Fraud Prevention Systems

Retail Banking Fraud - Market Overview

• Retail banking fraud encompasses Application level fraud and transactional level fraud
• Application fraud comprises fraud committed at the application stage across account opening, and secured and unsecured credit product applications whereas transactional fraud refers to that occurring during transactions such as account takeover and payments
• While technologies in POS like EMV (chip, tokenization and encryption) have decreased transactional fraud losses, application fraud is still a major issue in the banking space
• Though there are many players in the fraud detection software space, the supplier base is still low for retail banking due to greater regulation and requirement of access to consortium data (across other financial institutions including banks) in the fraud prevention system industry.
• Threat of substitution is low as there are only few players within the financial fraud prevention systems space catering to the retail banking industry.
• In countries like the UK where large syndicated databases form a primary part of the fraud prevention system ecosystem.
• Fraud prevention trends show that with an exponential growth in data from different channels such as mobile, email, ATM, etc., there is a need to develop effective early warning system using analytical predictor solutions that take a holistic approach towards identifying suspicious customer applications beforehand.
• While most fraud prevention system software providers focus on transactional fraud, there are only few suppliers who operate in the customer application fraud space for retail banking.
• Despite the low supplier base, intensity of rivalry is low as most suppliers offer flexible modular solutions that can be integrated across competitor solutions.
• With multiple application channels buoyed by the increasing preference for digital channels, it is essential for banks to monitor for identity not only at the application level but also throughout the customer lifecycle. Hence, the need for device intelligence systems that track web, e-mail and digital interaction behavior to derive abnormal pattern.

Global Financial Fraud Trends

• New-account fraud rose 70 percent in 2017,with account takrover fraud in the US growing three times over 2016,to reach a total loss of $55.1 billion
• Identity theft is a major component of new-account fraud where good credentials are used as facilitators for committing application fraud E.g., Social security number breach accounted for 500,000 fraud victims in 2014 and is expected to rise to 710,000 by 2018
• Identify Fraud number/victims reached 16.7 million in the US in 2017,an increase of 8 percentage over the previous year.ID fraud constitutes to 6.64 percent of consumers

• Total value netted by fraudsters was estimated at $16.8 billion in the US

• With regard to online fraud, CNP fraud accounted for 81 percent against POS fraud

Retail Banking Fraud Prevention Systems - Global Market Maturity

• While there are many players offering analytics based financial fraud detection software, there are only few players catering to the retail banking space. This is a direct consequence of regional/national regulations. Hence, the maturity is closely tied with the banking landscape
• While emerging economies still lag developed countries in terms of fraud technology adoption, they have the opportunity of leapfrogging into adopting advanced fraud detection software across the enterprise. (Its peers in the developed world face challenges integrating its legacy systems)

Global Fraud Prevention Systems Market - Drivers and Constraints

Drivers

Surging Adoption of Digitalization and IoT  

With lockdown regulations amidst the COVID-19 pandemic, people are increasingly turning to online transactions. The urban population, in particular, are digitally influenced to purchase any financial service or product, which implies they utilize banking applications or browse various websites to purchase financial products. 

This has triggered a sudden spike in the number of fake websites, which resemble banking apps, shops and home delivery services, trapping customers to do digital transactions. The rising use of the Internet of Things (IoT) and new IoT-enabled devices in the marketplace is becoming a crucial aspect of customer lifestyle and industrial operations. 

Connected devices provide convenience and are one of the reasons, which offers criminals the opportunity to break into the systems. The connected devices gather, transfer, and keep loads of consumer data, inviting privacy risks. 

Ad and ATM frauds are two major (and common) IoT frauds in the IoT world. The rise in fraud with cybercriminals targeting customers with fake activations of credit and debit cards, free COVID-19 tests, online bookings, and job offers have led to the adoption of fraud prevention systems.

Increasing Use of AI and ML in BFSI Industry

The banking, financial services and insurance (BFSI) industry is one of the early adopters of technology to avoid risks. Due to large-scale digital data transactions, financial institutions are exposed to a lot of vulnerability. 

The rising digital banking process has influenced financial institutions to safeguard transactions from fraud. At present, financial institutions are prioritizing financial risk mitigation as well as fraud prevention in real-time. Fraud prevention techniques are changing with the onset of pattern recognition. 

Machine learning (ML) has offered a major impetus to artificial intelligence (AI) in defending any system as ML shields companies from internal fraud and spot any deformities in people who may leak data. As such, the surging adoption of AI and ML will augur well for the fraud detection industry.

Constraints

Increasing Complexities of Frauds

With the adoption of EMV (Europay, MasterCard, and Visa) cards, identity frauds have gradually switched from offline to online.  Also, the complexity of fraud has increased, realizing the emergence of fraud accounts. Fraudsters are becoming savvier in their attacks. 

The growing customer expectations for round-the-clock digital access have compelled numerous companies, such as financial institutions and vendors, to reject stricter manual application review procedures to open accounts faster thus leaving more room for cyber-crimes. 

Supply Trends and Insights

Global/Regional Supplier

• Reactive to predictive analytics: Advanced analytics techniques based on machine learning (ML) such as neural networks and self-organizing maps are being used to identify fraud patterns and vulnerable customer applications. This, in turn, provides fraud scores for customer applications indicating proximity to a benchmark fraud characteristic.
• Big data: With the explosion in volume, variety and velocity of data, fraud prevention systems are gearing towards capabilities that enable digestion and monitoring of customer information across his/her entire lifecycle. For instance, looking at buying patterns to discern any unlikely/deviant purchase behavior in comparison with historic purchase behavior. These services are mostly provided as a bespoke managed service post-license purchase.
• Device intelligence to digital footprint: Apart from device intelligence services encompassing channels such as mobile, e-mail, IP, etc., there is also a need to look at synthetic identities where there are sudden spikes in credit requests from a seemingly authenticated source

Vertical/Local Supplier

• Vertical focused solutions:While there are few suppliers focussed on the retail banking vertical due to the need for dynamic regulatory systems, there are information sharing agreements through databases at the national level that contain cross-member (financial institutions and insurance) application data that help in screening for fraud at the application stage E.g., CIFAS, Hunter, SIRA in the UK, IFI in the Netherlands,FPN in Germany
• These fraud databases are also sometimes combined with data from other industries such as telecom data E.g., Fraud prevention pool in Germany

Engagement Trends

• Most adopted engagement model globally: Single vendor with a bespoke service
• Licensing metrics: The most widely used metric is volume of applications/number of submissions into the system. Some suppliers also use ‘pay per click' where in the initial submission and any updates or re-checks are counted separately
• Additional services such as integration to external consortium data through adaptors or APIs are charged as a separate fee. E.g., FICO Falcon Fraud Manager integrating with Hunter database

Why You Should Buy This Report

• The report provides insights into the fraud prevention systems market size, fraud prevention trends, and drivers and constraints.
• It offers Porter's five forces analysis of the global fraud prevention system market, region-wise and country-wise.
• It provides insight into supply trends and gives profiles and SWOT analysis of major players like Experian, TransUnion, and Equifax.
• Furthermore, this report on fraud management trends provides the pricing metrics analysis.