Mining Financial Data Without Actually Seeing It Can Detect Fraud

Quite interesting.  

 Mining Financial Data Without Actually Seeing It Can Detect Fraud  By Arnout Jaspers, Commissioned by CACM Staff, September 9, 2021

Large-scale data sharing is a potential goldmine for research, health, and security, but until recently this goldmine was largely inaccessible, due to privacy considerations. Now, banks are starting to use secure Multiparty Computation (MPC) to detect potentially fraudulent transactions while protecting the privacy of their customers.

MPC distributes computations on data between several parties in such a way that none of the parties can see the raw data, but the desired result can still be computed. Software to achieve this has been developed over the past years. A similar concept is homomorphic encryption, which guarantees that certain classes of computations performed on encrypted data give the same result as computations on the raw data.          

TNO, the Netherlands organization for applied scientific research, is working closely with two large Dutch banks, ABNAmro and Rabobank, on a pilot project to detect suspicious financial transactions using MPC and an algorithm inspired by Google's page-rank algorithm. The basic idea is that networks of financial transactions can be analyzed in similar fashion to how a search engine determines the importance, or rank, of a website. A website is 'important' if other 'important' websites link to it; although this is a self-referential definition, the page-rank algorithm can, after a number of iterations, produce a consistent ranking of websites. 

In this case, bank accounts are the nodes in the network, and two accounts are linked if a money transfer between them has taken place. Other than in the Internet page ranking, a link can have a weight, depending on how often and how much money was transferred. An account gets a high risk score, for instance for money laundering, if another high-risk account transferred money to it.

Each bank can create such a 'risk propagation network' for the accounts of its own clients because it has their financial transaction data, but many transactions happen between different banks. Risk scoring would improve significantly if the algorithm could add those external accounts to the network, but banks are hesitant to share these data because of their potential impact on privacy. Said Tjebbe Tauber, business developer for innovation and design at ABN AMRO's Detect Financial Crime unit, "We are carefully looking at what is, and what is not possible under the European privacy law."  .... ' 

Quantum Computing Catching up for Market Analysis

 Quite an interesting prediction.  Will there be a post-quantum market analysis era?   I can see some of the combinatorics coming in, but the accuracy of results are not yet there.  

Goldman Sachs Predicts Quantum Computing is 5 Years Away from Use in Markets  By Financial Times

Quantum computing could be brought to bear on some of the most complex calculations in financial markets within five years, considerably earlier than expected, according to research jointly conducted by Goldman Sachs.

The findings come as banks and other companies at the leading edge of quantum research have turned their attention to trying to get practical results using the imperfect quantum computers that are expected to be in use in the next few years, rather than wait for the much more powerful systems that are one day expected to bring a revolution in computing.

The bank's research, conducted with quantum start-up QC Ware, suggests that programmers looking to harness the machines could achieve practical results sooner in return for giving up some of the huge gains in performance that quantum systems promise.

From Financial Times

Wharton: Planning for AI Risk Governance

Useful thoughts on the concept of governance of AI in the paper linked to below.

How Can Financial Institutions Prepare for AI Risks?

Apr 13, 2021 Analytics Wharton Research North America

Artificial intelligence (AI) technologies hold big promise for the financial services industry, but they also bring risks that must be addressed with the right governance approaches, according to a white paper  by a group of academics and executives from the financial services and technology industries, published by Wharton AI for Business. 

Wharton is the academic partner of the group, which calls itself Artificial Intelligence/Machine Learning Risk & Security, or AIRS. Based in New York City, the AIRS working group was formed in 2019, and includes about 40 academics and industry practitioners. ..." 

Modifying the Way Companies Talk

Because machines are analyzing the patterns in what is said.   And of course, machines will soon also generate some of the conversation.

How machines are changing the way companies talk   By Khari Johnson @kharijohnson  in VentureBeat

Anyone who’s ever been on an earnings call knows company executives already tend to look at the world through rose-colored glasses, but a new study by economics and machine learning researchers says that’s getting worse, thanks to machine learning. The analysis found that companies are adapting their language in forecasts, SEC regulatory filings, and earnings calls due to the proliferation of AI used to analyze and derive signals from the words they use. In other words: Businesses are beginning to change the way they talk because they know machines are listening.

Forms of natural language processing are used to parse and process text in the financial documents companies are required to submit to the SEC. Machine learning tools are then able to do things like summarize text or determine whether language used is positive, neutral, or negative. Signals these tools provide are used to inform the decisions advisors, analysts, and investors make. Machine downloads are associated with faster trading after an SEC filing is posted.

This trend has implications for the financial industry and economy, as more companies shift their language in an attempt to influence machine learning reports. A paper detailing the analysis,    originally published in October by researchers from Columbia University and Georgia State University’s J. Mack Robinson College of Business, was highlighted in this month’s National Bureau of Economic Research (NBER) digest. Lead author Sean Cao studies how deep learning can be applied to corporate accounting and disclosure data.

“More and more companies realize that the target audience of their mandatory and voluntary disclosures no longer consists of just human analysts and investors. A substantial amount of buying and selling of shares [is] triggered by recommendations made by robots and algorithms which process information with machine learning tools and natural language processing kits,” the paper reads. “Anecdotal evidence suggests that executives have become aware that their speech patterns and emotions, evaluated by human or software, impact their assessment by investors and analysts.”

The researchers examined nearly 360,000 SEC filings between 2003 and 2016. Over that time period, regulatory filing downloads from the SEC’s Electronic Data Gathering, Analysis, and Retrieval (EDGAR) tool increased from roughly 360,000 filing downloads to 165 million, climbing from 39% of all downloads in 2003 to 78% in 2016.

A 2011 study concluded that the majority of words identified as negative by a Harvard dictionary aren’t actually considered negative in a financial context. That study also included lists of negative words used in 10-K filings. After the release of that list, researchers found high machine download companies began to change their behavior and use fewer negative words. ... ' 

McKinsey Talks AI Banks of the Future

The challenge is in how our behavior will adapt.  My recent banking interactions are less than pleasing.  Good non-technical overview piece.

AI-bank of the future: Can banks meet the AI challenge?

AI in banking may be the next big differentiator. Success requires a holistic transformation spanning multiple layers of the organization.  ... " 

Simulating the Market

Quite a claim, often mentioned in early AI 'tests'?  Can it work?   Is simulation sufficiently complex proxy for the market?

AI stock trading experiment beats market in simulation  by Chinese Association of Automation in TechExplore

Researchers in Italy have melded the emerging science of convolutional neural networks (CNNs) with deep learning—a discipline within artificial intelligence—to achieve a system of market forecasting with the potential for greater gains and fewer losses than previous attempts to use AI methods to manage stock portfolios. The team, led by Prof. Silvio Barra at the University of Cagliari, published their findings on IEEE/CAA Journal of Automatica Sinica.

The University of Cagliari-based team set out to create an AI-managed "buy and hold" (B&H) strategy—a system of deciding whether to take one of three possible actions—a long action (buying a stock and selling it before the market closes), a short action (selling a stock, then buying it back before the market closes), and a hold (deciding not to invest in a stock that day). At the heart of their proposed system is an automated cycle of analyzing layered images generated from current and past market data. Older B&H systems based their decisions on machine learning, a discipline that leans heavily on predictions based on past performance.....  "

More information: Silvio Barra, Salvatore Mario Carta, Andrea Corriga, Alessandro Sebastian Podda and Diego Reforgiato Recupero, "Deep Learning and Time Series-to-Image Encoding for Financial Forecasting," IEEE/CAA J. Autom. Sinica, vol. 7, no. 3, pp. 683-692, May 2020. www.ieee-jas.org/en/article/do … 109/JAS.2020.1003132

Honeywell Introduces a Quantum Computer

Somewhat unexpected, but the announced major client makes it seem serious.  Trading strategies are a kind of process and decision making approach that will be good to follow to see ow Quantum will help.

Honeywell to Roll Out Quantum Computer
The Wall Street Journal
Sara Castellanos
March 3, 2020

Honeywell will introduce an early-stage quantum computer for commercial experiments within about three months, with JPMorgan Chase as the first public user. The new machine is expected to be the world's most powerful quantum computer, based on its expected quantum volume (a measure of the performance of a quantum system) of at least 64. Honeywell’s Tony Uttley anticipates the technology will be used by organizations interested in developing new materials or new trading strategies for financial services, or by those looking to speed up calculations. Marco Pistoia of JPMorgan Chase said he expects to use quantum computing to speed up computing-intensive calculations, including Monte Carlo simulations, which are commonly used to calculate the theoretical value of an option. Quantum computing could also be used in portfolio optimization.  ... "   .... '

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.  .... " 

Behavioral Economics Driven by Digital Design

All design drives behavior, but how well does it do in achieving goals?  Financial domain an obvious space where there are numbers and needs.

How Digital Design Drives User Behavior
Shlomo Benartzi, Saurabh Bhargava in the HBR

Decisions of all kinds are increasingly made on screens — and with that shift comes an often-ignored consequence: the design of the digital world can profoundly, and often unnoticeably, influence the quality of our decisions.

A review of recent research provides clear evidence that many organizations are currently undervaluing the power of digital design and should invest more in behaviorally informed designs to help people make better choices. In many cases, even minor fixes can have a major impact, offering a return on investment that’s several times larger than the conventional use of financial incentives or marketing and education campaigns.

In our recent working paper, written with Lynn Conell-Price at the University of Pennsylvania, and Richard Mason at City, University of London, we collaborated with Voya Financial, a leading retirement service provider, to investigate how variation in the digital design of online enrollment interfaces could influence the initial contribution decisions of employees in 401(k) plans. The research involved more than 8,500 employees across a few hundred plans, who prior to being automatically enrolled in the plan, had visited a standardized online enrollment interface to either actively confirm their enrollment at the default rate, personalize their enrollment at a different rate, or decline enrollment altogether by selecting one of three horizontally arranged options. Our goal was to get employees to consider a deferral rate higher than the default, which is often too low to achieve financial security in retirement.  ... "

Blockchain Impact on Securities

Worth following.

Understanding Blockchain Technology’s Impact on the Securities Markets

A team of legal and business researchers from Columbia has been awarded a grant to study how blockchain technology is affecting the security markets.

The grant, from the Columbia-IBM Center for Blockchain and Data Transparency, will allow the researchers to design and conduct a survey of securities-market stakeholders such as regulators, academics, policymakers, securities employees and journalists. The survey will allow for a deeper understanding of how blockchain technologies and digital ledgers are likely to affect the markets and how their potential should shape future regulation.  Once the survey is done, the researchers will outline their findings in a white paper and present their results in a conference at Columbia. The researchers are affiliated with The Program in the Law and Economics of Capital Markets, a joint program of Columbia Law School and Columbia Business School.

Merritt B. Fox, Michael E. Patterson Professor of Law at Columbia Law School who is leading the legal aspects of the project, said there is a vast amount of potential in blockchain but also many pitfalls. Each of the various stakeholders to be interviewed for the survey has a unique perspective on these issues and it’s important to learn the learn these perspectives in order to design regulation that best advances the interests of society.

“The area is bursting with innovation and experimentation and we look forward to learning more about these,” said Fox. “Facilitating clearing and settlement, reducing the role of intermediaries, increasing global access to data, and furthering empirically-driven policymaking are just a few examples of areas we’ll look at.”

Juliette Fisbein, Director of Strategy and Operations for the Columbia University-IBM Center for Blockchain and Data Transparency, said the center awards grants to cutting-edge research in the area of blockchain and data transparency technologies, with this project being a good example of such research. Formed in the summer of 2018, the center is devoted to research, education, and innovation in blockchain technology and data transparency. The Data Science Instituteand Columbia Engineering are partnering with the center, which also works in tandem with Columbia’s Business School, the Law School, the School of International and Public Affairs as well as Columbia Technology Ventures.

“The center is pleased to fund multidisciplinary research allowing to combine the complementary perspectives of lawyers and economists,” Fisbein said, “and will continue to seek multidimensional expertise to study blockchain technology and its potential throughout 2020 and beyond. Additional calls for research grant proposals will be announced this fall.”

In this Q&A, Fox discusses how the researchers will seek to gain a broader understanding of the role that blockchain technology may play in the securities markets. .... 

China Ready to Launch Its Digital Renminbi

World wide implications?

Technology Review:   Chain Letter: MIT Technology Review
Blockchains, cryptocurrencies, and why they matter

12.12.19
Chain Letter from MIT Technology Review
#174: The next steps in China’s digital currency road map have been revealed

China may be just about to launch its digital renminbi in two cities. The People’s Bank of China is planning a real-world pilot of its digital currency, the first phase of which could begin before the end of this year, according to a report from an influential Chinese financial news publication. That would support recent speculation that China is on the verge of becoming the first major economy to issue sovereign digital money.

In August, an official from the PBOC said the currency, which China has been developing for several years, was “close” to being issued. The new report, from the financial news outlet Caijing, outlines specific next steps. It says the PBOC could launch a small-scale experiment in Shenzhen before the end of the year and then scale it up in 2020. In addition to Shenzhen, the pilot will take place in the eastern city of Suzhou, according to Caijing. If the tests go well, presumably the currency will go live soon afterward.

The Caijing report seems to confirm several details about the forthcoming currency system, called digital currency electronic payment (DCEP), that have appeared in news reports during the past several months. For instance, it confirms that the PBOC will partner with commercial banks to issue the currency, and that during the initial phase the banks will compete on how best to implement it. It says tests will likely include seven state-owned firms: the four largest commercial banks and three big telecom companies. According to the news report, the tests will involve real-world service scenarios in the areas of transportation, education, and medical treatment.  .... "   Full report. 

Wal-Mart, Facebook and Digital Tokens for Inclusion

Fascinating piece on the notion of 'Financial Inclusion' and its use by retailers of both products and of marketing data,  like Wal-Mart and Facebook.    Meaning of this discussed in the Gartner Blog.  Does this mean that companies like these are attempting to construct their own monetary systems to improve this inclusion?  How will this be regulated?   Implications?

Libra and Walmart “Blockchain” Tokens: Financial or Walled Garden Inclusion?   by cuzureau    Gartner Blog

Facebook has announced the development of a digital currency, Libra (cf. “Facebook Libra — Liberator or Trojan Horse”1 ) and Walmart has filed a patent application for a digital token (cf. patent application2). Both initiatives rely on blockchain technology. The two companies have multiple rationales for launching or planning such initiatives. In this blog post, we explore their claims toward financial inclusion.

Facebook has stressed in the Libra white papers its objective of improving financial inclusion globally. And Walmart’s patent application’s introduction, stresses that: “The cost of having little money is high because of frequent short-term borrowing, accumulated interest on short-term borrowing that becomes long-term, high bank fees proportional to wealth, high credit card fees, and high payday loan interests…. Providing digital currency based on blockchain may overcome the drawbacks associated with the low-income households”

Having more companies try to address financial inclusion is positive and across all markets. Mature banking markets such the US also have to deal with a financial services access gap. The FDIC National Survey of unbanked and underbanked Households (cf.  https://www.fdic.gov/householdsurvey/) estimates that in 2017 there were 8.4m unbanked (no account at an insured institution) households and 24.2m underbanked (checking or savings account only with insured institution), in the USA.   ... " 

DAML: Contract Language of Distributed Ledgers

Quite an interesting piece on contract languages and 'Smart Contracts".  A recent proposal made me look deeper into this idea, especially as it might connect to supply chain and procurement efficiencies.  Considerable 7-page piece, admittedly technical here, but worth taking a close look.  And of  course this gets to workflow, always a particular angle of interest of mine.  Below just a few excerpts.

Case Study
DAML: The Contract Language of Distributed Ledgers
A discussion between Shaul Kfir and Camille Fournier

When Shaul Kfir cofounded Digital Asset in 2014, he was out to prove something to the financial services industry. He saw it as being not only hamstrung by an inefficient system for transaction reconciliation, but also in danger of missing out on what blockchain technology could do to address its shortcomings.

Since then, Digital Asset has gone to market with its own distributed-ledger technology, DAML (Digital Asset Modeling Language). And that does indeed take advantage of blockchain—only not in quite the way Kfir had initially intended. He and Digital Asset ended up taking an engineering "journey" to get to where they are today.

Kfir readily admits his own background in cryptography and cryptocurrency—both as a researcher (at Technion and MIT) and as a cryptocurrency entrepreneur in Israel—had more than just a little to do with the course that was originally charted. As for lessons learned along the way, Camille Fournier, the head of platform development for a leading New York City hedge fund, helps to elicit those here. She brings to the exercise her own background in distributed-systems consensus (as one of the original committers to the Apache Zookeeper Project) and financial services (as a former VP of technology at Goldman Sachs).  ....  "

" .... To clarify, think about how large technology companies use their infrastructure to achieve greater agility. Most of them today have some logically centralized infrastructure that includes a central code repository and a CI/CD [continuous integration/continuous delivery] system. If these ideas can be expanded to an industry level in the sense that you can start rolling out workflows as smart contracts that are written only once and then made available for everyone to build upon, that's clearly more efficient than leaving it to each organization to write its own workflows. ... " 

Dark Side of AI in Healthcare

This example requires making deceptive prediction based on goals.  Expressing goals and being transparent about them is good,  but can be problematic in context for any kind of analytic method.

 Warnings of a Dark Side to AI in Health Care 
The New York Times
By Cade Metz; Craig S. Smith

Harvard University and Massachusetts Institute of Technology (MIT) researchers warn in a recently published study that new artificial intelligence (AI) technology designed to enhance healthcare is vulnerable to misuse, with "adversarial attacks" that can deceive the system into making misdiagnoses being one example. A more likely scenario is of doctors, hospitals, and other organizations manipulating the AI in billing or insurance software in an attempt to maximize revenue. The researchers said software developers and regulators must consider such possibilities as they build and evaluate AI technologies in the years to come. MIT's Samuel Finlayson said, "The inherent ambiguity in medical information, coupled with often-competing financial incentives, allows for high-stakes decisions to swing on very subtle bits of information." Changes doctors make to medical scans or other patient data in an effort to satisfy the AI used by insurance firms also could wind up in a patient's permanent record.  .... "

Rise of the Financial Robo Advisor

Much interested in the dynamics of how systems will dynamically and perceptively give advice.   In this blog have called them 'Assistants'.    How will they disrupt in giving financial advice?

The Rise of the Robo-advisor: How Fintech Is Disrupting Retirement  In Knowledge@Wharton

Artificial intelligence is changing the world of retirement planning. By using improved datasets and algorithms to efficiently deliver solutions tailored to people’s needs, AI can help them save, invest and retire better. One of the hottest trends to emerge in this area in recent years is the use of robo-advisors. These are software programs that use the data supplied by clients to create and automatically manage their investment portfolios. They’re gaining in popularity, but are they better than human advisors?

“Robo-advisors are a potential solution to the complexities of financial decision-making,” particularly in retirement planning, said Jill E. Fisch, law professor at the University of Pennsylvania. “But at the same time, there’s a lot we don’t know about robo-advisors — exactly how they work and how effective a solution they’re going to be.” She and other experts from Wharton and elsewhere spoke at a conference hosted by the Pension Research Council titled “The Disruptive Impact of FinTech on Retirement Systems.”   ... "