IIR & IBC Finance is part of the Knowledge and Networking Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 3099067.

Informa
8:30am - 8:50am

Registration & welcome coffee

More
8:50am - 9:00am

Chairman's opening address

  • Jonathan Regenstein - Director of Financial Services, RStudio
More
9:00am - 9:30am

Big picture fintech innovations that are taking the finance world by storm

What is the probable impact of fintech development on the financial services?

  • Emil Matsakh - Chief Analytics Officer, Commonwealth Bank of Australia
More
9:30am - 10:00am
Info

Trade based money laundering

Regulatory expectations and implications on banks & their clients

  • Talal Mahmud - Regional Head Trade, Financial Crime Compliance Americas, Standard Chartered Bank
More
10:00am - 10:30am
Info

Embracing the cryptocurrency and blockchain boom

Blockchain from hype to reality. What are the risks and consequences of using blockchain and smart contracts?

  • Periklis Thivaios - Researcher, IE Business School
More
10:30am - 11:00am

Morning coffee break

More
11:00am - 12:00pm
Info

AI & Machine learning

30mins: Expert briefing

Reducing the calculation burden in risk management using machine learning

Can AI be applied to derivatives pricing problems in a way that can stand up to regulatory scrutiny?

David O’Donovan, Risk Management Expert, Murex

30 mins: Panel discussion

AI and machine learning implementations for model development and validation

  • Methods for benchmarking models
  • What are the elements you can apply?
  • Successful case studies
  • Lourenco Miranda - Managing Director, Societe Generale
  • Xiaofeng Xia - Partner, Head of Quantitative Investments, Hongshang Asset Management
  • David O’Donovan - Risk Management Expert, Murex
  • Moderator Brad Carr - Director in Regulatory Affairs, IIF
More
12:00pm - 12:30pm
Info

How big data is changing banking and finance forever

30mins: Expert briefing

What finance can learn from big data analysis and scientific applications 

30mins: Panel discussion

From big data to insights: Do you hold the key to solving pressing issues and capturing market opportunities? 

  • Striving to adopt a fully data-driven approach
  • Optimizing business operations
  • Overcoming operational constraints

 Achieving customer-centric objectives

  • Dan Rosen - Co-founder and Chief Executive Officer, d1g1t Inc.
  • Norman Niemer - Chief Data Scientist, UBS Asset Management
  • Moderator Angel Lorente - Co-Founder and Master Connector, FinTech Connector
More
12:30pm - 1:00pm
Info

Fintech Disruption: The people impact of innovation

In the next 5 to 10 years the financial services industry will undergo a significant digital disruption that will impact the core infrastructure of banks and financial institutions. This innovation will disrupt the lives of millions of people that serve these institutions as employees, service providers, entrepreneurs, and investors

The questions we need to answer as we disrupt financial services are:

  • How do we reskill/retool the professionals to learn the new skills brought on by fintech innovation?
  • How do we ensure that entrepreneurs are creating real world solutions to financial service problems?
  •  How do we direct investors both internally and externally to the fintechinnovations that will have the biggest impact for all people
  • Angel Lorente - Co-Founder and Master Connector, FinTech Connector
More
1:00pm - 2:15pm

Lunch

More
Showing of Streams
3:15pm - 3:45pm

Afternoon coffee break

More
Showing of Streams
5:00pm - 5:45pm

Cocktails and conversations

More
8:30am - 8:50am 20 mins
Registration & welcome coffee
8:50am - 9:00am 10 mins
Chairman's opening address
  • Jonathan Regenstein - Director of Financial Services, RStudio
9:00am - 9:30am 30 mins
Info
Big picture fintech innovations that are taking the finance world by storm
  • Emil Matsakh - Chief Analytics Officer, Commonwealth Bank of Australia

What is the probable impact of fintech development on the financial services?

9:30am - 10:00am 30 mins
Info
Trade based money laundering
  • Talal Mahmud - Regional Head Trade, Financial Crime Compliance Americas, Standard Chartered Bank

Regulatory expectations and implications on banks & their clients

10:00am - 10:30am 30 mins
Info
Embracing the cryptocurrency and blockchain boom
  • Periklis Thivaios - Researcher, IE Business School

Blockchain from hype to reality. What are the risks and consequences of using blockchain and smart contracts?

10:30am - 11:00am 30 mins
Morning coffee break
11:00am - 12:00pm 60 mins
Info
AI & Machine learning
  • Lourenco Miranda - Managing Director, Societe Generale
  • Xiaofeng Xia - Partner, Head of Quantitative Investments, Hongshang Asset Management
  • David O’Donovan - Risk Management Expert, Murex
  • Moderator Brad Carr - Director in Regulatory Affairs, IIF

30mins: Expert briefing

Reducing the calculation burden in risk management using machine learning

Can AI be applied to derivatives pricing problems in a way that can stand up to regulatory scrutiny?

David O’Donovan, Risk Management Expert, Murex

30 mins: Panel discussion

AI and machine learning implementations for model development and validation

  • Methods for benchmarking models
  • What are the elements you can apply?
  • Successful case studies
12:00pm - 12:30pm 30 mins
Info
How big data is changing banking and finance forever
  • Dan Rosen - Co-founder and Chief Executive Officer, d1g1t Inc.
  • Norman Niemer - Chief Data Scientist, UBS Asset Management
  • Moderator Angel Lorente - Co-Founder and Master Connector, FinTech Connector

30mins: Expert briefing

What finance can learn from big data analysis and scientific applications 

30mins: Panel discussion

From big data to insights: Do you hold the key to solving pressing issues and capturing market opportunities? 

  • Striving to adopt a fully data-driven approach
  • Optimizing business operations
  • Overcoming operational constraints

 Achieving customer-centric objectives

12:30pm - 1:00pm 30 mins
Info
Fintech Disruption: The people impact of innovation
  • Angel Lorente - Co-Founder and Master Connector, FinTech Connector

In the next 5 to 10 years the financial services industry will undergo a significant digital disruption that will impact the core infrastructure of banks and financial institutions. This innovation will disrupt the lives of millions of people that serve these institutions as employees, service providers, entrepreneurs, and investors

The questions we need to answer as we disrupt financial services are:

  • How do we reskill/retool the professionals to learn the new skills brought on by fintech innovation?
  • How do we ensure that entrepreneurs are creating real world solutions to financial service problems?
  •  How do we direct investors both internally and externally to the fintechinnovations that will have the biggest impact for all people
1:00pm - 2:15pm 75 mins
Lunch
2:15pm - 3:15pm 60 mins
Info
Examining the risks and realities of embracing innovation
Cybersecurity: an interactive experiment
  • Antonio Giannino - Chief Risk Officer, Amagis Capital

An interactive simulation that will test the participants’ cyber resilience – ability to prepare for, respond to and recover from a cyber incident

2:15pm - 3:15pm 60 mins
Info
Reinforcement Learning (RL) approach to portfolio trading
Case studies
  • Igor Halperin - Adjunct Professor of Financial Machine Learning, NYU Tandon School of Engineering

Use case 1. Trading a European option with RL.

Use case 2. Using RL to find optimal portfolios for both individual investors and the whole market. Connection with the Black-Litterman model.

2:15pm - 3:15pm 60 mins
Info
Hands-on data engineering tutorial for alternative data
The best tools to analyze alternative investment data
  • Norman Niemer - Chief Data Scientist, UBS Asset Management

Alternative data such as credit card transaction and web data is becoming an integral part of the investment process. Unlike buying datasets and hiring people, the technology infrastructure required to analyze alternative data can be acquired at minimal to zero cost. This is a hands-on technical tutorial where we will use open source python libraries to cover the end-to-end flow of analyzing alternative data. *Bring your laptops with Anaconda python preinstalled!* Specifically in this two-part tutorial you will learn how to:

  1. obtain data from vendors and ingest it without relying on your IT department with luigi and d6tpipe
  2. load data into an analysis package and solve problems with data schema changes with pandas, sql and d6tstack
  3. quickly join data from different vendors using fuzzy joins and address problems with inconsistent identifiers and dates with d6tjoin
  4. preprocess, explore and visualize data for statistical analysis with pandas and seaborn
  5. build a machine learning model that predicts sales beats with sklearn


With that you will have the infrastructure needed to analyze alternative data at a cost of $0!

3:15pm - 3:45pm 30 mins
Afternoon coffee break
3:45pm - 5:00pm 75 mins
Info
Examining the risks and realities of embracing innovation
Innovation from the ground up
  • Dimitri Anagnostopoulos - Principal, True North Partners
  • Periklis Thivaios - Researcher, IE Business School

How can the risk managers drive strategic change and innovation in a role seen as downside risk protection?

3:45pm - 5:00pm 75 mins
Info
Reinforcement Learning (RL) approach to portfolio trading
Case study and summary
  • Igor Halperin - Adjunct Professor of Financial Machine Learning, NYU Tandon School of Engineering

Use case 3. Modeling market dynamics. Going beyond RL: the role of symmetries. The QED model of dynamics of stocks with defaults.

Summary: The role of priors and regularization for RL and ML in finance. Future directions.


3:45pm - 5:00pm 75 mins
Info
Hands-on data engineering tutorial for alternative data
The best tools to analyze alternative investment data
  • Norman Niemer - Chief Data Scientist, UBS Asset Management

Alternative data such as credit card transaction and web data is becoming an integral part of the investment process. Unlike buying datasets and hiring people, the technology infrastructure required to analyze alternative data can be acquired at minimal to zero cost. This is a hands-on technical tutorial where we will use open source python libraries to cover the end-to-end flow of analyzing alternative data. *Bring your laptops with Anaconda python preinstalled!* Specifically in this two-part tutorial you will learn how to:

  1. obtain data from vendors and ingest it without relying on your IT department with luigi and d6tpipe
  2. load data into an analysis package and solve problems with data schema changes with pandas, sql and d6tstack
  3. quickly join data from different vendors using fuzzy joins and address problems with inconsistent identifiers and dates with d6tjoin
  4. preprocess, explore and visualize data for statistical analysis with pandas and seaborn
  5. build a machine learning model that predicts sales beats with sklearn


With that you will have the infrastructure needed to analyze alternative data at a cost of $0!

5:00pm - 5:45pm 45 mins
Cocktails and conversations