Challenger Banks - where's the challenge?

You can pay for groceries and get money out of an ATM with your face. As fintech is enabling a more customer-friendly experience on mobile devices, security hangs in the balance. It is easy to make a transaction, but what are the real steps involved? This webinar will showcase the complex technology and will help financial services companies understand the work that goes on behind the scenes to make some simple and easy processes actually happen.

Join this panel to learn about:
- Why biometrics are becoming easier to employ in identity verification
- The challenges that fintechs face in creating a seamless user experience - even if you're wearing a face mask
- the nuts and bolts behind complex technology that solves identity fraud

Panelists:
Reinhard Hochrieser, VP, Global Product Management, Jumio
Sujata Dasgupta, Global Practice Head – Financial Crimes Compliance, Tata Consultancy Services
Rachel McLaughlin, FinTech/RegTech Industry Consultant

FinTech are adopted world wide in Financial organizations for the growth of businesses and customer satisfaction.
The advanced machine learning techniques are reshaping the financial services due to its high computing power and ability to analyze the Big Data.
The Financial Companies are deploying Artificial Intelligence and Machine Learning technologies to streamline the processes, optimize portfolios, decrease risks and reduce the human errors.
• You'll learn:-
- The concept of Artificial Intelligence and Machine Learning
- Need of Artificial Intelligence and Machine Learning in FinTech - Machine learning Process for FinTech
- Case Study

This presentation will be reviewing the following topic areas:

1) What the Data Protection Legislation and ICO Guidance says about AI.
2) A little bit of Myth Busting.
3) What I would like to see in terms of AI developments/AI as a Data Protection Compliance enabler.
4) My Top Tips for making sure your AI is Data Protection Compliant by Design and by Default.




(Please note that any views expressed in the talk/presentation/ Q and A, and any handouts/takeaways, other materials, are my own and do not necessarily represent those of my current, employer (or, any past employers). I am not a fully qualified lawyer and my talk/presentation, responses to questions, and any associated materials do not give legal advice.)

Financial services data is being created at a breakneck pace. Because this data is sensitive information on customer and operations, identifying, minimizing and preventing fraud is top of mind. Indeed, regulations & compliance procedures are aimed at ensuring customer data is treated properly. Data & analytics can help ensure compliance with banking regulations. Join this panel to learn about:
- The new tools are being used to help secure financial services data
- The strategies involved in safeguarding PII
- Staying compliant with financial services regulations

Dror Shapira:
dror.shapira@inviou.com

David Fleck:
DavidF@veritabledata.com

Ian Mitchell:
ian.mitchell@pwc.com

Adam Martin:
adam@progeny.tech

How to use machine learning techniques to improve your approval rate while minimizing fraud

With increased focus on using machine learning as a key pillar in the fraud detection process, it is important for merchants to stay focused on the end-goal of increasing approvals and not leave money on the table. Vesta Data Science team will share some key insights to stay ahead on maximizing revenue and how Vesta makes their customers more and more successful. We will go in depth into the following

o Machine learning pipeline and automated model refresh and why that is key
o Ensemble model techniques – getting the best performance from your models
o Integrating with unsupervised machine learning

The banking & payments industry relies heavily on data. From marketing and CRM to internal processes and regulatory compliance, working with data properly can mean the difference between success in failure. But with so much data to work with, and limited time to work to deliver value, human error can result in massive fines, and a loss of customers. AI and Machine Learning are becoming increasingly valuable in keeping financial services operating smoothly and protecting their customers. Join this panel to learn about:
- How AI can help banks learn about & implement new regulations.
- How to ensure regulatory filings are correct and done on time.
- How Machine Learning can help reduce fraud and personalize marketing.
- And more!


Panel moderated by:
Dr Estelle Brack, Founder & Chairman, KiraliT
Featuring:
Michael Robinson, Vice President, Insurance UK & EU, Genpact
Labhesh Patel, Chief Technology Officer and Chief Scientist, Jumio
Clive Elleforde, Chief Revenue Officer, Sovran

Keeping customers at the heart of its decisions is the mantra to success for businesses who aspire to sustain and grow. Well planned and carefully selected use cases, powered by AI are helping financial services organisations serve customers in far more efficient and creative ways than ever before by bringing the best of Human and machine together.

In this talk we will explore:
1. What are some of the real world use cases from banking
2. What are some of the challenges in adopting AI in banking
3. What is the way forward for the industry

Chatbots in Financial Services haven't delivered what we expected. So, what’s next?
The world’s media is littered with articles stating that Covid-19, and the sudden emptying of call centres, has driven organizations to implement AI to cope with the increased burden of customer contact. All this, whilst in tandem reducing the cost of doing so.

Additionally, business continuity has become a board room imperative. AI is now seen as a potential opportunity to create future stability and the financial services sector is not immune to this pressure.

However, by 2020 most financial services organisations had already made significant investments in AI technology with the expectation of increased customer service, dramatically lower costs and a much-reduced reliance on large and expensive call centres. But it didn’t work to plan.
In this enlightening presentation Chris Tew and Alex Hoffman will discuss why most of today’s AI technology isn’t up to the current industry requirements and what financial services organisation need to think about, now and tomorrow.

Topics covered include:

• What’s the root cause of such an AI failure to date?
• How to address the current issues presented by Covid-19
• What are the opportunities for AI future innovation?

Traditionally, risk management professionals had to choose between the full picture and interactive analytics. Banks deal with many types of risks every day including market risk, credit risk, operational risk, business risk, etc. Millions of data points are collected daily around the world and are made available for risk-related decision-making. How can businesses enable their users to fully leverage all the data assets when they make these critical decisions?

In this session, we will talk about how a global investment bank built a risk analytics platform on Kyligence Intelligent Data Cloud. Kyligence analyzes users historical data, identifies the questions that are relevant to risk analysts, prepares the most up-to-date answers, and places these answers at the fingertips of all their analysts around the world. By adopting Kyligence technology, the risk management team is able to get insight from all of its historical data instantaneously, at a fraction of the cost of a traditional data warehouse.

Speaker Bio:
Li Kang serves as the head of Kyligence's operations for the Americas. Bringing with him a deep technical background in analytics from his time as an engineer and solutions architect, Li drives both the technical and business strategy for all of Kyligence's major efforts in the West.

Data is more valuable than oil, and the ability of the financial services industry to gather, process, analyze, and sell data is creates opportunities and challenges. Proper data management systems that are primed for compliance can help reduce risks, propelling the industry forward.

Join this panel to:
- Hear about the newest tools & strategies available to help fintechs and financial services firms manage their data effectively
- Learn best practices in data gathering & aggregation
- Discover retroactive data cleansing tools and procedures for financial services institutions

Panel moderated by:
Elena Kozhemyakina, CEO and Founder, Fintech4Funds

Panelists:
Rajeev Pai, Senior Business Consultant - Design and Initiation – Data & Analytics, HSBC Global Services
Pat Bates, Principal Sales Engineer, Privitar
Carlos Gutierrez Arguello, Open Innovation and Partnerships Director, DemTech

Technology is driving organisational change at a breath-taking pace and those charged with governance and management need to ensure that risk management and compliance evolves in step to provide efficient and effective control in the age of disruption.

The good news is that sophisticated data and technology tools can enhance or replace previously tedious and judgement-based activities with efficient, evidence-based, real-time and predictive compliance and risk management.

In this session Nida will focus on how analytics, machine learning and AI is and can be used by organisations to optimise areas such as governance, risk management, fraud prevention, compliance, audit and assurance.

With regulations around data processing becoming ever more stringent, and the huge risk of reputational damage from leaked data, join Privitar to better understand how managing data privacy isn’t easy, what you should consider when implementing it and then how you can make it work in your organisation.

In this webinar you will learn about:

- How organizations can balance the risk of speedy access to data with privacy
- The best strategies for implementing data privacy
- How data privacy can be adopted enterprise-wide

Financial Services and Banking institutions are in a race to adopt and deploy Artificial Intelligence, its subset Machine Learning, and other advanced analytics. Why? Finance is a field which uses a huge amount of data. It is not possible anymore to analyse that volume of information without powerful machines. The disruption is now, and it is only the beginning.

These technologies have become instrumental for financial institutions to dive into users’ data as much as possible so that the organisation is able to deliver a product as tailored as possible to client’s needs. At the same time the public concern is growing about the use of AI technologies and their potential to harm individuals.

Whether your organisation is already capitalising on AI initiatives and you are helping the business managing its financial data, or your organisation is starting its AI journey, you will need to keep your eyes on the prize: record, collect, process, share, transfer data in an effective compliant manner and ultimately in an ethical fashion. In this highly regulated industry, fulfilling your multiple compliance mandates and your – sometimes – overlapping obligations is the foundation. You want to add the ethical dimension to your foundation building programme.

This talk will explore 3 key topics highlighting what authorities have put in place to strike the balance between privacy and AI innovation:

- Guidelines and initiatives at EU level; within UK, and France jurisdictions
- The existing GDPR regulation and some of its provisions whether they are general or specific to AI (article 5, article 22, consent, breaches)
- How considering financial data protection through an ethical lens can help in reducing risk

This session will address the following areas:

- Digital Wealth Management and customer centric solutions
- Analysis in wealth Management. Personalised experience
- Artificial Intelligence: new combination of science and human based advisory models are emerging
- How to cover regulation with Wealth Management Solutions

Jaime Bolivar, Managing Director, TechRules
Begoña Rubio, Business Development & Marketing Director, TechRules
Javier Carrallo, Business Development Manager, TechRules

Join Ryan Ross as he sits down with Daniel P. Simon, Author The Money Hackers, to discuss the world of fintech as discussed in the book.

About the book:
Whether you’ve heard of fintech or not, it’s already changing your life. Have you ever “Venmoed” someone? Do you think of investing in Bitcoin - even though you can’t quite explain what it is? If you’ve deposited a check using your iPhone, that’s fintech. And if you’ve gone to a bank branch and discovered it has been closed and shuttered for good, odds are that’s because of fintech too.

The Money Hackers focuses on some of fintech’s most powerful disruptors - a ragtag collection of financial outsiders and savants - and uses their incredible stories to explain not just how the technology works, but how the Silicon Valley thinking behind the technology, ideas like friction, hedonic adaptation, democratization, and disintermediation, is having a drastic effect on the entire banking and finance industry.

About Dan:
Daniel P. Simon is a writer, entrepreneur, and financial communications expert. He has been part of the Fintech Revolution since its inception, advising on some of the biggest brands in the space including Morgan Stanley, Bloomberg, and Goldman Sachs.

Daniel’s focus on finance and its future led him to become CEO and Co-Founder of Vested, an integrated communications firm where he and his team partner with top financial and fintech companies.

Daniel’s natural curiosity about all things related to finance and his unique viewpoint as an insider in the financial industry have perfectly positioned him to be an authority on the beginnings of the fintech revolution. He’s been watching the industry since its inception and has chronicled its major events, from the day when Apple launched its App Store, to the Winkelvoss twins becoming key players in the world of Bitcoin, and beyond.