\n<\/p>\n
SINGAPORE –\u00a0Media
\u00a0<\/p>\n The biggest challenge faced by financial
\u00a0<\/p>\n Southeast
\u00a0<\/p>\n GBG developed its machine learning
\u00a0<\/p>\n “Winning Asia Risk 2021 award for the Best AI
\u00a0<\/p>\n “Machine learning helps financial institutions
\u00a0<\/p>\n A recent survey conducted by GBG with 118
\u00a0<\/p>\n According to Adam Emslie, Head of Analytics at GBG<\/b>, the most important factor
\u00a0<\/p>\n “Stemming from a single end to end solution,
\u00a0<\/p>\n The Asia Risk Technology Awards are the longest-running
\u00a0<\/p>\n “With instances of financial crime increasing around the
\u00a0<\/p>\n The
The win for GBG is the latest in a string of
For more information on GBG’s expansion of
SINGAPORE –\u00a0Media
OutReach\u00a0– 29 September 2021 –\u00a0GBG (AIM:GBG),
the global expert in digital identity, helping businesses prevent fraud and
meet complex compliance requirements, has today announced it has won the award
for Best AI or Machine Learning Innovation of the Year from Asia
Risk Awards 2021. \u00a0 The biggest challenge faced by financial
institutions today …<\/p>\n","protected":false},"author":1,"featured_media":17799,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[60],"tags":[],"_links":{"self":[{"href":"https:\/\/eodishasamachar.com\/en\/wp-json\/wp\/v2\/posts\/17798"}],"collection":[{"href":"https:\/\/eodishasamachar.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/eodishasamachar.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/eodishasamachar.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/eodishasamachar.com\/en\/wp-json\/wp\/v2\/comments?post=17798"}],"version-history":[{"count":0,"href":"https:\/\/eodishasamachar.com\/en\/wp-json\/wp\/v2\/posts\/17798\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/eodishasamachar.com\/en\/wp-json\/wp\/v2\/media\/17799"}],"wp:attachment":[{"href":"https:\/\/eodishasamachar.com\/en\/wp-json\/wp\/v2\/media?parent=17798"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/eodishasamachar.com\/en\/wp-json\/wp\/v2\/categories?post=17798"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/eodishasamachar.com\/en\/wp-json\/wp\/v2\/tags?post=17798"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nOutReach<\/a>\u00a0– 29 September 2021 –\u00a0GBG <\/a>(AIM:GBG),
\nthe global expert in digital identity, helping businesses prevent fraud and
\nmeet complex compliance requirements, has today announced it has won the award
\nfor Best AI or Machine Learning Innovation of the Year from Asia
\nRisk Awards 2021.<\/a><\/p>\n
\ninstitutions today is not the increasing volume of financial crime, but in the
\ncreativity and sophistication in which fraud attacks are executed. In managing
\nuncharted financial crimes, financial institutions (FIs) are seeing higher
\nfalse positive rates, higher fraud alerts, and more missed frauds, which are
\ndetrimental to achieving target business growth when customers are unable to
\nonboard and transact with success.<\/p>\n
\nAsia’s first fraud bureau, CTOS IDguard<\/a>, which is powered by GBG’s fraud
\nand financial crime platform, is currently deploying GBG
\nMachine Learning<\/a> and is seeing an uplift in fraud detection of up to 30%
\nfor credit card applications. Another Tier 1 global bank has also tested its machine
\nlearning technology to see a 22% reduction in false positives for credit card
\napplications. The machine learning technology at GBG has specifically helped
\nits customer base in addressing a range of financial crimes including account
\ntakeover, identity theft, loan never-payment, and money laundering.<\/p>\n
\ncapabilities in response to the increasing innovativeness and complexity in
\nwhich fraud attacks are executed. With Financial Crime 4.0<\/a> escalating, a rule-based
\nsystem is insufficient to detect and keep up with digital and emerging fraud
\ntypologies. GBG’s machine learning utilises both supervised and unsupervised
\nalgorithms; these algorithms are built into their core financial crime platform
\nand can be easily and quickly configured, trained and deployed via a low
\ncode\/no code user interface. In addition, it also seamlessly accepts the import
\nof custom models created in different algorithms via a Python notebook-like
\ninterface.<\/p>\n
\nor Machine Learning Innovation of the Year is testament to GBG’s success to
\nautomate, scale and unlock the value of deriving intelligence from a range of
\nhistorical, new and additional data in real-time. The goal of machine learning
\nis to uncover implicit inconsistencies in behavior that are not an act of human
\nerror, analyse and flag out anomalies to detect and prevent new possible fraud
\nscenarios as quickly as possible. It’s a watershed moment for our whole team
\nacross the globe,” says Dev Dhiman, APAC
\nManaging Director of GBG<\/b>.<\/p>\n
\nenhance two fundamental processes \u2013 customer experience management and
\nfinancial crime prevention. Reducing false positive rates is not just about
\nstreamlining internal processes and costs, but in enabling legitimate customers
\nto onboard and continuously transact with success. GBG’s machine learning which
\nunderpins its core financial crime technology can help financial institutions
\nmaintain stronger customer lifetime value while prioritising financial crime
\nmanagement,” concludes Dhiman<\/p>\n
\nfinancial institutions across Southeast Asia found machine learning is quickly
\nbecoming a mainstream solution for fraud detection and prevention. In the
\nsurvey, machine learning is the number one fraud prevention solution
\nrespondents are exploring this year, with more than one-third selecting this
\noption above others.<\/p>\n
\nabout machine learning models is not that they’re workable, but that they meet
\nthe efficiency and accuracy standards as demanded by customers and industry.<\/p>\n
\nGBG’s Digital Risk Management and Intelligence platform<\/a>
\npasses data from origination and transactions directly into the machine
\nlearning models bypassing the need for data extraction, resulting in faster
\nmodel training and deployment than what the industry typically offers. In
\naddition, fraud and compliance objectives can be achieved through multiple
\nworkflows with the GBG Intelligence Center<\/a>. Fraud analysts are
\nenabled to prioritise and enhance accuracy in detection and prevention of
\nlarger fraud challenges,” says Emslie.<\/p>\n
\nand most prestigious awards for firms and individuals involved in the Asia’s
\nderivatives markets and in risk management. The awards recognise vendors that
\nare serving financial services firms in meaningful and innovative ways. The
\nteam at Asia Risk spoke about why it chose GBG for this to win the prestigious
\nbest in class for AI or Machine Learning Innovation of the Year. <\/p>\n
\nworld, firms are struggling to cope with the rising volume of investigations
\nthat they have to conduct and ensuring that their fraud detection tools are
\naccurate and efficient. The judges were most impressed with the performance of
\nGBG’s artificial intelligence and machine learning to help reduce false
\npositives and improve fraud detection of emerging typologies,” says Blake Evans-Pritchard, bureau chief for
\nAsia Risk<\/b>.<\/p>\n
\nAsia Risk Awards 2021 were announced online throughout September 27-30, 2021.<\/b><\/p>\n
\nindustry-recognised achievements for the company:<\/p>\n
\nmachine learning across GBG’s end to end financial crime platform to improve
\nfraud detection accuracy, click here<\/a>.<\/p>\n<\/p><\/div>\n\n
Source link <\/a><\/p>\n","protected":false},"excerpt":{"rendered":"