New York Tech Journal
Tech news from the Big Apple

Investing using #DeepLearning, #MacroTrading and #Chatbots

Posted on June 2nd, 2017


Qplum, 185 Hudson Street , Jersey City, suite 1620

Mansi Singhal and Gaurav Chakravorty @Qplum  gave two presentations on how Qplum uses machine learning within a systematic macro investment strategy. Mansi talked about how a macro economic world view is used to focus the ML team on target markets. She walked the audience through an economic analysis of the factors driving the U.S. residential housing market and how an understanding of the drivers (interest rates, GDP, demographics,…) and anticipation of future economic trends (e.g. higher interest rates) would lead them to focus on (or not consider) that market for further analysis by the ML group.

Gaurav ( talked about how they use an AutoEncoder to better understand the factors driving a statistical arbitrage strategy. Here, instead of using a method like principal components analysis, they use a deep learning algorithm to determine the factors driving the prices of a group of stocks. The model uses a relatively shallow neural net. To understand the underlying factors, they look at which factors are the largest driver of current market moves and determine the historical time periods when this factor has been active. One distinction between their factor models and classic CAPM models is that non-linearities are introduced by the activation functions within each layer of the neural net.

Next, Aziz Lookman talked about his analysis showing that an analysis of county-by-county unemployment rates affects the default rates (and therefore the investment returns) on loans within Lending Club.

Lastly, Hardik Patel @Qplum talked about the opportunities and challenges of creating a financial chatbot. The opportunity is that the investment goals and concerns are unique for each customer, so each will have different questions and need different types of information and advice.

The wide variety of questions and answers challenges the developer so their approach has been to develop and LSTM model of the questions which will point the bot to a template that will generate the answer. Their initial input will use word vectors and bag of words methods to map questions to categories.

posted in:  data analysis, Data science, finance    / leave comments:   No comments yet

#ExtremeEvents and short term reversals in #RiskAversion

Posted on April 17th, 2017


04/17/2017 @ 101 NJ Hall, 75 Hamilton Street, New Brunswick, NJ

Kim Oosterlinck @FreeUniversityOfBrussels presented work done by Matthieu Gilson, Kim Oosterlinck, Andrey Ukhov. Kim started by reviewing the literature that shows no consensus on whether risk aversion increases or decreases in following extreme events such as war. In addition, these studies often have only two points on which to make this evaluation.

He presented a method for tracking overall risk aversion within a population on a daily basis for several years. His analysis values the lottery part of Belgian bonds which consisted of a fixed coupon bond with the opportunity to win a cash prize every month. These bonds were sold to retail customers and made up 11% of Belgian bond market in 1938. By discounting the cash flows based on the yields for other, fixed coupon Belgian bonds, one can compare the risk neutral price (RNP) relative to the market price (MP).

When MP/RNP > 1 this indicates the average holder is risk loving.

There are three  periods in their observations from 1938 to 1948.

  1. Risk neutral to risk averse from 1938 to 1940, when German invaded and occupied Belgian
  2. Risk aversion to risk seeking from 1940 to 1945 during the German occupation
  3. Risk seeking to risk neutral from 1945 to 1948.

Lots of competing theories on when people become more or less risk averse

These data give the strongest support is habituation to background risk as the best explanation of the increase in risk aversion. Prospect theory also does well as an explanation.

[The findings of increased risk seeking form 1940 to 1945 could also be consistent with a flat yield curve at 3% from 1month to 3 years in 1940 to a steep yield curve in 1945 going from 0% at 1 month to 3% at 3 years. ]

posted in:  finance    / leave comments:   No comments yet

Mobile Moolah: a panel on #Cashless #transactions

Posted on March 8th, 2017


03/08/2017 @Rise, 43 West 23rd Street, NY, 2nd floor

Kate Christensen, @Barclays, moderator

Norm Merritt is a global CEO @ShopKeep

David True is the General Manager of US operations at @Seqr Payments – QR code payments on phones

Karl Kilb, CEO of @Boloro Global – multifactor identification using USSD network

Hassan Ahmed manages Business Operations at @Venmo – mobile payments

The panel discussion started and ended with a discussion about the future of point of sale payments as the future of mobile payments. Currently, mobile POS is already disrupting retail as there is not central checkout point in Apple stores and an Amazon store in Seattle allows customers to just walk out as they are billed automatically.

E-commerce transactions have a greater chance of fraud so there is an extra 30 basis points charged over in-store transactions. Ways to reduce fraud include phone biometrics, a separate digital id verification (Boloro) and text verification on your phone.

The future of in-store sales indicates that many traditional fixed console POS devices are becoming obsolete, but there was disagreement of the speed of this transformation especially for supermarkets and other low-margin, high capital costs stores. There is also the resistance of some retailers such as Walmart and Target to allowing NFC, contact-less transactions as this could compromise their ownership of the SKU, item-by-item purchase data.

Unfortunately, the panel did not get into the long term implications of regulations for these non-bank payment agents. As these services become larger and accept balances (such as is currently done by Paypal), they will come under increased scrutiny under the banking laws. These include deposit insurance, know your customer, anti-money laundering, and anti-discrimination laws. All of these will require additional costs and changes in privacy rules to tighten information available to consumers but allow greater access by regulators and law-enforcement agencies.


posted in:  finance, Mobile Payments NYC    / leave comments:   No comments yet

DesignDrivenNYC: growing the design group and design function in organizations

Posted on May 11th, 2016


05/10/2016 @WeWork, 115 West 18th Street, 2nd floor, NY

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Three speakers spoke about their methods to integrate #design processes into all parts of product #development within retail-facing #financial firms. Betterment is a small, but rapidly growing company that is upsizing the design team. Citi and Learnvest are moving from a haphazard view of design to a single customer-centric design process throughout the organization:

In the first presentation, Jamie Strollo @Betterment spoke about the challenges the UI/UX design team faces as the company goes from a small startup to 9 designers to doubling by year end. Originally Betterment had a flat organization, but now there are challenges: integration of new people and avoiding the bad dynamics of large meetings. Design is the only shared resource across the company, so there was duplication in work. Some strategies for tackling a new design challenge are:

  1. Kick off strong – ask what is the problem?, what is success?, how do we measure?, constraints? Initially concentrate on measuring the drop-off rate when evaluating a design change. But eventually shift to measuring the effect on profitability.
  2. Assumption gathering – for stakeholders, high-level activity, focus on fears and confidence, agree of riskiest assumptions, talk to customers to validate.
  3. Focus on Top 5’s
    1. Great for large groups, Iterations
    2. High-level activity
    3. Select only top 5 design needs
    4. Helps to Establish patterns
    5. Bridge the “delete” conversation
  4. Ideation / paper prototyping – better for smaller groups. Bring in other areas of expertise, let others have a voice
  5. Managing feedback – decide who are the decision makers, who to inform. No big UI critiques (a polished presentation gives a finished feeling and makes it hard to change), share often and early, speak about objectives and key results. Start conversation by what is the objective.
  6. Invest in relationships – customers and coworkers

Another challenge as the company grows is creating a method to give better estimates of the time to complete a design. This is hard since much of time goes into understanding the problem

In the second presentation, Billy Seabrook @Citi spoke about how Citi has created a single world-wide design team. The goal of better design is to move customer’s view of the bank from a transactional experience to a relational experience.

Starting six months ago, Billy has approached the following challenges within the bank:

  1. Organization – create agile groups adding individuals looking at strategies; research and usability studies; producers to keep on time and budget.
  2. Skills – Create a cohort of coaches to teach design thinking throughout the bank. Minimal viable product is at the intersection of business viability + customer desirability + technical feasibility; Partner with IDO to foster agile design thinking throughout all parts of the bank
  3. Applied Projects – Citi Fintech launched 6 months ago to launch the bank of the future: focus on mobile (mobile only), speed and simplicity (2 weeks of design thinking + 2 week dev sprints)

To foster common branding and look-and-feel world-wide, document templates are shared world-wide. Senior people in each location are in constant contact.

Coaches have backgrounds of policy or planning. The main thing is the mind set of being customer centric.  In the past, most of the product design was outsourced, so design principals were inconsistent also there was a lack of consistency in evaluating designs.

The Design group reports to the COO of Fintech and is considered a cost center (despite its’ close affiliation with profit centers).

In the final presentation, Abigail Hart Gray @Learnvest (help financial planners create simple, effective, .., plans for retirement…) talked about the challenges of integrating a unified design process into product development at Northwestern Mutual (acquired Learnvest last year).

Abigail started with the question of a Defining Design Driven? She interviewed experienced design professionals and found commonalities:

  1. Team structure – be at the table when decision are made
  2. Process – iterative process
  3. Outcomes – but interviewees disagreed up whether good design resulted in products that were best for customer or best for business.

She talked about becoming a champion of design within the company:

  1. know the capabilities
  2. need to invest in design
  3. designers must educate their audience and sell their vision.

If you need to explain the interface, it stinks!

Steps to get started (data-driven, customer centric, outputs oriented):

  1. pick something with low stakes – no bottom line implications
  2. research well
  3. measure everything
  4. share results
  5. repeat

As an aside on the measurement process, one needs to consider the possibility that customer behavior changes by knowing that they are being observed. The Hawthorne effect can elevate or suppress responses depending on prior customer engagement (friends&family vs. the general population), frequency of engagement (daily vs. occasional), etc.

posted in:  applications, DesignDrivenNYC, finance, UI, UX    / leave comments:   No comments yet

#DigitalPayments and #Fintech

Posted on September 29th, 2015

09/29/2015 @ Barclays, 101 Barclay St., NY

A panel of experts and a series of presentations covered the topics of digital payments and fintech initiatives on a wide range of topics including consumer verification to currency exchange.


The panel covered many topics including

  1. Payments are made in two steps: 1. Account # verification 2. Account owner verification. The use of biometrics and EMV-chip credit cards is changing this landscape.
  2. Fintech often piggy backs on the current bank infrastructure
  3. It is challenging to groom the IT talent pool as the speed of innovation has quickened
  4. Distributed ledger is an opportunity to speed payments and move information quicker
  5. There is a need to build governance and rules on top of the technology such as block chain
  6. Customer desires may be contradictory: immediate payment vs. revocability, ease of use vs. fraud is hard
  7. The bank relationship with customers may change with the proliferation of payment services.
  8. There is a sense that banks are moving from model in which banks owned the technology to one in which the bank manages the technology – agnostic as to the technology. Focus on business serving the client.

After the panel, there were six 5 minute presentations by Irish companies exploiting technology in finance:

Fexco transaction services – Denis McCarthy – started doing FX transactions in County Kerry,Ireland. Now global retail payments.  Challenges 1. Legacy platforms.2. cross-border processing 3. Alternative payments 4. Omni-channel experience (in store, online). sell a white label solution.

Sysnet Global Solutions – Safemaker product to simplify security & compliance. 85% of breaches are stolen credit card information. Most are small businesses. Create a customized program for small businesses to secure their network – maintain compliance.

Trustev – Rurik Bradbury – stop online fraud. Can flag in real-time. Cloud data base –how they behave when come to web site. Are they trying to mask their location, is it a spam bot, look at credit file, social, known email address, …

Continuum Commerce – online customer needs an issuing bank and the retailer needs an acquiring bank. If there is a cross currency transaction the retail bank will apply a 3% fee for FX. Continuum allows the customer to have the option to pay in their native currency as opposed to the default currency of the retailer at a lower fee.

Acquirer Systems –help customers protect their brand value. Automated test and validation services so the retailer can accept a card with confidence. E.g. help retailers in the U.S. update their systems so they can accept EMV (chip-based) systems.

Daon – Conor White – make it easy for consumers to pay and interact online by authenticating humans using a mobile biometrics. Using face, voice recognition. Device is encrypted and by taking a selfie (person needs to blink so the system knows that it is not a picture.) For a demo go to  to get a link for you to try the system.

posted in:  applications, Big data, data analysis, databases, finance, security    / leave comments:   No comments yet

Patterns and Best Practices for Building #Low-Latency #Trading Applications

Posted on August 18th, 2015

NYC Java

08/17/2015 @Barclays Capital, 745 7th Ave, NY

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Buko Obele, software architect @Neeve Research, spoke about how to build low latency trading systems in #Java.

Buko introduced the topic by noting the competitive importance of getting to a trade submitted to the market first and that in 2010 low latency meant < 10ms, but now to be competitive trades need to be submitted in less than 250 microseconds. This means that the electronic decision to trade needs to be done in less than 90 microseconds.

He then argued that Java is the best language to use in developing trading systems since

  1. Popular and is updated to the stay in the forefront of computing
  2. Lots of programmers know Java
  3. Good for coding business logic

However, special programming practices are needed to successfully use Java in a low-latency trading environment. These coding methods consider

  1. Key metric = Time to First Slice (TTFS). Need to worry about the tails.
  2. In low latency, need to consider outside the JVM, including the OS, BIOS, Hardware, Network

As a result the Java code may not look like Java code you usually see. To see how the code needs to be written Buko talked about 5 enemies of high performance Java code and then talked about how to surmount these issues through specialized coding methods.

Enemy #1: the Garbage Collector => need to do your own garbage collection.

Enemy #2: the language and the library: the following affect performance: strings, bigDecimal, autoboxing, Java Collections (e.g. ArrayList grows, Maps rehash), Exceptions, Advance for-loop (create an Iterator), Java 8 Optional Lambda…

Enemy #3: Threads: threads block/context switch, the scheduler will intervene, difficult to reason about performance when there are many threads

Enemy #4: I/O: L1 Cache at 5ns up to disk at 10ms. Main memory is 100ns. To be fast enough one needs to consider where data are stored

Enemy #5: Layers of abstraction: when data is passed from one layer to another the data are copied. The scheduler de-priortizes our process to give other processes their “fair share”

Buko then spoke about how to conquer these issues

#1 Zero garbage – pool objects, share objects, reuse objects, pass parameters. Pre-allocate everything you need to trade that day (3mm trades/day) => no garbage to collect. Since space is pre-created, there is no need to call constructors during the day.

#2. No strings, no dates, no big decimal, no autoboxing. When they receive strings, copy the message directly into their domain as a stream of bytes. All messages are cached at startup. For money values, treat them as fixed precision numbers.

Do not use Exceptions. Instead use a pattern of violations. Always pass a list of potential violations. If a routine has a problem it will add a violation to the list of violations. Aggregate State: have an array of objects into which things are stored. To lookup characteristics, pass an enum to a function.. Replace Java Collections with HPPC and Koloboke or other optimized collections. Be careful with lambdas – can lead to an allocation. Replace foreach() with for(int i=0; i< …; i++) loops

#3. Business logic is single threaded. Use separate threads for I/O and replicating data. Use Lock-Free Queues that allows threads to pass information without synchronization. Threads are pinned to a core – use busy spinning so the core is always looking at the queue. Be mindful of Numa – the physical structure of the board to place each CPU close to the data stream it needs to access.

#4. Use in memory computing. All data is kept in memory as plain old Java objects. No data layer.  “memory is the new disk”. Event sourcing – a database provides assurance of high availability. But they do everything in memory. Instead us event sourcing – every message is processed twice and the backup and the main are coordinated. If the main process fails, the backup can take over in less than a second. Primary will wait for the backup to indicate that the message has been processed. Disaster Recovery is supported using a separate off-site replication – don’t wait for the DR site to complete its calculations, but other than it’s similar.

#5. Zero copy –use a special network card to bypass the network card. Use a DirectByeBuffer to refer to the off-heap data (so you don’t need to copy to the heap). Use framing – to view the buffer without needing to decode the entire message. Can copy the input buffer using bulk copy and could possibly keep it in the buffer and then use a bulk copy to send it to the market. Never copy data into the JVM heap. Try to make the messages look like their states so there is no translation so they can be directly worked in the domain.

Finally he talked about

X Platform is a way forward so you can concentrate on the business logic. It creates the underlying structure that you can use in low-latency trading.

posted in:  finance, New York Java Meetup    / leave comments:   No comments yet

#Payments Investing with Jordan Bettman

Posted on June 25th, 2015


06/25/2015 @EntrepreneursRoundtableAccelerator, 214 W 29th Street 5th Floor, NY


Jordan Bettman @BainCapitalVentures spoke about his experiences funding startup firms. BCV does lending from 3-5mm series A to 80mm majority recapitalization.

Jordan, who was interviewed by Derek Webster, concentrated on the opportunities he sees in his specialty: financial services. Jordan was excited by new ventures in insurance (For instance, there is a p2p auto insurance startup in Germany which underwrites using social networks). He also said there are lending startups that show promise.

Jordan talked extensively about commercial payments. He explained that electronic payments to merchants were pervasive, but the complexity of b2b payments has slowed the use of electronic systems. He cited the experience of Home Depot Services which accepted ACH, but subsequently stopped accepting it from commercial builders.

The lesson from this is that both accounts payable and accounts receivable need to be automated for the system to succeed. This is the context for two of their investments: Chrome River (AP) and Bill Trust(AR).

Jordan also talked about what he has learned.

  1. The success of a startup is base on the founder’s ability to navigate issues in a changing world
  2. Consider how the founder handled past mistakes
  3. It now takes 7 years for a company to mature, so you are in for the long haul
  4. Consider carefully the capabilities of established players to respond
  5. Know what the company can do to defend its advantage
  6. Founders have blind spots so it is important they hire quality people to fill those holes

He had views on the future of payment systems

  1. Payment systems are dominated by large scale competitors with big cost advantages, so startups need to be revolutionary. (e.g. Strip can set up an account within 24 hours)
  2. NFC will eventually gain acceptance as a payment method, but it will take time: domestically the current credit card experience is not broken. But the 3rd world, may skip the credit card stage and go directly to non-contact payment. (Similar to the pervasive use of mobile payment methods in Kenya)
  3. Payment tokens (the 16 digit code is translated into a code) might be important if hacking attacks on phones increase.

Jordan closed with the following observations

  1. The NY startup ecosystem has grown rapidly, but still does not have the gravitas of SF, with the possible exception of financial systems
  2. Solvency & fairness are considerations when investing in insurance companies, but it will take time for the regulators to understand how social media and big data affect underwriting decisions.
  3. Plaid is a startup which leverages their expertise in big data. They partner with banks to clean and standardize data.

posted in:  applications, Big data, finance, Mobile Payments NYC, startup    / leave comments:   No comments yet

The #Psychology of #Savings and Personal #Finance with Qapital

Posted on April 13th, 2015


04/13/2015 @TurnToTech, 184 Fifth Ave, 4th floor, NY


Jane Ruffino – head of marketing @Qapital – talked about an app to help “millennial” savers save money and attain their goals. Qapital was started in 2012 and launched a product in Sweden in 2013. In March they launched an Apple app for the U.S. market with an Android app later this year. The app is paired with a debit card to one of 5 banks. The goal is to provide encouragement to save for one’s goals using automatic triggers and feedback on attaining goals such as money for a vacation or a major purchase.

Jane emphasized findings from focus groups targeting two audiences.

Age 18-24 – many see cash flow as savings

Age 25-40 – many see cash flow as reserves, but also are saving for bigger-ticket items.

In both audiences, the focus groups said

  1. money is boring, but pursuit of goals is important
  2. they want more from their money – but there is no education on how to invest their savings
  3. they don’t identify as ‘money people’ even if they are good savers
  4. they have anxiety about debt, stability and security
  5. shame defines their relationship to money – about having no money or not knowing what to do with it. This also appears when they consider if they deserve the vacation they want to take?

Given these findings, she recommends that the following be considered when designing the app:

  1. Make money less boring – create a sense of purpose: what do you want this year? Take care of needs and wants
  2. Let them be in charge – the reinforcement must match their interests and goals
  3. Give them credit – people know more about finance than they give themselves credit for – (money management associated with their mother)
  4. Validate their actions – e.g. gamify – save together to cheer each other on.
  5. Help them celebrate every win.

Making the goal concrete is essential to both give focus and create a tangible reward. Short- and intermediate-term goals are the emphasis. Creating the rules for saving should be part of the entertainment / reward for saving.

One challenge will be to keep users interested in the app to avoid the rapid drop-off in usage experienced by some fitness and dieting apps (see notes: Brian Cugelman from the previous meeting of ActionDesignNYC).

Further research on millennial’s money-views might be illuminating as we move from a zero interest rate environment (savings are a safe way to store money) to a higher interest rate environment (one can earn interest that will compound over time).

Jane’s emphasis was on savings behavior, but this might be the gateway to education on investing. I would not be surprised to see a relationship between savings behavior/rewards and risk tolerance/aversion as an investor(for a technical discussion of risk aversion download the paper on my research blog post).

posted in:  ActionDesignNYC, applications, finance, psychology    / leave comments:   No comments yet