Would You Take Financial Advice From A.I.?

 Sttill waiting for a good opportunity.

Would You Take Financial Advice From an A.I.?

By The New York Times,  May 22, 2023

As of now, the technology is promising, but its not 100% accurate.

Even if you don’t think you’re familiar with it, chances are you’ve already been using generative A.I.

Paul Weiner, an artist, has been experimenting with artificial intelligence for the past year, generating A.I.-created visual disinformation and seeing whether he can get the images to spread. But recently, he turned to ChatGPT, a chatbot that has the ability to respond to complex questions, for a much different reason: With his 30th birthday looming, he decided to ask it for advice about retirement planning.

"Maybe ChatGPT would have some answers that I might otherwise get from someone who I'd have to pay a lot of money to," he said.

Generative A.I. like ChatGPT has knowledge workers gripping the rails, bracing for how it might affect their jobs, and consumers leaning in to see what costly services could soon be replaced with a prompt. As the investment industry turns to artificial intelligence as a financial planning and advice tool, the values of accuracy, humanity, security and accessibility are jostling for prominence. In the future, who — or what — will we be asking to advise us on some of life's most important decisions?

From The New York Times

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How does Quantum Computing Impact the Finance Industry?

Intriguing connection ...

How does Quantum Computing Impact the Finance Industry?

By Cointelegraph May 5, 2023

QCs in banking can be a game changer due to the potential of multiplying the speed and volume of calculations and transactions.

Based on the World Economic Forum's estimate from 2022, national governments have invested more than $25 billion in quantum computing research, and over $1 billion in venture capital deals were closed in the previous year. Quantum computers (QCs) are in the early stages of development, and there are many technical challenges that need to be overcome before they can become practical tools for everyday use.

Nevertheless, they have already demonstrated great potential for applications in a wide range of fields. QCs have the ability to solve complex mathematical problems exponentially faster than classical computers, making them ideal for several complex tasks. The finance industry is one of the first runners in testing the technology. However, from the military to pharmaceuticals, logistics and manufacturing companies, several industries are experimenting with QC.

The mentioned features of QCs can have an enormous impact on the future of financial services. There are several tasks where financial forecasting and financial modeling can be supported by QCs for faster and more accurate processes. Notably, portfolio optimization, risk management and asset pricing are some of the most mentioned examples. However, their potential advantages and threats to cryptography make it important for financial service providers to monitor the technology.

Collaboration is crucial in the area of QCs due to the fact that technology and software development enable the revolution. Accelerating programs are initiated by the largest tech companies for experimentation with their hardware, software or cloud solutions, such as IBM, Microsoft, Google or Amazon.

From Cointelegraph

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Crypto Declared a Risk

Crypto is Possible Systemic Risk

ACM NEWS

FSOC Warns Crypto is Possible Systemic Risk

By Politico, October 4, 2022

Said U.S. Treasury Secretary Janet Yellen, “We've seen very significant shocks and volatility within the crypto asset system, particularly over the last year.”

Top U.S. banking and markets regulators on Monday warned that the crypto industry could pose a major risk to the financial system if lawmakers and agencies don't act soon to set ground rules.

The Financial Stability Oversight Council — a Treasury-led panel of top officials from the Federal Reserve, SEC and other agencies — released a 120-page report that identified a wide range of regulatory gaps and market risks affecting everything from Bitcoin trading platforms and stablecoins to consumer protection and cyberattacks.

Those risks will get more severe as the industry expands and digital asset businesses forge ties with traditional financial institutions like banks and payment systems, according to the report, which was produced in accordance with President Joe Biden's March executive order on crypto.

From Politico

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Deep Learning and Quantitative Finance

Of special interest, plan to attend:  

March 16 Talk, "Deep Learning for Sequences in Quantitative Finance" with David Kriegman

Register now (and more info)    for the next free ACM TechTalk, "Deep Learning for Sequences in Quantitative Finance," presented on Wednesday, March 16 at 12:00 PM ET/17:00 PM UTC by David Kriegman, Professor of Computer Science & Engineering at the University of California, San Diego. Andrew Rosenfeld, Senior Vice President at Two Sigma, will moderate the questions and answers session following the talk.

Leave your comments and questions with our speaker now and any time before the live event on ACM's Discourse Page. And check out the page after the webcast for extended discussion with your peers in the computing community, as well as further resources on deep learning, machine learning, and more.

(If you'd like to attend but can't make it to the virtual event, you still need to register to receive a recording of the TechTalk when it becomes available.)

Note: You can stream this and all ACM TechTalks on your mobile device, including smartphones and tablets.

The quantitative investment process can be viewed as one that takes in raw data at one end and executes trades that buy and sell financial instruments at the other end. The process naturally decomposes into steps of feature extraction, forecasting the returns of individual instruments, portfolio allocation to decide quantities to trade, and trading execution. Many of the steps in this process are readily expressed as machine learning problems that can be addressed using deep learning sequence methods. This talk will provide an overview of this pipeline and deep learning for sequences. No background knowledge in finance or deep learning is required. .... ' 

Autonomous Financial Operations

Introduction,  uses and implications:

How Ready are you for Autonomous Finance Operations?  in HBR

August 10, 2021

Few technological advances fuel the public imagination like the concept of autonomous vehicles. It’s easy to understand the broad appeal of self-driving cars, operating without any need for human involvement or intervention, potentially boosting safety and productivity and curbing energy consumption.

Now, imagine how implementing a similar complex technology could support businesses by using autonomous finance operations to significantly improve organizations’ spend strategies and finance management.

Corporate finance has traditionally remained reliant on largely manual efforts and legacy tools, making it one of the most time-consuming, labor-intensive, costly functions. Despite the introduction of automation software to manage repeatable, basic tasks, many processes remain fundamentally unchanged from the way they operated decades ago, with manual effort at the core of the undertaking.

But when those same finance teams have autonomous technology to support them and to provide critical spend insights, they are finally free to think bigger about how to strengthen their organizations and to have a greater impact on overall transformation and growth.

That future is now a reality for many modern CFOs and their teams. And, much like fully-self-driving cars, the promise of fully autonomous finance operations and all the advantages they might bring is growing closer and closer.   .... ' 

Small Business Exporters

From friend Steve King, who has run this blog on small business needs for years:

Barlow Research on Small Business Exporters

Barlow Research   is one of our go-to sources on all things related to small business use of financial services.

Their article Five Truths about International Business in the Middle Market covers survey research on the exporting and importing by U.S. firms with between $10 million and $500 million in sales (midmarket companies).

As shown in the Barlow chart below (click to enlarge), the key finding is that about one-third of firms in this size category conduct business internationally. ... ' 

Towards Decentralized Finance

Notable look at where this might be going.  Getting some reading that it is being much more broadly applied than expected.   But there remains some strongly based skepticism.  

Traditional Centralized Systems in Business & Finance

Blockchain is transforming the future of the financial industry, as well as many other businesses.

Posted by   Ryan Kh  January 19, 2021

Blockchain in finance

The Incredible Predictive Analytics Capabilities Of Blockchain

Blockchain is one of the most important technologies to shape the world. One of the biggest industries that has been affected has been finance.

The market for blockchain technology in the financial sector is expected to reach over $3 billion by 2024. The question many experts are asking is: “what factors are driving the growth in blockchain in the financial industry?”

Blockchain Transforms Financial Industry

The world constantly changes and evolves. Whether it is due to the environment or human innovation, life progresses. It is up to mankind to adapt and make the best out of the circumstances we experience. Life has its ups and downs, victors and victims, and challenges and opportunities.

In business, we learn about how the business cycle accurately imitates life. There are good times and bad times. There are even okay times. It is those times in business and life that people must embrace and learn from. They must learn to harness their strength to persevere through change to experience the beauty of it.

With all that being said, we are emerging in a period of evolution in a world plagued by troubling times. A time that will fully embrace the advancement of technology in all areas of life. A time that world leaders and innovators refer to as the fourth industrial revolution. The change that seems most prevailing in terms of technological advancement is in business and finance to kickstart this revolution. In the year 2009, a man under the alias of Satoshi Nakamoto invented the first digital currency called bitcoin and initiated the use of blockchains. ... ' 

AI in Banking

Useful survey of AI uses in Banking..Notable use of BPM.

Barclays Innovating in use of AI in Banking

Barclays Bank is emerging as an innovator in the use of AI in financial services. The UK bank, ranked 20th on the S&P Global’s list of the top 100 banks, works with suppliers of AI products and services more than it develops AI applications in house, according to a recent account from  emerj.

Here are three AI initiatives underway at Barclays and the industry partners working on each one:

Risk Modeling with Simudyne, employs predictive analytics to assess loan risk
Voice Recognition for Authentication, with Nuance, aims to apply verification and authentication using voice recognition;

Business Process Automation with IBM, a project to automate debit card deactivation, and analyze customer feedback.

New Combinatorial Optimization Algorithm

Combinatorics are of particular interest to me, are part of any kind of complex process choice problem.  Note the use of annealing, being used in some quantum methods.  Here a new advance, examining.

Optimization Algorithm Sets Speed Record for Solving Combinatorial Problems
IEEE Spectrum
John Boyd
February 10, 2020

Researchers at Toshiba Corp. in Japan have developed a quantum-inspired heuristics algorithm that is 10 times faster than competing technologies. In October, the researchers announced a prototype device implementing the algorithm that can detect and execute optimal arbitrage opportunities from among eight currency combinations in real time. The researchers claim the likelihood of the algorithm finding the most profitable arbitrage opportunities is greater than 90%. The team implemented the Simulated Bifurcation Algorithm on a single flat-panel gate array (FPGA) chip, and were able to run 8,000 operations in parallel to solve a 2,000-spin problem. In a separate test using eight GPUs, the system solved a 100,000-spin problem in 10 seconds—1,000 times faster than when using standard optimized simulated annealing software.  .... " 

Seeking Digital Identity

On capability long considered for blockchain was assuring identity.  Just published draft guidance below. 

FATF Releases Guidance on Global Digital IDs as Use Cases Grow  in Coindesk 

The Financial Action Task Force (FATF) wants financial institutions to prepare for the global expansion of digital identification systems.

FATF published its draft guidance on digital identity Thursday, for governments, regulated entities and other stakeholders to enforce anti-money laundering (AML) and counter financing terrorism (CFT) regulations.  (77 page PDF)

The intergovernmental organization aims to address emerging security and transparency issues as the process of financial transactions become more digital, according to the guidance.

On its website, FATF listed a number of questions acting as “areas of focus,” requesting private stakeholders to provide feedback via email by Nov. 29, 2019.

The areas include the specific risks digital ID might pose to AML/CFT enforcement; how it might support financial inclusion; how a system might aid in transaction monitoring; and the potential impact on implementing FATF’s record-keeping requirements.

Notably, the guidance specifically lists distributed ledger technology (DLT) as a tool that can aid in the growth of digital ID networks. A number of blockchain companies have already set their eyes on this particular area, such as Civic.   .... " 

Fraud Detection with AI

And even the predictive risk of the exposure to financial crimes.

How AI Can Help with the Detection of Financial Crimes
Paige Dickie develops artificial intelligence (AI) and digital strategy for Canada’s banking sector at the Vector Institute for Artificial Intelligence in Toronto. She began her career in management consulting — much to the disappointment of her father, an engineer — because she had earned advanced engineering degrees in biomedical and mechanical engineering. Dickie initially worked at McKinsey, the global consulting firm, helping multinational financial institutions across a range of fields from data strategy and digital transformation to setting up innovation centers. She recently joined Vector to lead what she describes as “an exciting project with Canada’s banking industry. It’s an industry-wide, sector-wide, country-wide initiative where we have three different work streams — a consortium work stream, a regulatory work stream, and a research-based work stream.”

Knowledge@Wharton interviewed Dickie at a recent conference on artificial intelligence and machine learning in the financial industry, organized in New York City by the SWIFT Institute in collaboration with Cornell’s SC Johnson College of Business.

According to Dickie, AI can have a significant impact in data-rich domains where prediction and pattern recognition play an important role. For instance, in areas such as risk assessment and fraud detection in the banking sector, AI can identify aberrations by analyzing past behaviors. But, of course, there are also concerns around issues such as fairness, interpretability, security and privacy.

An edited transcript of the conversation follows.  ... " 

JP Morgan's AI Initiatives

A Podcast and transcript. Useful case study. in Knowledge@Wharton 

Apoorv Saxena, global head of AI and machine-learning services for JPMorgan Chase, discusses the bank's AI initiatives.

When America’s biggest bank, JPMorgan Chase, hired Apoorv Saxena in August 2018 as its global head of AI and machine-learning services based in San Mateo, Calif., finance industry watchers saw that as a sign that the bank was making a big bet on artificial intelligence to shape its future strategies. Saxena previously headed product management for cloud-based artificial intelligence at Google. At JPMorgan Chase, he also oversees asset and wealth management artificial intelligence technology.

 According to Saxena, AI will help financial services companies expand banking penetration worldwide, launch new products and deepen customer engagements. AI has helped technology companies and others outside of traditional banking enter financial services, such as with mobile banking and digital money offerings. However, only firms that can earn customer trust, meet regulatory compliance requirements and enhance customer service will make the cut, he notes. Meanwhile, regulations will have to come up to speed with the impact of AI’s advances and help make way for the industry to grow. The U.S. could learn some useful lessons from other countries like China, as it seeks to promote innovation as well as growth at scale, he adds.

JPMorgan Chase is making a significant investment in AI research, Saxena notes. For now, he is focusing on building “a rock-star team” to lead AI initiatives at the bank, he says on social media. Knowledge@Wharton spoke with Saxena at the recently held AI Frontiers conference in San Jose.

An edited transcript of the conversation follows. ... "

Wharton, MIT and BC Aim to Disrupt Global Supply Chain

Another example of verification and validation applications of Blockchain infrastructure, here in supply chain.   Such applications are an ideal experimental first step.   Useful details at the link. 

How a New Technology Can Disrupt the Global Supply Chain
Operations Management  In Knowledge@Wharton

An interdisciplinary team from MIT, Wharton and Boston College has created a new blockchain-based system that has the potential to disrupt the global supply chain. Called ‘b_verify,’ the system is designed to help small and medium-size enterprises — especially those in developing nations — get financing from lenders at potentially better terms while mitigating warehouse deposit fraud. The system brings greater transparency to a key part of the supply chain, which can have a big impact on global trade financing. B_verify introduces a series of blockchain technology innovations tailored to facilitate supply chain finance and operations management.

“The potential benefits are vast and global in scale,” said Gerry Tsoukalas, Wharton professor of operations, information and decisions, who was part of the team. Small and medium-size enterprises, he said, represent the backbone of many economies in the world, and they account for more than half of the jobs as well as a third of global GDP. But despite their scope and impact, these companies have a harder time getting financing than larger established firms. He said the World Bank estimates their global financing shortfall to be $2.6 trillion.

Small and medium-sized firms also find it difficult to get financing on terms as favorable as the ones big companies get because they usually lack the latter’s track record and reputation. Banks typically would charge higher interest rates or put more restrictions on loans to smaller enterprises because they are less certain of repayment. Add to the mix the propensity for fraud, especially in the developing world, and smaller firms get the worse end of the proverbial stick. “Obtaining loans at reasonable rates can be very challenging for small firms,” Tsoukalas said.   .... "

Leveraging Social Determinants of Health

As I understand this,  the high ROI comes from decreasing unnecessary costs.   Which shows sometimes simple data analysis can provide value.  Just make sure to continue to measure these results.

What Montefiore's 300% ROI from social determinants investments means for the future of other hospitals ...   in Healthcarefinance  via Ryan Doherty of MidMark

By Susan Morse, Senior Editor

Montefiore Health System in the Bronx has tackled the social determinants of health by investing in housing, a move that has cut down on emergency room visits and unnecessary hospitalizations for an annual 300 percent return on investment.

"The lowest I've seen is 300 percent ROI, some years it's higher," said Henie Lustgarten, consultant and president of the Bronx Health & Housing Consortium, an organization Montefiore helped to develop.

Investing in the social determinants of health is becoming more commonplace even as hospitals and physicians ask whether it is their place to step outside of traditional care to not only look at, but try to fix, other reasons that keep patients from getting better.

Value-based care and managed care has spurred many to realize that food insecurity, isolation, lack of housing and other factors must be addressed in their populations for continuity of care to succeed as a real goal.

For many hospitals, buying food and investing in housing becomes less expensive than having a patient return to the emergency room numerous times a year. 

The big opportunity for any hospital 

America's Health Insurance Plans has shown that payers support social determinants issues. By collecting information from members about their social determinants and running that up against claims and other data, insurers can get a more complete picture of members' health, and opportunities for improvement, AHIP said in blog posted Monday.

Addressing social determinants has led to a 26 percent decrease in emergency spending, AHIP said, citing a recent U.S. News op-ed by Ken Burdick, CEO of WellCare Health Plans.

The WellCare findings saw an additional 10 percent reduction in healthcare costs – equating to more than $2,400 in annual savings per person – for people who were successfully connected to social services compared to a control group of members who were not.  ...  "

Virtualitics Announces Commercial Release

I had reported on this earlier.  We had experimented with immersing decision makers in data. See my tag links below for an image of our experiment. This is finally what looks to be a good commercial implementation of the idea.  Will look to experiment with it.  Now promoting the inclusion of AI/machine learning methods.  And also now desktop interaction?   Probably a good idea before the AR/VR  revolution takes off.  Also includes what they present as 'innovative maps' that work in 3D.

" .. We are excited to officially launch the commercial release of Virtualitics.

As part of this launch we are offering a free trial program. Simply click here and select the "Request a trial" on the form if you are interested in a trial.

While VR will enhance the visualization of high-dimensional data and provide a real-time collaborative place for your team, it is not necessary. Virtualitics is cross-platform and offers all of the sophisticated AI routines and rich 3D visualizations in desktop as well.

Also please see below a link to a video of our CEO Michael presenting Virtualitics at the Fintech Innovation Lab in NY, with an introduction by Blackrock:
https://www.youtube.com/watch?v=4tM0oWm8jZA&feature=youtu.be

Feel feel to contact me directly with any questions.

Paul Gearhart, Head of Customer Solutions
Virtualitics ... "

Measure of Risk

Reminds me when we had roomfuls of economists.  Not recently.  Seems its always done elsewhere these days and its hard to get numbers for ROI or acceptable risks calculations.

A Measure of Risk Appetite for the Macroeconomy
by Carolin E. Pflueger, Emil Siriwardane, and Adi Sunderam

OVERVIEW — This paper sheds new light on connections between financial markets and the macroeconomy. It shows that investors’ appetite for risk—revealed by common movements in the pricing of volatile securities—helps determine economic outcomes and real interest rates. ...  "

Social Networks and Innovations

An interesting view of how social networks influence elements of opinion.   In particular addressing the kinds of innovations.

How Social Networks Contribute to the Spread of Unproven Innovations

Wharton's Valentina Assenova discusses her research on social networks and the adoption of complex innovations.

There are some new products and services that are very obviously good  — a cure for a deadly disease, for example, or some other type of medical innovation. But other innovations have value that is more uncertain, such as an unproven technology. In her latest research paper, Wharton management professor Valentina Assenova examines the role of social networks, both online and offline, in the spread of these complex innovations. Her paper is titled, “Modeling the Diffusion of Complex Innovations as a Process of Opinion Formation Through Social Networks.” She joined Knowledge@Wharton to discuss her findings about which kinds of innovations spread more quickly than others in different networks, the role of influencers, and what that means for entrepreneurs.

An edited transcript of the conversation follows.

Knowledge@Wharton: What was the inspiration for this research?

Valentina Assenova: The inspiration for this research was looking at the spread of microfinance. Microfinance is one of those innovations that is not obviously good or bad, and there is a lot of mixed evidence around whether or not it is actually beneficial for women, whether it improves welfare and so forth. But it was something that really got me intrigued about the role of public opinions and of social networks — in the sense of people who you talk to for advice, for help in making a decision — and how some of these complex innovations spread.    ... " 

Alexa Assistants come to the Trading Floor

Another example where hands-free can be very useful, and you need information quickly.   Adding an information channel.

JPMorgan Brings Amazon’s Alexa to Wall Street Trading Floors
By Hugh Son and Katherine Chiglinsky  in Bloomberg Tech

Voice-activated assistant can now send reports from analysts

Other firms such as New York Life using it to help employees
“Alexa, ask JPMorgan what the price target for Apple is.”

It’s a request that JPMorgan Chase & Co. institutional clients can now get quickly answered through Amazon.com Inc.’s ubiquitous voice-activated assistant. The bank and the e-commerce giant have partnered to provide JPMorgan’s Wall Street users with another way to access its research. Alexa is able to send analysts’ reports and related queries, and the bank is testing other features, like providing prices on bonds or swaps, according to David Hudson, global head of markets execution for the New York-based bank.

Voice assistants are “clearly becoming something people are habituated to in their lives,” Hudson said. “It’s about taking information that’s somewhere in the bank, that someone has to generally go and look for, or which is time-consuming or requires authentication to get, and putting that to you in another channel.”  .... " 

Trading with Reinforcement Learning

Nice example of reinforcement learning.  Not really prediction of the kind might want, below just the introduction that sets the stage, click through to more detail that makes the case for usefulness of the method.   Also make the case of why financial prediction is difficult.   Application to crypto currency is interesting because of its general inscrutable nature.  See also paper on RL with Sparse rewards: https://arxiv.org/abs/1709.10089 

Introduction to Learning to Trade with Reinforcement Learning  By Denny Britz, in WildML

Thanks a lot to @aerinykim, @suzatweet and @hardmaru for the useful feedback!

The academic Deep Learning research community has largely stayed away from the financial markets. Maybe that’s because the finance industry has a bad reputation, the problem doesn’t seem interesting from a research perspective, or because data is difficult and expensive to obtain.

In this post, I’m going to argue that training Reinforcement Learning agents to trade in the financial (and cryptocurrency) markets can be an extremely interesting research problem. I believe that it has not received enough attention from the research community but has the potential to push the state-of-the art of many related fields. It is quite similar to training agents for multiplayer games such as DotA, and many of the same research problems carry over. Knowing virtually nothing about trading, I have spent the past few months working on a project in this field.

This is not a “price prediction using Deep Learning” post. So, if you’re looking for example code and models you may be disappointed. Instead, I want to talk on a more high level about why learning to trade using Machine Learning is difficult, what some of the challenges are, and where I think Reinforcement Learning fits in. If there’s enough interest in this area I may follow up with another post that includes concrete examples.

I expect most readers to have no background in trading, just like I didn’t, so I will start out with covering some of the basics. I’m by no means an expert, so please let me know in the comments so if you find mistakes. I will use cryptocurrencies as a running example in this post, but the same concepts apply to most of the financial markets. The reason to use cryptocurrencies is that data is free, public, and easily accessible. Anyone can sign up to trade. The barriers to trading in the financial markets are a little higher, and data can be expensive. And well, there’s more hype so it’s more fun :)  .... " 

Conversational Banking Assistant Pilot

Intriguing statement of how this is operating, and how it can deal with a messy conversational interaction.   Because of the nature of the interaction, this would appear to be particularly important and difficult to assure correctness.   How exactly is this beyond rules or a chatbot interaction?   Sentiment also included.  Learning too.    More detail at the link.  ...

USAA Rolls Out Innovative Conversational AI Solution
Going beyond traditional rules-based voice or chatbot digital banking solutions, a non-bot, natural language banking experience is being offered to USAA members in an Amazon Alexa pilot with Clinc.    By Jim Marous, Co-Publisher of The Financial Brand and Owner/Publisher of the Digital Banking Report

Subscribe TodayLast September, a team of computer science professors at the University of Michigan introduced an application developed in their research lab that they believed would change the way consumers would do banking in the future. Combining the science and technology from academia, with the needs for a better voice-first mobile banking capability, Clinc won ‘Best of Show’ honors at Finovate in New York City with their Finie (“the financial genie”) application.

The intelligent personal assistant uses sophisticated natural language processing engines that have been trained with a deeper knowledge of the financial and banking industry as opposed to using a rules-based approach. Unlike solutions that currently exist from Siri, Alexa and Cortana, Clinc’s machine learning capability allows the application to expand knowledge and improve responses with every query. By identifying and analyzing dozens of factors like speech patterns, word structure and sentiment, Clinc is able to understand, to remember and to respond to unconstrained, contextual, messy human language.  ... "