Machine learning, orchestration and improved fraud detection accuracy capabilities designed to de-risk Asia’s fast-evolving digital onboarding needs for growing financial institutions
SINGAPORE – Media OutReach – 30 January 2020 – GBG (AIM:GBG), the global technology specialist in fraud & compliance management, identity verification and location data intelligence, today announced the launch of four fraud solutions, including its flagship Instinct Hub now as a platform solution. Businesses across the globe are enabled to onboard quality customers more swiftly, while simultaneously protecting their organizations and their customers against losses from fraud and financial crimes in an increasingly complex digital landscape.
“Nearly one in two enterprises in Asia Pacific are falling victim to fraud, money laundering, or other forms of financial crime[1]. Financial institutions find themselves facing unprecedented diversity of application and transactional channels — from branch to online and e-wallets. These channels and criminal activities are evolving at a speed and complexity that these enterprises, and the financial institutions that support them, are hard-pressed to keep up with,” said June Lee, Managing Director of APAC, GBG.
“To aid in that fight, GBG offers a layered digital fraud and compliance solution which unifies data across vertical silos to improve financial crime detection accuracy across the customer journey. Straight through process across identity verification (KYC/AML) onboarding and transaction phases onboard good actors faster; coupled with machine learning it all in all increases online fraud detection by 30 percent and reduces false positives by up to 20 percent — giving business leaders a truly holistic approach to defending their customers and de-risking their organizations.”
GBG’s fraud and compliance management product suite is accredited by Chartis as best of breed anti money laundering (AML) and watchlist solutions, for their strong case management and analytics capabilities, focused functionality and ability to integrate with other best-in-class point solutions. They already power the anti-fraud risk efforts of many of the region’s largest institutions, from regional banking giant HSBC, BNP Paribas Personal Finance in Spain, major wagering players in Australia like Tabcorp to 9 out of 10 of Malaysia’s top tier banks. At the foundation of its offering sits Instinct Hub, a key solution to its digital risk management and intelligence platform, which manages swift and frictionless new customer digital onboarding Instinct Hub is upscaled to combat complex financial crimes 4.0 attacks against a customer identity and perpetrated across online, mobile and branch networks, GBG Instinct Hub is designed for organizations who are embracing digital transformation, e-banking channels and launching digital banking products. This newest version of GBG Instinct Hub has enhanced operational efficiency and effectiveness gains — fraud analysts and investigators are able to quickly identify, visualize and are alerted to suspicious behaviours with an improved user interface and dashboard, as well as an improved workflow.
Other solutions include:
Predator 5.0, GBG’s autonomous solution for identifying and ceasing suspicious transactions and payments that can cost financial institutions billions in losses.[2] The solution offers an unprecedented agility and flexibility to add and defend digital and payment transactions through dynamic channel modification and behaviour abnormality security. Financial institutions are enabled to scale to new channels and new behaviour flows as needed to detect schemers. This newest version also provides process automation benefits through an augmented reviewing experience with quick action buttons, user-defined interfaces, dynamic holistic views, and the ability to trigger straight through actions into banking systems.
Orchestration, a module for Instinct Hub that can raise fraud detection up to 30 percent by dynamically activating the desired best of breed cyber, identity, geolocation and bespoke third party calls such as to proprietary banking systems and fraud bureaus. It drills down on suspicious behaviour by triangulating additional parameters including social media behaviour, device reputation, geolocation, blacklists, and email usage; and
Machine Learning, a module for Instinct Hub that uses advanced modelling techniques to detect complex criminal attacks, augment detection accuracy and reduce false positives. The end user intuitive interface extends the realm of machine learning modelling beyond data scientists and utilizes predictive machine learning logic to analyse vast quantities of data. The end results providing greater piece of mind protection, better quality alerts less workload for investigators and ultimately onboard good customers quicker.
All of GBG’s solutions can be supported across a range of infrastructure models, from full on-premise to private, public, and hybrid cloud. “Financial institutions and other enterprises must increasingly balance the imperatives of digital transformation with the need to maintain watertight defences against financial and cybercrimes,” said June Lee. “With that in mind, GBG’s solutions are designed especially to provide frictionless and fully-automated layers of protection which evolve to the changing customer experience, payments models, and infrastructure choices that digitally transforming organizations may employ.”
“Having the right tools in place and being able to utilize them quickly is crucial for businesses to be on the front foot when it comes to mitigating financial crime, which is why GBG ensures its customers have access to local professional services so they can get laser focused support, whenever they require it,” said Michelle Weatherhead, Operations Director of APAC, GBG. “By having both onsite and remote expert advisory and support capabilities in the region, our customers can ensure they combat complex fraud and compliance challenges, and keep their own customers safe, without compromising on delivering a seamless experience.”
