Artificial intelligence for banking fraud prevention.
A presentation on how it takes its root in the digitalisation ways and how it impacts customer experience.
Artificial Intelligence for Banking Fraud PreventionJérôme Kehrli
Artificial Intelligence at NetGuardians:
"From skepticism to large scale adoption towards fraud prevention"
Slides of my speech at the EPFL / EMBA Innovation Leader 2018 event.
Future of artificial intelligence in the banking sectorusmsystems
The banking sector is becoming an active adapter of artificial intelligence — exploring and implementing this technology in new ways. The penetration of artificial intelligence in the banking sector had been unnoticed and sluggish until the advent of the era of internet banking.
Artificial Intelligence in the Financial IndustriesGerardo Salandra
As Artificial Intelligence makes its way into our lives, many financial institutions are faced with the difficult question “Should AI be embraced?”. While the eagerness to integrate AI into the financial sector has waxed and waned over the past few decades, it now appears that Fintech is ready to dive head-first into AI as a standard for handling customer transactions, financial risk assessment, industry regulatory compliance and reduced institutional costs.
There is no doubt that AI can be invaluable for the financial industry, but it comes at a price. We expect to witness both success stories and tragic failures over the course of the next few years. With any first-generation technology, there are going to be bugs to solve, and a learning curve before intimate industry familiarity with AI is obtained.
AI is not only going to revolutionize the financial industry but become the industry itself.
Artificial Intelligence: a driver of innovation in the Banking Sector - The Italian case
Marco Rotoloni (Head of the research team on banking operations, ABI Lab)
We are all consumers of financial services more or less. We have bank accounts, possibly life insurance, some of us have credit cards, some of us have fixed deposits, some of us may be doing share trading and investment, some of us are borrowers of loans. These are all financial services. Financial Technology or FinTech is a way of delivering or improving the delivery of financial services using technology and innovation.
The use of smartphones and internet to improve the services in banking, investing, lending and borrowing etc are examples of technologies aiming to make financial services more accessible to the people. The use of Artificial intelligence, Machine learning, Blockchain, Cryptocurrency etc are redefining the way we are used to receiving financial services. FinTech is an emerging industry. Startups, established financial institutions as well as technology companies are disrupting this space to replace or enhance the usage of currently existing financial services.
In this video we will restrict ourselves to the usage of AI in FinTech.
We will learn about different areas where FinTech is already serving a great deal.
We will learn about the areas where we look forward to seeing more disruptions and innovations to make financial services more secure and accessible to the general public.
Artificial Intelligence for Banking Fraud PreventionJérôme Kehrli
Artificial Intelligence at NetGuardians:
"From skepticism to large scale adoption towards fraud prevention"
Slides of my speech at the EPFL / EMBA Innovation Leader 2018 event.
Future of artificial intelligence in the banking sectorusmsystems
The banking sector is becoming an active adapter of artificial intelligence — exploring and implementing this technology in new ways. The penetration of artificial intelligence in the banking sector had been unnoticed and sluggish until the advent of the era of internet banking.
Artificial Intelligence in the Financial IndustriesGerardo Salandra
As Artificial Intelligence makes its way into our lives, many financial institutions are faced with the difficult question “Should AI be embraced?”. While the eagerness to integrate AI into the financial sector has waxed and waned over the past few decades, it now appears that Fintech is ready to dive head-first into AI as a standard for handling customer transactions, financial risk assessment, industry regulatory compliance and reduced institutional costs.
There is no doubt that AI can be invaluable for the financial industry, but it comes at a price. We expect to witness both success stories and tragic failures over the course of the next few years. With any first-generation technology, there are going to be bugs to solve, and a learning curve before intimate industry familiarity with AI is obtained.
AI is not only going to revolutionize the financial industry but become the industry itself.
Artificial Intelligence: a driver of innovation in the Banking Sector - The Italian case
Marco Rotoloni (Head of the research team on banking operations, ABI Lab)
We are all consumers of financial services more or less. We have bank accounts, possibly life insurance, some of us have credit cards, some of us have fixed deposits, some of us may be doing share trading and investment, some of us are borrowers of loans. These are all financial services. Financial Technology or FinTech is a way of delivering or improving the delivery of financial services using technology and innovation.
The use of smartphones and internet to improve the services in banking, investing, lending and borrowing etc are examples of technologies aiming to make financial services more accessible to the people. The use of Artificial intelligence, Machine learning, Blockchain, Cryptocurrency etc are redefining the way we are used to receiving financial services. FinTech is an emerging industry. Startups, established financial institutions as well as technology companies are disrupting this space to replace or enhance the usage of currently existing financial services.
In this video we will restrict ourselves to the usage of AI in FinTech.
We will learn about different areas where FinTech is already serving a great deal.
We will learn about the areas where we look forward to seeing more disruptions and innovations to make financial services more secure and accessible to the general public.
Sameer is a digital strategist focusing on removing friction across Banks, NBFCs, Fintechs and Software providers. He is working with Financial Institutions for establishing their digital strategy in alignment with business strategy. The digital strategy would generate value through increase in digital footprint / revenues / cross-sell. This would also reduce costs through productivity gains, automation and process realignment. Digital initiatives as part of strategy would include loan origination, Cross sell platform, Omnichannel platform, Analytics & AI, Mobility and Fintech tie-ups.
This deck is part of his open innovation approach. This can be used by anyone.
"Digital Banking" by Nikolay Spasov
The presentation was part of the 2016 Digital Marketing Masterclass organized by Interactive Advertising Bureau (IAB) Bulgaria and New Bulgarian University (NBU). The scope of the lecture is to present the current trends in banking and the available technologies that are supporting the industry.
AI powered Decision Making in Banks - How Banks today are using Advanced analytics in credit Decisioning, enhancing customer life time value, lower operating costs and stronger customer acquisition
The Journey to Digital Transformation with Touch BankBackbase
The presentation of Andrei Kozliar, CEO of Touch Bank. In this webinar, Jouk Pleiter, CEO of Backbase, talks to two of the most innovative banks in Europe – Touch Bank and CheBanca!
Digital transformation is about fundamentally changing how banks attract, interact with and satisfy consumers, and it affects all levels of your organisation. Antonio and Andrei will share real-life examples of digital transformation in our new webinar, which will look at:
what was needed to start their digital transformation journeys
the key elements for success.
Antonio Fratta Pasini is Head of CRM and Omni-channel for CheBanca!, the retail bank of Mediobanca Group, the third largest financial services group in Italy. CheBanca! has always been at the forefront of innovation, from flagship futuristic branches to award-winning banking apps such as WOW!
Andrei Kozliar is CEO of Touch Bank, a neobank created by OTP Bank. Founded in 1949, OTP Bank is one of the largest independent financial service providers in Central and Eastern Europe, serving nine countries. Recognizing that today’s digital-savvy customers and emerging digital natives are going to be the fastest growing customer segment, OTP Bank decided to launch a new, digital- and mobile-only bank under the label Touch Bank.
Towards the Next Generation Financial Crimes Platform - How Data, Analytics, ...Molly Alexander
Towards the Next Generation Financial Crimes Platform - How Data, Analytics, & ML Are Transforming the Fight Against Fraud, AML & Cybersecurity -Nadeem Asghar
Digital redefinition of banking banking transformationDraup
The increase in the number of digital use cases in the banking and financial services industry has led to the emergence of newer digital hotspots in the US. States such as Minnesota, North Carolina, Texas, and California have a high density of mature talent specializing in these digital cases. These digital use cases have also given rise to new hotspots in neighbouring states such as Iowa, Arizona, and Ohio. Bank of America, Wells Fargo, and JP Morgan Chase have capitalized on this rapid digitalization to create solutions in anti-money laundering, digital wealth management, information security, cloud technology.
Analysing the Digital Maturity of Top US Banks
The digital maturity of banks and financial institutions has been measured by their competency in innovation which includes their competitive intensity and growth potential and assessing their capabilities in terms of talent scalability and maturity of skills in new age technologies. By these parameters, firms such as Bank of America, Wells Fargo, Citi, and Capital One have identified as digital leaders while Union Bank, First Republic Bank, HSBC US have been relatively slower in the digital race.
Case-by-Case Analysis of Banking Transformation
Bank of America:
Bank of America has over 14 digital centres with over 76% of the digital talent based out of centres located in the US. The 4,000+ digital workforce is involved in functions such as app development, analytics, security, and cloud. Bank of America is one of the few leading banks looking to increase the digital capabilities of all its bank branches through interactive systems that need very little human intervention. Some branches are also fully automated equipped with an interactive teller machine and a video conferencing room.
Citi Group:
Citi is taking cues from its innovation labs that are involved in developing cutting-edge solutions such as beacons. The firm’s 3,500+ digital talent pool is predominantly based out of North America. The bank’s smart branches are equipped with interactive media walls that display local weather, stock information, and financial updates. Citi announced their partnership with Nasdaq which was formed to create payment systems that use DLT (Distributed Ledger Technology) to record payments.
Wells Fargo:
The firm’s large 7,500+ digital workforce is largely consolidated in the United States with sporadic distribution in India as well. The firm has 15 digital centres with only 2 of them located outside the US i.e. in Hyderabad, and Bengaluru. Over 28% of digital talent is involved in new-age solutions such as RPA, Blockchain, IoT and AI.
KYC automation using artificial intelligence (AI)EY
Knowing Your Customer (KYC) is the process of understanding and validating the authenticity of the business’ potential clients and risk that it might impose onto the relationship. KYC solutions enable access to detailed information ensuring the credibility of clients and expediting the client onboarding. KYC solution also automate previously manual processes and reduce repetition, saving time and money for the firm.
The KYC solution streamlines the KYC process by automating the processing of customer data, sorting the data by type and storing it in a data lake. The solution reduces clutter and maintains lean operations by centralizing KYC data for any branch to query from. The solution increases operational efficiency and reduces overhead manpower cost incurred in processing consumer data manually. The time to process a client’s information is reduced from 18 minutes to 1 minute by leveraging on automation.
Find out more at www.ey.com/sg/fintechhub.
For enquiries, contact us via email at fintech@sg.ey.com.
apidays LIVE Singapore - Open Banking: A foundation for the new world by Bhar...apidays
apidays LIVE Singapore - Connected Commerce
Open Banking: A foundation for the new world
Bharat Bhushan, CTO - Banking and Financial Markets, EMEA, Technical Leadership Team, IBM Academy of Technology
Digital lending is quickly growing among the 'thin file' borrowers i.e. the borrowers with no or negligible credit history. These borrowers can be both consumers or businesses.
But, in recent months the digital lenders are struggling with liquidity crises due to the pandemic. As RBI extended loan moratorium to borrowers, the Digital Lenders are in a catch-22 situation. While their borrowers expect them to extend the moratorium, financial institutions they borrow from (Banks and large NBFCs) are either refusing to or delaying to extend the moratorium to the digital lenders. digital lenders Association of India (DLAI) has already approached the RBI to get the moratorium benefits.
It is quite expected that many digital lenders (especially ones with weaker balance sheets) will not survive not only because of the liquidity crisis but also exposure to less creditworthy borrowers who are often small businesses and less creditworthy individuals. The economic repercussions of the lockdown may leave many of the borrowers unable to repay as small businesses shut down and people lose employment.
Although, the lockdowns have caused rapid digital adoption which is beneficial for the industry in the long-term. This indicates that the industry is expected to go through a lot of consolidation as cash strapped players look to be acquired to get some exit.
Let us understand this industry.
BBS-248 Artificial Intelligence (AI) for Financial ServicesOzgur Karakaya
• Artificial Intelligence (AI) general info and the AI world market
• AI in financial sector: services that AI can be applied (Investing, Management, Market Research, Blockchain, Fraud Detection, AI Assistants/Bots, etc.)
• AI firms, products and the tech behind.
Building the 10x better bank, by @joukpleiter & @jelmerdejong
Slides of the November 11, 2015 webinar 'Omni-channel banking & the digital transformation roadmap'.
In this webinar, Jouk Pleiter and Jelmer de Jong of Backbase will talk about building the 10-times-better bank.
The financial services market is going through many changes. New challengers have appeared and are looking for a slice of the market. In addition, customers are more demanding and more informed, expecting convenience and simplicity when it comes to financial services, particularly online and via mobile devices. People love digital services such as Netflix, Amazon, and Uber because they’re easy to use and deliver great customer experiences. They deliver 10 times more convenience and better customer experiences than the status quo, and are therefore winning the market. It’s only a matter of time before the 10-times-better bank is founded, a thought that's on the radar of every banker.
In this webinar, we outline the journey of creating the 10-times-better bank, providing a detailed analysis of how banks can begin their digital journey, with a strong focus on five main points:
1) new competitors in banking: the disrupters
2) customer experience: the key ingredients
3) omni-channel and the changing channel mix
4) mobile's impact on online sales and share of wallet
5) regaining control in the era of digitization
Consumers are looking for more than just banking and machine learning helps banks deliver that.
Machine learning contributes to areas such as credit decisions, risk management, personalized customer experiences, fraud detection, automation and much more.
This PDF will address the following points:
1. An overview of the banking sector and its importance in the economy
2. The top 5 banks in the US benefiting from the power of machine learning
3. The areas in banking where Machine Learning is applied
I delivered a talk on application of Artificial Intelligence in Fintech to the visiting students of University of Applied Sciences, Wurzburg-Schweinfurt, Germany at Christ University
Today's customers are fundamentally different from customers of past years as they are harder to acquire, retain, and delight because of the explosion in digital technologies consumers use day to day. New digital experiences are forcing banks to play catch-up and match the innovative and engaging interactions and products — such as mobile payments — that non-banks are offering to those same customers. This IDC research, sponsored by TCS Digital Software & Solutions Group, revealed three key themes for digital transformation in the banking industry.
Use of Articificial Intelligence and technologies in providing financial services is what fintech does. Whether it is Payment gateway, insurance, banking, lending, stock trading, taxes.
How Fintech evolved over the years in the World and Indian Economy.
Indian Fintech Companies under different categories
Common Fintech practices adopted by Fintech Companies with better flexibility, convenience and accessibile financial products and services
Enabling digital business with governed data lakeKaran Sachdeva
Digital business is enabled by Artificial intelligence, Machine learning, and data science. Artificial intelligence and machine learning are dependent on right Information architecture and data foundation. Governed data lake infused with governance and data science platform gives you the power to take the organization in the digital transformation and AI journey.
Sameer is a digital strategist focusing on removing friction across Banks, NBFCs, Fintechs and Software providers. He is working with Financial Institutions for establishing their digital strategy in alignment with business strategy. The digital strategy would generate value through increase in digital footprint / revenues / cross-sell. This would also reduce costs through productivity gains, automation and process realignment. Digital initiatives as part of strategy would include loan origination, Cross sell platform, Omnichannel platform, Analytics & AI, Mobility and Fintech tie-ups.
This deck is part of his open innovation approach. This can be used by anyone.
"Digital Banking" by Nikolay Spasov
The presentation was part of the 2016 Digital Marketing Masterclass organized by Interactive Advertising Bureau (IAB) Bulgaria and New Bulgarian University (NBU). The scope of the lecture is to present the current trends in banking and the available technologies that are supporting the industry.
AI powered Decision Making in Banks - How Banks today are using Advanced analytics in credit Decisioning, enhancing customer life time value, lower operating costs and stronger customer acquisition
The Journey to Digital Transformation with Touch BankBackbase
The presentation of Andrei Kozliar, CEO of Touch Bank. In this webinar, Jouk Pleiter, CEO of Backbase, talks to two of the most innovative banks in Europe – Touch Bank and CheBanca!
Digital transformation is about fundamentally changing how banks attract, interact with and satisfy consumers, and it affects all levels of your organisation. Antonio and Andrei will share real-life examples of digital transformation in our new webinar, which will look at:
what was needed to start their digital transformation journeys
the key elements for success.
Antonio Fratta Pasini is Head of CRM and Omni-channel for CheBanca!, the retail bank of Mediobanca Group, the third largest financial services group in Italy. CheBanca! has always been at the forefront of innovation, from flagship futuristic branches to award-winning banking apps such as WOW!
Andrei Kozliar is CEO of Touch Bank, a neobank created by OTP Bank. Founded in 1949, OTP Bank is one of the largest independent financial service providers in Central and Eastern Europe, serving nine countries. Recognizing that today’s digital-savvy customers and emerging digital natives are going to be the fastest growing customer segment, OTP Bank decided to launch a new, digital- and mobile-only bank under the label Touch Bank.
Towards the Next Generation Financial Crimes Platform - How Data, Analytics, ...Molly Alexander
Towards the Next Generation Financial Crimes Platform - How Data, Analytics, & ML Are Transforming the Fight Against Fraud, AML & Cybersecurity -Nadeem Asghar
Digital redefinition of banking banking transformationDraup
The increase in the number of digital use cases in the banking and financial services industry has led to the emergence of newer digital hotspots in the US. States such as Minnesota, North Carolina, Texas, and California have a high density of mature talent specializing in these digital cases. These digital use cases have also given rise to new hotspots in neighbouring states such as Iowa, Arizona, and Ohio. Bank of America, Wells Fargo, and JP Morgan Chase have capitalized on this rapid digitalization to create solutions in anti-money laundering, digital wealth management, information security, cloud technology.
Analysing the Digital Maturity of Top US Banks
The digital maturity of banks and financial institutions has been measured by their competency in innovation which includes their competitive intensity and growth potential and assessing their capabilities in terms of talent scalability and maturity of skills in new age technologies. By these parameters, firms such as Bank of America, Wells Fargo, Citi, and Capital One have identified as digital leaders while Union Bank, First Republic Bank, HSBC US have been relatively slower in the digital race.
Case-by-Case Analysis of Banking Transformation
Bank of America:
Bank of America has over 14 digital centres with over 76% of the digital talent based out of centres located in the US. The 4,000+ digital workforce is involved in functions such as app development, analytics, security, and cloud. Bank of America is one of the few leading banks looking to increase the digital capabilities of all its bank branches through interactive systems that need very little human intervention. Some branches are also fully automated equipped with an interactive teller machine and a video conferencing room.
Citi Group:
Citi is taking cues from its innovation labs that are involved in developing cutting-edge solutions such as beacons. The firm’s 3,500+ digital talent pool is predominantly based out of North America. The bank’s smart branches are equipped with interactive media walls that display local weather, stock information, and financial updates. Citi announced their partnership with Nasdaq which was formed to create payment systems that use DLT (Distributed Ledger Technology) to record payments.
Wells Fargo:
The firm’s large 7,500+ digital workforce is largely consolidated in the United States with sporadic distribution in India as well. The firm has 15 digital centres with only 2 of them located outside the US i.e. in Hyderabad, and Bengaluru. Over 28% of digital talent is involved in new-age solutions such as RPA, Blockchain, IoT and AI.
KYC automation using artificial intelligence (AI)EY
Knowing Your Customer (KYC) is the process of understanding and validating the authenticity of the business’ potential clients and risk that it might impose onto the relationship. KYC solutions enable access to detailed information ensuring the credibility of clients and expediting the client onboarding. KYC solution also automate previously manual processes and reduce repetition, saving time and money for the firm.
The KYC solution streamlines the KYC process by automating the processing of customer data, sorting the data by type and storing it in a data lake. The solution reduces clutter and maintains lean operations by centralizing KYC data for any branch to query from. The solution increases operational efficiency and reduces overhead manpower cost incurred in processing consumer data manually. The time to process a client’s information is reduced from 18 minutes to 1 minute by leveraging on automation.
Find out more at www.ey.com/sg/fintechhub.
For enquiries, contact us via email at fintech@sg.ey.com.
apidays LIVE Singapore - Open Banking: A foundation for the new world by Bhar...apidays
apidays LIVE Singapore - Connected Commerce
Open Banking: A foundation for the new world
Bharat Bhushan, CTO - Banking and Financial Markets, EMEA, Technical Leadership Team, IBM Academy of Technology
Digital lending is quickly growing among the 'thin file' borrowers i.e. the borrowers with no or negligible credit history. These borrowers can be both consumers or businesses.
But, in recent months the digital lenders are struggling with liquidity crises due to the pandemic. As RBI extended loan moratorium to borrowers, the Digital Lenders are in a catch-22 situation. While their borrowers expect them to extend the moratorium, financial institutions they borrow from (Banks and large NBFCs) are either refusing to or delaying to extend the moratorium to the digital lenders. digital lenders Association of India (DLAI) has already approached the RBI to get the moratorium benefits.
It is quite expected that many digital lenders (especially ones with weaker balance sheets) will not survive not only because of the liquidity crisis but also exposure to less creditworthy borrowers who are often small businesses and less creditworthy individuals. The economic repercussions of the lockdown may leave many of the borrowers unable to repay as small businesses shut down and people lose employment.
Although, the lockdowns have caused rapid digital adoption which is beneficial for the industry in the long-term. This indicates that the industry is expected to go through a lot of consolidation as cash strapped players look to be acquired to get some exit.
Let us understand this industry.
BBS-248 Artificial Intelligence (AI) for Financial ServicesOzgur Karakaya
• Artificial Intelligence (AI) general info and the AI world market
• AI in financial sector: services that AI can be applied (Investing, Management, Market Research, Blockchain, Fraud Detection, AI Assistants/Bots, etc.)
• AI firms, products and the tech behind.
Building the 10x better bank, by @joukpleiter & @jelmerdejong
Slides of the November 11, 2015 webinar 'Omni-channel banking & the digital transformation roadmap'.
In this webinar, Jouk Pleiter and Jelmer de Jong of Backbase will talk about building the 10-times-better bank.
The financial services market is going through many changes. New challengers have appeared and are looking for a slice of the market. In addition, customers are more demanding and more informed, expecting convenience and simplicity when it comes to financial services, particularly online and via mobile devices. People love digital services such as Netflix, Amazon, and Uber because they’re easy to use and deliver great customer experiences. They deliver 10 times more convenience and better customer experiences than the status quo, and are therefore winning the market. It’s only a matter of time before the 10-times-better bank is founded, a thought that's on the radar of every banker.
In this webinar, we outline the journey of creating the 10-times-better bank, providing a detailed analysis of how banks can begin their digital journey, with a strong focus on five main points:
1) new competitors in banking: the disrupters
2) customer experience: the key ingredients
3) omni-channel and the changing channel mix
4) mobile's impact on online sales and share of wallet
5) regaining control in the era of digitization
Consumers are looking for more than just banking and machine learning helps banks deliver that.
Machine learning contributes to areas such as credit decisions, risk management, personalized customer experiences, fraud detection, automation and much more.
This PDF will address the following points:
1. An overview of the banking sector and its importance in the economy
2. The top 5 banks in the US benefiting from the power of machine learning
3. The areas in banking where Machine Learning is applied
I delivered a talk on application of Artificial Intelligence in Fintech to the visiting students of University of Applied Sciences, Wurzburg-Schweinfurt, Germany at Christ University
Today's customers are fundamentally different from customers of past years as they are harder to acquire, retain, and delight because of the explosion in digital technologies consumers use day to day. New digital experiences are forcing banks to play catch-up and match the innovative and engaging interactions and products — such as mobile payments — that non-banks are offering to those same customers. This IDC research, sponsored by TCS Digital Software & Solutions Group, revealed three key themes for digital transformation in the banking industry.
Use of Articificial Intelligence and technologies in providing financial services is what fintech does. Whether it is Payment gateway, insurance, banking, lending, stock trading, taxes.
How Fintech evolved over the years in the World and Indian Economy.
Indian Fintech Companies under different categories
Common Fintech practices adopted by Fintech Companies with better flexibility, convenience and accessibile financial products and services
Enabling digital business with governed data lakeKaran Sachdeva
Digital business is enabled by Artificial intelligence, Machine learning, and data science. Artificial intelligence and machine learning are dependent on right Information architecture and data foundation. Governed data lake infused with governance and data science platform gives you the power to take the organization in the digital transformation and AI journey.
Enterprises are faced by information overload. Big data appears as an opportunity, but has no relevance until enterprises can put it in context of their activities, processes, and organizations, Applying MDM principles to Big Data is therefore an opportunity that enterprises should target.
This presentation covers the following topics :
- what is MDM and Information Management
- what is Big Data and what are the use cases
- why and how Big Data can take advantage of MDM ? why and how MDM can take advantage of Big Data ?
Fortify Your Enterprise with IBM Smarter Counter-Fraud SolutionsPerficient, Inc.
Organizations lose an estimated five percent of annual revenues to fraud, totaling nearly $1 trillion in the U.S. alone. Cyber criminals are more organized and better equipped than ever, and continue to evolve their strategies in order to undermine even the strongest protections.
We continue to hear about major security breaches across all industries, but what is being done to fix the problem? There must be a tight interlock between risk, security, fraud and financial crimes management. Current solutions are proving inadequate as point solutions and a corporate silo mentality directly contribute to the risk of fraudulent activities going undetected.
Our webinar covered:
-How IBM’s Smarter Counter Fraud initiative can help public and private organizations prevent, identify and investigate fraudulent activities
-Real-world use cases including how one financial institution stopped $1M in fraud in the first week after implementing a counter-fraud solution
-Perficient’s multi-tiered approach to help guide successful business outcomes
It’s time to stop the bad guys with IBM Smarter Counter Fraud and Perficient – learn how now!
A Pre-Built Customer Intelligence Management System
AllSight empowers your customer-facing employees to create exceptional customer experiences. AllSight is different than your existing systems.
It manages an evolving likeness of your customer. It investigates every possible source of customer data. And it generates deep customer intelligence through analytics. It delivers that intelligence to your customer-facing employees through their existing applications or via its customer intelligence dashboard.
Learn more by reading our FREE white paper on Customer Intelligence Management and the new era of Customer 360.
A pre-built Customer Intelligence Management system.
AllSight empowers your customer-facing employees to create exceptional customer experiences. AllSight is different than your existing systems.
It manages an evolving likeness of your customer. It investigates every possible source of customer data. And it generates deep customer intelligence through analytics. It delivers that intelligence to your customer-facing employees through their existing applications or via its customer intelligence dashboard.
Learn more by reading our FREE white paper on Customer Intelligence Management and the new era of Customer 360.
As the internet has expanded and criminals have found more ways of creating revenue from stolen information, the need for digital threat intelligence management (DTIM) has increased. Without a means of early identification, companies that are being targeted have no way of knowing their customer’s or employee’s security is threatened or that their brand is being stolen, resulting in an erosion of reputation. DTIM is the early warning system to aid those organizations in identifying the infringements and thefts before severe damage is done.
These slides--based on the webinar from leading IT analyst firm Enterprise Management Associates (EMA) and RiskIQ -- highlight why DTIM is a growing necessity for mid- and large-sized organizations.
Speaker: Vince Leat, Industry Consulting Executive, Teradata
Large enterprises need a partner who has done it before. Teradata has successfully implemented AI across multiple industries, proving the technology as well as producing material business outcomes. Teradata continues to channel IP from successful, field-based AI client engagements into accelerators that lead to faster time to value and reduce the risk of custom AI initiatives. Hear how Teradata helps customers build opportunities derived from AI.
Digitalization: A Challenge and An Opportunity for BanksJérôme Kehrli
Today’s banking industry era is strongly defined by a word - digital. The urgency to act is only getting severe each day. Banks using digital technologies to automate processes, improve regulatory compliance, and transform the customer experience may realize a profit upside of 40% or more, while laggards that resist digital innovation will be punished by customers, financial markets, regulators, and may see up to 35% of net profit eroded, according to a McKinsey analysis.
The vital question to answer is, do we get digitalization right? Why is it getting extremely urgent to digitize?
This document contains a brief on Blue Bricks' 3 products - Service Guard, XPAT 2.0 and Axiom Protect. Please do have a read and we look forward to hearing from you.
The customer journey could essentially be divided into 7 elements. We’ll touch upon the issue of ‘Privacy’ and how one balance social and commercial value. Practical examples of
customer analytics at its best will be discussed as well as the importance of the eco-system.
Similar to Artificial Intelligence and Digital Banking - What about fraud prevention ? (20)
Introduction to Modern Software ArchitectureJérôme Kehrli
This talk offers an introduction to software architecture with a modern perspective. We will consider a new way to identify architectural elements and walk through some examples of modern architectures, the NoSQL world, Big Data architectures and micro-services.
A proposed framework for Agile Roadmap Design and MaintenanceJérôme Kehrli
Maintaining a relevant and meaningful roadmap while adopting a state of the art Agile methodology is challenging and somewhat antonymous.
This presentation proposes a framework for designing and maintaining an Agile Roadmap.
A presentation of the search for Product-Market Fit with the principles, practices and processes that lead to it, from the Lean-Startup and Design Thinking perspective
From Product Vision to Story Map - Lean / Agile Product shapingJérôme Kehrli
A lot of Software Engineering projects fail for a lack of shared vision due to poor communication among people involved in the project.
A sound maintenance of the product backlog can only be achieved if all the people have a good understanding of what they have to do (common vision).
Roman Pichler, in a post originally written in Jul 16 2012, has proposed a really interesting approach: use various canvas to create and share product vision and product backlog creation and refinement.
This presentation is a drive through these various boards and canvas that should be designed in prior to any product development: the Product Vision, the Lean Canvas, The Product Definition and the Story Map.
Introduction to NetGuardians' Big Data Software StackJérôme Kehrli
NetGuardians is executing it's Big Data Analytics Platform on three key Big Data components underneath: ElasticSearch, Apache Mesos and Apache Spark. This is a presentation of the behaviour of this software stack.
Periodic Table of Agile Principles and PracticesJérôme Kehrli
Recently I fell by chance on the Periodic Table of the Elements... Long time no see... Remembering my physics lessons in University, I always loved that table. I remembered spending hours understanding the layout and admiring the beauty of its natural simplicity.
So I had the idea of trying the same layout, not the same approach since both are not comparable, really only the same layout for Agile Principles and Practices.
The result is in this presentation: The Periodic Table of Agile Principles and Practices:
Agility and planning : tools and processesJérôme Kehrli
In this presentation, I intend to present the fundamentals, the roles, the processes, the rituals and the values that I believe a team would need to embrace to achieve success down the line in Agile Software Development Management - Product Management, Team Management and Project Management - with the ultimate goal of making planning and forecasting as simple and efficient as it can be.
Bytecode manipulation with Javassist for fun and profitJérôme Kehrli
Java bytecode is the form of instructions that the JVM executes.
A Java programmer, normally, does not need to be aware of how Java bytecode works.
Understanding the bytecode, however, is essential to the areas of tooling and program analysis, where the applications can modify the bytecode to adjust the behavior according to the application's domain. Profilers, mocking tools, AOP, ORM frameworks, IoC Containers, boilerplate code generators, etc. require to understand Java bytecode thoroughly and come up with means of manipulating it at runtime.
Each and every of these advanced features of what is nowadays standard approaches when programming with Java require a sound understanding of the Java bytecode, not to mention completely new languages running on the JVM such as Scala or Clojure.
Bytecode manipulation is not easy though ... except with Javassist.
Of all the libraries and tools providing advanced bytecode manipulation features, Javassist is the easiest to use and the quickest to master. It takes a few minutes to every initiated Java developer to understand and be able to use Javassist efficiently. And mastering bytecode manipulation, opens a whole new world of approaches and possibilities.
DevOps is a methodology capturing the practices adopted from the very start by the web giants who had a unique opportunity as well as a strong requirement to invent new ways of working due to the very nature of their business: the need to evolve their systems at an unprecedented pace as well as extend them and their business sometimes on a daily basis.
While DevOps makes obviously a critical sense for startups, I believe that the big corporations with large and old-fashioned IT departments are actually the ones that can benefit the most from adopting these principles and practices.
Some years ago, Eric Ries, Steve Blank and others initiated The Lean Startup movement. The Lean Startup is a movement, an inspiration, a set of principles and practices that any entrepreneur initiating a startup would be well advised to follow.
Projecting myself into it, I think that if I had read Ries' book before, or even better Blank's book, I would maybe own my own company today, around AirXCell or another product, instead of being disgusted and honestly not considering it for the near future.
In addition to giving a pretty important set of principles when it comes to creating and running a startup, The Lean Startup also implies an extended set of Engineering practices, especially software engineering practices.
Smart Contracts are a central component to next-generation blockchain platforms. Blockchain technology is much broader than just bitcoin. The sustained levels of robust security achieved by public cryptocurrencies have demonstrated to the world that this new wave of blockchain technologies can provide efficiencies and intangible technological benefits very similar to what the internet has done.
Blockchains are a very powerful technology, capable of going much further than only "simple" financial transaction; a technology capable of performing complex operations, capable of understanding much more than just how many bitcoins one currently has in his digital wallet.
This is where the idea of Smart Contracts come in. Smart Contracts are in the process of becoming a cornerstone for enterprise blockchain applications and will likely become one of the pillars of blockchain technology.
In this presentation, we will explore what a smart contract is, how it works, and how it is being used.
The Blockchain - The Technology behind Bitcoin Jérôme Kehrli
The blockchain and blockchain related topics are becoming increasingly discussed and studied nowadays. There is not one single day where I don't hear about it, that being on linkedin or elsewhere.
I interested myself deeply in the blockchain topic recently and this is the first article of a coming whole serie around the blockchain.
This presentation is an introduction to the blockchain, presents what it is in the light of its initial deployment in the Bitcoin project as well as all technical details and architecture concerns behind it.
We won't focus here on business applications aside from what is required to present the blockchain purpose, more concrete business applications and evolutions will be the topic of another presentation I'll post in a few weeks
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Artificial intelligence for banking fraud prevention
How it takes its root in the digitalisation ways
How it impacts customer experience
Legitimacy
Software Editor / Yverdon / 2 former students
Big Data Analytics - banking institutions - fraud prevention
Founded 2018 – long incubation – developing 2012
Figures
Sales Turnover
Only 8 years
A revolution in society / economy – 3rd industrial revolution
Iphone revolution our society
connection : we have a device connecting us to others and to services 24/7, but not only ( … Windows mobile)
User Experience : one click to reach key services and experiences
This interconnection has been key for many things:
Social network rise : symbiotic relation between smartphones and facebook ( )
Many other phenomenas
Consequence:
Millenials , GenXers : almost born with an iphone1) immediacy, 2) all about me myself and I (egocentricity / individualization) 3) Service : when I want, where I want, how I want
Change of Use / change of habits / change of behaviours => digitalization of society
difitalization of corporations and services (Uber, Netflix, Amazon, Paypal)
Yesterday – in 2008, we were amazed by the first smartphones.
Today they have almost become a part of ourselves. We cannot go without them anymore.
Nowadays, new technologies emerge first in the consummer market and then spread into business. New solutions emerge every month and corporations cannot keep up the pace.
This new reality has a name : it’s the consumerization.
.. Cray / iphone
-- 10’000 times more powerfull (1M computer moon)
People are used to be connected all the time, with highly efficient devices on highly responsive services, everywhere and for every possible need.
Today over 4 billion people are interconnected and exchange data, everywhere, all the time ,and for every possible need
Is it the biggest invention of the decade ? Likely, but the previous decade, not the current one.
The real revolution that is coming is the Internet of Things …
Tomorrow, in a few years, Gartner: over 40 billion objects will be interconnected, all the time, everywhere and for every possible need
Another story …
I cannot stress enough how much this is important and what it means in terms of change of society.
Today, we are inter-connected on different kind of medias, during a continuous time and for every possible need.This has become a part of the human behaviour.In a few years the majority of the workforce will be composed by millenials, by people almost born with an iphone.
In 2018, over 4 billion people are connected all the time, everywhere and for every kind of needs.
Again:
Change of Use / change of habits / change of behaviours => digitalization of society
digitalization of corporation and services
…
Mbank … (TODO recover from octo)
Challenges : change of use / change of behaviours / change of means force banking institiutions to adapt !
Overview of the challenges on 6 dimensions
Competitiveness
Think comparison web sites (comparis) / drop of everything not understood in 2 mins / all about me myself and I
Customer satisfaction
RDV amag / shopping 24/ 7 when I want, where I want and how I want
promise 0.5% mortgage interest / never applies / devastating impact …
Customer centricity
put customer back in the center of the preoccupations : meet him / inspire needs to him / listen to him
Marketing and branding
it’s all about reputation and innovation
consider the customer channels (mobile phones, youtube, social networks) and not the usual channels
Operational efficiency
Reduce costs, reduce delays, automated, digitalize
Risk management / mitigation
new channels : attack surface increase
more risks better risk mitigation techniques
audit / internal control : continuous, comprehensive, automated, real-time
fraud costs explodes
IMHO the most important challenges banks are facing with the digitalization and the changes of use and behaviours.
Happily, new technologies and these changes also offer opportunities
What are these opportunities on the same 6 dimensions
Competitiveness
Digital products are naturally simpler
Big Data analytics and AI enables to build
Customer satisfaction
A chatbot or an assistant app never sleeps, unlike a branch umployee
In an online world, positioning products and pricing is natural
Customer centricity
Getting online and digital with today technologies is not difficult
Technology give banks a chance to meet the customer and set themselves apart in the industry
Big Data analytics enables banks to understand customer needs and trends in an unprecedented way
Marketing and branding
Again, it’s all about innovation and reputation
The digital world offers unprecedented opportunities to convince a potential customer to buy a product : thin of try and buy, sandboxes, universality of channels
Operational efficiency
Technology is an enabled to process automation, dematerialization and digitalization
AI Analytics offer a brand new world of business and financial insights
Risk mitigation
Big Data Analytics and new UI technologies : dashboards, data visualization, real-time KPIs and KRIs
Artificial intelligence for fraud prevention
Real-time is never been so close
Conclusion : just as technology initiates change of behaviour and uses that challenges banking institutions, technology also offers unprecendented opportunities to catch up with these challenges
AI is the next step towards meeting these challenges and benefiting from the opportunities of the technology
- Show a set of initiatives in these regards
AI make banks smarter.
AI leads to better customer intelligence and thus a better customer experience—a key to increasing profit.
Examples:
AI learns the behaviors of market participants learn how markets behave enable better risk assessments
AI improve banks’ customer service in several ways – me and my banker (takes him huge time) – AI in no time and where, how, when I want
3 ways
Customer Experience revolution : when putting technology in direct contact with the customer (we’ll see examples)
AI analytics : improve operational efficiency in various domains (investment research, credit scoring) or provide personalized advisory to customers (we’ll see examples)
Risk mitigation : better fraud detection, as far as fraud prevention, more efficient AML controls, more efficient compliance controls, etc.
Let’s see some examples.
Note : worried 2 years ago when writing slides => banks caught up => AI has been key
Voice Assisted Banking
Physical presence is fading - technology empowers customers to use banking services -> voice commands and touch screens.
Natural language processing technology answer questions, find information, and connect users with various banking services educes human error, systemizing the efficiency.
Barclay : voice chatbot
VNLP : customers talk to a device and get information they need for vital transactions.
ML model the characteristics of the customer—for example, incomes and typical investments—and predict their preferred investment behavior and interests such as stock choices.
ML run in background, VNLP gives advices
RBS – chatbot luvo Luvo is a NLP AI bot which will answer customer's questions and perform simple banking tasks like money transfers. If Luvo is unable to find the answer it will pass a customer over to a member of staff.Not only advises but performs simple tasks.
BoA - Chatbot Erica
ML and predictive analytics to provide financial guidance. Erica can also help customers with simple transactions such as checking account status or simple payments.Also voice (NLP and VNLP)
Goive sparing and investment advices.
Challenged addressed by these initiatives
Opportunities actionned by these
Realtime Big Data processing with Machine Learning : provide personalised, value-added products to customers as it learns about spending habits or investment profiles.
Data-driven AI applications for financial decisions : advice, calculations, scoring and forecasts, for the bank or for the customers
RBS : automated lending process
approve commercial real estate loans up to $2.7 million—a process that normally takes days—in less than 45 minutes. The 2017 AI-driven launch is part of the bank’s broader digital and innovation agenda.
UBS "virtual research agents " that can perform investment research to near-human levels.imitate the quality of an investment analyst.
screen through market data, through SEC filings and do a company valuation with all of the inputs that a human analyst would use
UBS SmartWealth
ask customers a set of questions so that a machine-learning algorithm can assign them a risk category and invest their money in a specific and portfoliobring the fees attached to investing down to attract more customers into the bank smaller customers that would not be worth it for an asset manager chatbots … mimic what an asset manager provide to HNWI – private banking for retail customers
Fraud detection / AML - advanced significantly due to improvements in artificial intelligence.
Companies like MasterCard and Visa have been using AI to detect fraudulent transaction patterns for several years now.
react proactively and inform the customer.
Transaction analytics but also behaviour analysis (suspicious behaviour, not only transactions / ZugKB)
Lloyd …
HSBC has also been working with the London-based big data startup Quantexa to help the bank spot potential money laundering activity.HSBC has been piloting the technology since 2017, which uses AI techniques to analyse internal, publicly available, and transactional data within a customer’s wider network to spot rogue behaviour. It is now integrating Quantexa technology into its systems this year.
NetGuardians …
My conclusion on the intiatives I have been mentionning today
We have seen some examples if initiatives and the challenges they address as well as the opportunities they activates
AI is key to addressethe challenges of the digitalisation
AI is the state of the art, the bleeding edge of the opportunities coming from the digitalizatiin
AI enables to go faster, further, stronger in the digital transformation
Would want to speak present more in details what we do at NetGuardians et and how it impacts customer experience
In February 2016, a group that we deem around 20 persons, composed by financial experts, software engineers and hackers have attacked the information system of the Bangladesh Central Bank.
They manage to compromise the bank internal gateway to the SWIFT Network. The SWIFT network is the international banking messaging network used by banks to communicate and transfer money through electronic wire.
The pirates used the SWIFT network to withdraw money from the Bangladesh Central bank VOSTRO account by the US Federal Reserve.
They manage to transfer 81 millions USD to the Philippines and used the Philippino casinos to launder the stolen funds.
As a sidenote, the fact that they have stolen “only” 81 million USD is an amazing luck for the bank, or rather an amazing bad luck for the cybercriminals.
An Anti-Money laundering system – rule-based - deployed in the US federal Reserve blocked the 6th transaction because the beneficiary name contained the word “Jupiter”. Jupiter was on a sanction screening list in the US because a cargo ship navigating under Iranian flag is called “Jupiter” something. The 6th transaction being blocked, all the further ones, around thirty, have been blocked as well.
But 5 transactions pass through before the 6th has been blocked by the Fed and went further through the correspondent banking network
Another transaction has been blocked by the Deutsche Bank, a routing bank, because of a typo “ Shilka Fandation” instead of “Shilka Fundation”
So only 4 transactions our of 35 successfully arrived to the Philippines and as such the total loss have been reduces from 951 million USD initially intended to “only” 81 millions USD
The Retefe worm is a worm developed by a team of cybercriminals targeting specifically the ebanking platforms of small and mid size Austrian And Swiss Banking Institutions
The worm is used by the thieves to take control of the victim’s ebanking sessions and to submit fraudulent transactions to the system
This worm is 4 years old
For 4 years, fraudsters keep on updating it, modifying it and extending it to counter the anti-viruses software and the specific protections put in place by the banks.
This worm is 4 years old and nevertheless, as pointed out by the Computer security section of the federal finance department, it is still making today between 10 and 90 victims in Switzerland and Austria,
Today, in the swiss banks …
My conclusion from these examples is as follows:
Today, fraudsters and cybercriminals are professionals
The time when fraud was coming from a little hacker working in his garage or a back-office employee disappointed by his bonus, is over.
Today, attackers are professionals who have industrialized their methods
In the second half of the 2000’s, however, the costs linked to fraud, increasingly external, the complexity of attacks and the maturity of attackers rise.
Banking institutions react by deploying quite massively and for the first time specific analytics systems aimed at detecting banking fraud, both external and internal.
At this time, these systems are rules-engines that work by checking or searching pre-defined and well defined conditions within the data extracted from the information system.
In a way these systems can be considered as simple extensions of the security checks and rules implementing directly within the operational information system.
The solutions come most of the time from the AML – Anti Money Laundering – World, their editors having understood that banking fraud was a way to extend their sales
A very simple rule example is show at the bottom of this slide.
At this time, a first set of papers have already been published on the success, still somewhat relative in this early days, of some Machine Learning approaches implemented towards banking fraud detection.
But Machine Learning and Artificial Intelligence are considered with a lot of condescension and skepticism.
Bankers and their engineers are not willing to consider an approach whose interpretation of results is deemed fuzzy.
NetGuardians has been built at these times and the NetGuardians platform could be seen as a gigantic rule engine,.
Unfortunately, the reality of fraud and financial cybercrime evolved fast and dramatically.
Let me give you two examples
Artificial Intelligence provides the solution to this problem
In 2016, we started at NetGuardians to integrate the first advanced algorithms, so called Machine Learning algorithms, in our systems.
We let an Artificial Intelligence analyze continuously the history of billions of transactions in the system and learn about individuals habits and behaviours.
With big data technologies, AI can analyze a very extended depth of history and build dynamic profiles for each and every individual related to a financial transactions.
Individuals are both Customer and Users (Internal Employees)
Profiling customers is required for both Internal and External Fraud.
Profiling users is required for Internal Fraud.
Big Data technologies are key to maintain these profiles up-to-date in real time by tracking each and every interaction between the user and the bank systems
In addition to a financial transaction direct characteristics such as the beneficiary, the target bank country, the amount of the transaction, its currency, etc., the machine can correlate a lot of indirect characteristics, such as where in the world was located the ATM where the user withdrawn money from, where was he connected to his ebanking session, etc.
For each and every individual a dynamic and up to date profile captures his behaviour and his habits
Then, each and every financial transaction, regardless of its type, it being a security trade order, an ATM withdrawal or an ebanking payment, is compared against the user profile and a risk score is computed.
Based on this risk score, the machine eventually decides whether the transactions is genuine or not and whether it requires further investigation by a human analyst within the bank.
The machine can look at the big picture and analyze transactions at a broader scale.
Recall the Audi example. When such a transaction is very unusual for a specific customer, looking at other customers with similar conditions, habits and behaviour is required.
And here again AI comes in help.
AI can analyze behaviours and habits of customers and group together the people with same patterns. People that are the same age, same wealth level, same origins or same … will have a strong tendency to behave the same: for instance drive the same kind of car, such as an Audi, live in a flats of the same size, pay the same amount of telephone bills at the end of the month, etc.
The machine can analyze customer activities and transactions on the large scale and cluster together customers with same behaviour.
Then, these groups can be profiled just as individuals.
And finally, a transaction can be scored against the customer group profile in addition to the customer profile.
Recalling the Audi example. When scoring this specific payment against the individual profile, the transaction will be flagged as suspicious.
Scoring it against the group profile will clearly indicate that it’s a genuine transaction. People buy new Audis every day, especially in Switzerland
[On blank page]
Let me give you a simple example of what I mean by analyzing a customer’s interaction with the banking Information system.
The interactions of a customer with the ebanking application is the simplest example I can come up with.
[Page down on Genuine User]
Imagine the situation of a genuine user of the ebanking platform whose behaviour when inputting is payments is always the same
He logs in the ebanking platform
He looks at his account balance
He performed all his payment, from input to validation, many of them
He checks his pending orders, making sure he missed none of them
He logs out the platform
[Page Down on Worm]
Now if a worm hijacks the ebanking session, the worm will do none of that
The worm will likely go directly from login to payment input, validation to logout
Here I am only showing transitions but one can also consider User think time, keyboard stroke speed, etc.
[Page Down on principle]
AI can analyze all this behaviour and activity tails a user or customer leaves on the banking information systems and build a model capturing this behaviour
Then, when an individual action is performed, the machine can compute the likelihood of that action to be performed by a legitimate user or an attacker based on the past activity.
And here as well, AI can build profiles of this activities and their likelihood both at individual level and group level through clustering techniques.
…
NetGuardians digitalizes and improves Fraud detection
Sysmosoft digitalizes the call-back
A breakthrough : not only we reduce the amount of hits, i.e. the amount of confirmations asked to customers, but we automate the handling of these reconfirmations and customer call-back.
For the customer: a reconfirmation call-back is received a few minutes after the transaction is input
- confidence / reputation /
- ease of re-confirmation – one fingerprint (strong authentication)
…
In the future, the callback will increasingly be handled by chatbots and robots
Just answer a few questions
Validate or reject the transaction
CONCLUSION
NetGuardians makes fraud prevention enter the digital era :
+ fully digitalized and automated process / No more human intervention
+ AI / Big Data
- Customer experience impacts
+ Seamless user experience for reconfirmation
+ indirect but essential : protecting the customer assets
+ protecting the banking institution reputation and brand
- I would like to conclude my presentation on the netx slide
Banks are embracing AI / more and more initiatives / finally catching up with fintechs (acquisition …)
Implement AI to replicate user experience seen in eCommerce and uber, netflix, etc.
Amazons and Uber aren’t suffering from regulatory pressure …
Regardles s– innovative spirit and digital mindset first class user experience within a regulated environment
3 ways to leverage power of AI
Millenials and GenXers willing to share personnal information in exchnage for a more customized, streamlined service (unlike baby boomers)All “about me myself and I”, “where I want, when I want, how I want” meet the customer (channels) / personalized service / recommendations (don’t‘ like searching)
Few banks have the resource of BoA or UBSFirst dig into cost-saving applications (Operational efficiency [automate, digitalize internal processes], risk mitigation [NG]). Then use these savings to invest on more interesting applications (CX / UX)
Wells-fagro : Ai Enterprise Solution Team ! – connect bank staff with AI experts / brainstorm on applications !
Last worls : a few years ago I was convinced that this schema would be the truth in the coming 10 years…Today I am less pessimistic – many initiatives in bank in regards to digitalization and CX – THANKS TO AI !!!