Name: Fintech Data Journey
Start: 2021-08-24T17:00:00Z
End: 2021-08-24T17:00:26.000Z
Location: BrightTALK
Rating: 5

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The Nexum AI Platform Adoption Framework: A guiding framework for leaders who want to leverage the power of AI to transform their business. And a tool to assess where you are in your journey and define where you want to be.

Nexum AI as a Service was developed as an engineer’s guide to building AI-enabled platforms and services. The aim of the  our platform is to get you up and running, and able to produce results quickly, without getting stuck in the weeds. AI and  machine learning are big topics, and there is an awful lot to learn if you wish to master these disciplines. We examine these  from a developer’s perspective to provide a practical, hands-on guide. All of the major cloud vendors are engaged in a race to provide relevant AI services, such as  
○ Image recognition  
○ Speech-to-text, text-to-speech  
○ Chatbots Language translation  
○ Natural language processing  
○ Recommendations  

We review the current state of the art, and we categorize the available services on Google into a standard architectural  structure. Following we dive right in and build a serverless image recognition system as our first AI as a Service platform.

NEXUM Cloud’s AI Platform Adoption Framework AI as a Service

In a rapidly growing FinTech market in the UK companies need innovative approaches to distinguish themselves from competition and to constantly create value for their customers. Collecting and utilising proprietary customer data becomes a key enabler for success. This presentation will focus on how to leverage transaction and customer behaviour data for effective CRM strategies to boost customer loyalty and retention.

Harnessing Data for Effective Customer Relationship Management in a Fintech

Implementing AI in Finance.

AI is no different from implementing any new technology project, you need a strategy, the right people and a clear goal to make the implementation a success.  Often with AI projects, scepticism, a lack of defined use cases or the culture prevents successful adoption.

The presentation will look at the high level basics needed to implement AI.  We will cover the following topics:

- Data/People/Culture
- The right use cases
- Engaging with the business/customers
- The right technology
- Gain trust in the AI
- Appendix – NLP / Supervised Learning

The key takeaways will be the steps required to actually get AI implemented and adopted.  Breaking down the challenges across culture, use cases, engagement, technology and trust in AI itself.  We will also cover the key concepts of NLP and Supervised Learning.

How to make an AI implementation happen…

This webinar will cover:

- Definitions of key terms
- What is the rationale for looking at digital backend and/or blockchain-based payment systems?
- International payments landscape – cursory overview (China focus)
- What is happening in the UK/USA
- Next steps and options for businesses to engage

Where crypto meets payments: CBDCs, stablecoins, and digital rails in context

In the last months the fintech landscape has significantly changed and as a consequence, the Venture Capital investment approach to the sector. Fintech still accounts for a significant share of venture funding globally but new themes are emerging and they require deeper knowledge and understanding. We will discuss old and new investment thesis both from a VC and strategic players point of view.

A Venture Capital perspective of digital transformation in Financial Services

Embedded finance is the seamless distribution and integration of financial products into existing services offered by non-financial brands during the most relevant part of the user journey. Over the last 36-months, Buy Now Pay Later (BNPL) has experienced incredible growth and showing little signs of slowing down – it’s valued at over $4billion and growing.

The embedded finance market presents a £7trillion opportunity by 2030, but it will take more than BNPL to reach this milestone. In this webinar, Barry McCarthy, Founder of Assure Hedge, looks at what’s next for embedded finance.

·     Where are the opportunities?

·     How does data influence product creation?

·     How embedded finance keeps business afloat?

·     How embedded finance gives businesses access to global talent

Embedded Finance: Beyond Buy Now and Pay Later

During H1 2021 alone, financial institutions have already been fined over $2 billion.
This has been partly due to failures in risk identification and by not having effective AML and KYC  in place to monitor accounts.
However, customer onboarding is getting tricky as regulations vary across industry and by region; 
Join us to learn about best practices for customer onboarding, and continuous trust.
 
Takeaways

-Learn about the challenges posed by regulation
-Get industry best practice hints and ideas
-Reduce onboarding fraud whilst minimizing friction

Seamless Customer Onboarding: Fact verses Friction

Discover new revenue streams and cost savings for banks as custodians of users' identities and data (without the current liability model). Find out how SSI revolutionises customer experience while reducing costs and improving data.

Self-Sovereign Identity: New Recurring Revenue for Existing Data

Learn about how protecting your data can actually expand your business.

Data-centric zero trust opens up new workflows for KYC and source of wealth validation, broker to customer direct transactions, transaction insights, customer support, and on-prem to hybrid cloud data transfer.

Protect against ransomware extortion while staying compliant with data residency, a chain of custody, and right to forget. Gain an understanding of how a data-centric cyber solution will keep your data safe when your network is hacked and allow you to reduce costs while expanding opportunities.

Frictionless and Secure KYC with Data-Centric Zero Trust

Video: NEXUM Cloud’s AI Platform Adoption Framework AI as a Service

Online data is a vast and ever-expanding resource in the battle against financial crime. 

However, the volume of information can be overwhelming, and it can be a struggle to identify what’s relevant. 

In addition, the information explosion has led to more public scrutiny than ever, and reputations that took years to build can be destroyed in one headline.  

How can you ensure you get a full and fair picture?

In this expert discussion you will learn:

1. The latest risks and challenges relating to the use of open source material to fight financial crime
2. Regulatory expectations on using open source data for due diligence and monitoring
3. How technological innovations can harness public information
4. Emerging best practices for reputational risk protection in the digital age


Chair: Laetitia Hoffmann, Global Product Manager - Due Diligence at Dow Jones
Shaun O’Mahony, Co-Founder of Xapien
Daniel Secretan, Co-Founder of Xapien
Tom Lawman, Senior Consultant at FINTRAIL

Mobilising online data to fight financial crime

• Tokenization of everything – Assets, Money, Cryptocurrencies
• Digital Identities & payments – phase one : Centralized identity, phase two: Federated Identity, Phase three: User-centric Identity, Phase Four : Self-sovereign Identity, from personal data controlled/owned and centrally stored by business to owned/controlled and de-centrally stored by User
• Increasing A2A Payments and open banking support – open finanance API network, Account Entry Push Notifications, Reservation of funds, Deferred and recurring payments, Request to Pay, Initiation of a consumer loan = BNPL, SEPA Direct DebitImproving conversion and UX
• Value Added Services around payments e.g. - BNPL will further grow, Credit card-based BNPL as fight back for banks, Digital Receipts will get more momentum, Next Generation Loyalty Offers - the age of data blindness & simple transaction-rewarding is over
• Improving the PSD2 SCA with better use of newer 3DS protocols (EMVCo 3DS 2.3) - eCOM Tokenization, Click To Pay, Delegated Authentication, split SDK and device binding
• Increasing Interest in Crypto Assets - Crypto trading apps as part of their digital offering
• Green & Sustainable Payments – Carbon free - For the Financial Services Industry, Green Payment is going from niche to mainstream through the following development drivers: technology, consumers, data and coming soon

Digital ID, Open Banking, BNPL, Tokenization, PSD2 SCA, Crypto Assets, Payments

Coinfirm AML Oracle was the first smart contract-based solution for AML compliance of the burgeoning decentralized finance (DeFi) scene. The Oracle unlocks a key barrier that DeFi presented to previously developed blockchain compliance technology on the market.

Because DeFi protocols run on-chain smart contracts – meaning that any compliance layer needs the same format of technology required to interact with a DeFi provider such as a decentralised exchange (DEX) through client smart contracts – a specifically tailored solution is necessary.

Currently operated with Ethereum and RSK protocol, the Coinfirm AML Oracle is that solution – enabling decentralized entities to continue their lending, staking and general DeFi activities without fear of falling afoul of nefarious actors in their system – with an added emphasis on security and cost-effective gas usage.

The Financial Action Task Force's updated draft guidance from 09.03.2021 massively expands the types of entities falling under the FATF’s purview. The updated guidance requests member states to ensure DeFi platforms are covered by AML laws, even if there is no single party responsible for live networks. The Coinfirm AML Oracle offers both a partial and fully decentralized solution to proactively manage compliance risks and comply with regulations.

When users interact with a decentralized finance provider, their wallet address is queried for risk through the Coinfirm AML Oracle, which in turn passes data from Coinfirm’s API to generate a report ID C-Score based on 330+ risk evaluation scenarios that relays the information to the DEX.

The Future of Regulatory Compliance in Defi Space

In today’s complex environment organizations are embarking on Digital Transformation journey.  Compared to existing systems, blockchains are faster, cheaper, more reliable, and much more secure.  For example, in healthcare, patients often have medical history scattered among various medical records maintained in several health-care establishments.  The data is available only in the scope of those specific systems.  Having a Blockchain Medical Profile to store an individual’s medical profile that is accessible from anywhere at the time of need.  This omnipresence of the medical data will be a boon for the field of medical informatics.  

Similarly, in financial institutions, transactions that happens within and among financial institutions can be delivered, provided immediately, shared, and completely transparent stored on an immutable ledger via Blockchain technology.  

The faster the information is received and the more accurate it is, the better.  Blockchain is ideal for delivering that information because it provides immediate, shared and completely transparent information stored on an immutable ledger that can be accessed only by permissioned network members.  Blockchain technology and its infrastructure (hardware, software, and facilities, connectivity, mobility, performance, and security and such can be easily deployed and managed using ITIL best practices.

Speakers: 
Waseem Ahmed, VP IT Production Operations, Citibank NA
Atif Farid Mohammad PhD, Adjunct Professor, Artificial Intelligence, Machine Learning, Blockchain, UNC Charlotte

Blockchain Adoption, Management, and Application

Learn about the data migration from SQL to big data infrastructure.
Know about the data scraping and data collection. 
Data Analytics techniques using machine learning, python and tableau.
The road map and challenges of building risk models.

Key Points:
Building Data platform
Data Migration
Data Collection
Data Analytics
Risk models

Fintech Data Journey

Fintech

Data Analysis

Data Analytics

Data Architecture

Data Best Practices

SQL server

Big Data Analytics

Big Data

Risk Management

Machine Learning

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Fintech Data Journey

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