Identifying the relevant Entity name requires the ability to: Understand the Name in Multiple Languages. Example: Khaled Mashal in arabic: الد مشعل Resolve different Transliterations and Spellings. Example: Khaled Mashal can be spelled according to different pronunciations with either K, Q or H as it’s first letter: Haled, Qaled, Khaled.. Distinguish between different Name-structures, especially […]
AML Name Screening mathematical equation:
Z = (spelling variations x transliteration x name structures) x 170,000,000 data
Sanction & PEP lists – 6,500,000 names X 20 Aliases = 170,000,000 entries
Spelling Variations & Transliterations – can go beyond hundreds of different variations!
Are Banks stocks rating at risk for missing ESG goals due to Social Discrimination & Bias in legacy AML solutions implemented in banks today? The new ESG movement is democratizing the business world, no longer pure capitalism rules but what is good for all people, of every background, religion, and social status. Major funds have […]
“Find a Needle in a Haystack” The AML Name Screening challenge A major challenge in AML Name Screening is numerous name variations, that obscure the real entity; yet identification by name is the required by law method, but current simple technologies today make this task elusive and hard requiring advanced means and technology for deep […]