Post-Modern Porfolio Theory with David Siegel

Blockchain is all over the news nowadays, but what does it mean to the automotive industry?

Understanding Blockchain technology: zooming out to observe structural challenges in the automotive industry

How could blockchain address these challenges?

This is the first of a year-long global webinar series, focusing on the current activities and actions within financial services, geared toward the achievement of the Global Sustainable Development Goals.

Topics in this webinar series balance the three dimensions of sustainable development: Economic, Social, and Environmental.

In this webinar, Genady will talk about implementing AI projects in a financial services environment. More specifically, he will cover the following topic areas:

- Understanding what Artificial Intelligence can and can’t do
- What to take into consideration before the implementation and how FSI is different from other industries
- Step by step solution implementation avoiding common mistakes
- Choosing right resources for a task in-house vs. partnering vs. buying

Join our live webinar to learn which elements of AI are driving value for risk and compliance? (i.e. ML, NLP, RPA). Also learn about AI in practice - how regulated financial institutions are utilizing AI today, why
why AI is the only answer to addressing big data compliance challenges, at scale. We will also go over what happened when RegTech met SupTech – how are regulators are applying AI to ease and accelerate compliance processes.

Findings from this year's Fintech Disruptors Research on trends in digital finance across the EMEA region ask as many questions as they answer - when does enough technology become too much - and how has the fall out from data breaches and social media data scandals tipped the balance back in favour of old-fashioned retail banking?

Taking in 4 key trends that will define the next decade of fintech - discover possible scenarios to some of these questions and more in our webinar that explores how the industry is responding to the promise of an automated financial services future and the progress it's making so far.

Any process and interaction that can be digitised is being digitised - either for customer convenience or, for operational efficiency and costs. But, what happens when every bank and every possible process is digitised. What next? How can banks differentiate themselves? What role can data and AI play in creating value?

In this session, we will hear from industry leaders on their views on this topic and pragmatic recommendations on how to get started on this journey.

Moderated by:
Bharat Bhushan, CTO Banking & Financial Markets, IBM
Panelists:
Marie Measures, CIO, Coventry Building Society
Richard Price, Sales Director, TIBCO
Valentina Kristensen, Director, Growth & Communications, OakNorth
Mitesh Soni, Senior Director - Innovation and Fintech, Finastra

Machine learning can help process the enormous volume of data that is overwhelming traditional IT security infrastructure and human researchers. It automates and scales cybersecurity to meet these
growing challenges.

Leveraging the capabilities of machine-learning enabled systems is critical for organizations that are highly targeted for cyberattacks. This presentation will examine the benefits machine learning provides to reduce fraud and manage risk.

In most cases fraud, risk, and information security functions often only interact in the aftermath of a breach, and security and fraud point solutions typically remain isolated. With maturity in data pipelines, availability of shared data sets across risk, fraud, and information security, AI can be effectively used to detect anomalies and be predictive.

In this webinar, Dr. Srinivas Mukkamala, a recognized expert on AI and neural networks, will discuss how a risk-based approach can facilitate the convergence of cybersecurity and fraud.

Join Aslam Mohammad at BPC Banking Technologies as he discusses how machine learning plays a crucial role in modern fraud prevention solutions. Discover what implementation options you have as a financial institution and what lessons can be learned from the field.

What is AI and how is it different from traditional analytics?
How is AI currently applied in context of different types of fraud and data sets?
How does AI help people make smarter decisions and what does that mean for workflow and process + future roles working with AI
What do companies need to do to be AI ready for fraud prevention?
What does the future look like in terms of extension of AI capability and usefulness and how will this play out across into types of fraud and crime for example AML, Sanctions, employee misconduct etc?

There’s much hype and excitement around how AI and machine learning could transform the world of finance. But a key area of development growing behind the scenes of talking robots and automated assistants is how these new technologies will have a seismic impact on Anti-Money Laundering (AML) and Counter-terror Financing (CTF) back-end compliance processes. AI can dramatically improve AML risk data collection; spotting new risks faster and digging deeper for hidden risks.

It will also shift customer onboarding & KYC processes from ‘name matching’ to contextual ‘identity matching’ to reduce false positives and false negatives. Unlike other industries, the training data required to make this a reality with machine learning techniques are available today.

AI-driven compliance will ultimately have an enormous impact on how financial services will work - increasing automation, reducing manual overheads and helping prevent financial crime.


Presented by Charles Delingpole, CEO & Founder ComplyAdvantage

Charles Delingpole founded ComplyAdvantage in 2014, and as CEO leads the product development and growth of the company. Charles set up his first company, The Student Room Group, now the world’s largest student discussion forum, when he was 16. After completing his MA in Politics at Trinity College Cambridge, and then an MSc in Management, Strategy and Finance from the LSE, he became an associate at J.P. Morgan Cazenove. He then went on to co-found FinTech firm MarketInvoice, a peer -to - peer financing company which uses customer data to digitise the approach to financial risk analysis.