the individuals who own homes, understanding the “deep” economics is very important. From valuations to other analytical models, Quantarium intends to revolutionize the approach and economics.

Marketing Darwinism: Clement, you have a background in large companies like Microsoft, how is it being a CEO of a start-up.

Clement: Thanks for the question. There is nothing headier than building something with world-class people who humble me every day with their vigor and intelligence. At Microsoft, I learned how to manage A+ teams and to think about products and customers at scale. Applying that to the need for speed in the startup world is my biggest challenge and joy.

Marketing Darwinism: Clement, I must ask you this. A.I. has become a “buzz phrase” …how do you distinguish yourself.

Clement: You are certainly correct about that. The technology business is very much about fashion and phraseology. Unfortunately, it is also often about false claims as well. Quantarium’s founders team, with Ph.D’s and accomplished experts in the field, undertook the approach that A.I. is best when it enhances the ability for people to both arrive at a valuable truth in a quicker and more judicious fashion, and then start to predict future truths, or certainties, given the current business exigencies. Quantarium established itself as an A.I. company from the get-go, it’s in our DNA; as a matter of fact, the first platform Quantarium built, QVM/Quantarium Valuation Model relied on M.L./A.I. technologies such as evolutionary programming when “Artificial Intelligence” was not such a buzz phrase yet. Our team consists not only of award winning Mathematicians and Engineers but also of some of the best “technology translators” in the industry. Algorithms and A.I. are indeed assets, however when you add them to the human agency and agility, you get real applications of real A.I.

Marketing Darwinism: What’s in store for Quantarium in the next phase of your growth?

Clement: Good question. While structured as a tridimensional growth approach, with a clear focus on increasing market share, innovation / differentiated I.P. and product expansion, in many ways we’ve been silent for too long. We enjoy genuine, solid relationships with our customers and partners but haven’t “splashed” in the market yet. That has been by design but the time has now come to shout from the rooftops. We’re showing up at conferences like the O’Reilly AI Summit and Strata. While we remain humble and true to ourselves, we are bold at the same time so watch out for us.


About Clement

Clement is Co-Founder and CEO of Quantarium, an Artificial Intelligence company enabling vertical industries via advanced Predictive and Analytic models, and smart decision-ing engines. As the name of the company suggests, inspired by Quantum Physics and fueled by the power and potential of Machine Learning such as synthesizing and leveraging approaches from Quantitative Genetics, towards resolving significant predictive challenges, Clement is an accomplished international professional for leveraging Data Science and A.I. as well as a proven business leader.

With degrees in Computer Science, Clement spent 14 years building large-scale and Enterprise-level software products and services in areas traversing Content Management and Enterprise Search. Responsible for strategy and product development, Clement directed enterprise teams for Microsoft such as SharePoint, and MS Enterprise Search, while building a proven track-record for recruiting and developing teams with exceptional culture. Prior to Microsoft, Clement started and ran several software companies.

Originally hailing from Romania, Clement lives in the Seattle-area with his wife and children. He is actively involved in a variety of philanthropies and applies philosophy to technology as he builds lasting companies.

August 14, 2018by Paul Dunay
Artificial Intelligence, Branding, Business Intelligence, Customer Experience, Customer Support, Data Mining, Reputation Management

Artificial Intelligence is changing Customer Service

No matter how much technology has changed our day to day lives, both at home and at work, what remains essential to running a successful business is customers—how you treat them, how they feel about your product or service, and whether they share those good (or bad) feelings.

In decades past, interacting with customers and helping to manage their problems and expectations was something that was left mostly to humans, which meant any good or bad things could also be subject to staffing or competing deadlines. But technology has helped with that in a unique way: by automating much of the customer journey through artificial intelligence, or AI.

Customers may not realize it, but a part of the process with many companies is already managed by AI. It’s helping with predictive needs, to name just one area. And its use will only continue to grow. This graphic explains what it’s doing and how business will continue to use AI.

Click To Enlarge

Rise of the Chat Bots: How A.I. Changed Customer Service

Via Salesforce

November 14, 2017by Paul Dunay

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Welcome to my blog, my name is Paul Dunay and I lead Red Hat's Financial Services Marketing team Globally, I am also a Certified Professional Coach, Author and Award-Winning B2B Marketing Expert. Any views expressed are my own.

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