Resistant AI, the AI and machine learning financial crime prevention specialist, has announced that Habito, an online mortgage broker and lender, whose mission is to make it easier to get a mortgage and buy a home, has reported a 30 per cent increase in mortgage fraud detection following the implementation of the former’s Document Forensics solution.
Habito’s first-line risk teams were facing challenges in assessing the authenticity of documents, and escalated cases were taking longer for financial crime investigators to resolve. To confirm authenticity, the teams were also relying on outreach to the institutions that issued the documents, which slowed down decisions. To meet these rising challenges, Habito turned to Resistant AI’s Document Forensics solution.
“Resistant AI identifies manipulated documentation far faster and far more accurately than we humans can and also brings us to conclusions faster and with more confidence,” commented Matthew Willis, Habito financial crime investigator. “This has broadened our horizons to the risks that exist with digital documentation, whereas before, we were stumbling in the dark. They have helped us to drastically reduce both the time it takes to catch fraud and the amount of fraud that makes it past us to lenders.”
Resistant Al subjects every customer interaction to forensic analysis to detect document forgery, serial fraud, synthetic identities, bots, account takeovers, money laundering, and unknown financial threats operating at scale. Document Forensics was integrated as part of the Habito mortgage application process, with workflow triggers tied to the various verdicts provided to each document.
Applications with “Warning” or “High Risk” documents triggered escalations to the financial fraud investigation team. If the forensic analysis demonstrates clear attempts at fraudulent manipulation, the application can be declined immediately. As a result, the Habito team has been freed up to log the results and analyse them for fraud trends to build their risk intelligence. In less clear cut cases where further investigation was needed, time spent on each case was reduced by 52 minutes.
In addition, confidence in Resistant AI’s verdicts of authenticity meant applications with documents that met that standard could automatically move on to underwriting stages. In these cases, document assessment was reduced to mere seconds. Since it only takes 50-80 authentic samples to create new “Trusted” models of authenticity, coverage of the document types Habito dealt with increased daily in production from the incoming stream of documents.
“Habito has established a strong reputation for innovation and frictionless customer experience, and the implementation of Resistant AI Document Forensics underlines their commitment to the highest standards of performance and efficiency,” said Martin Rehak, founder and CEO, Resistant AI. “It also signals the increasing role Resistant AI is playing in the fight against financial fraud and the value of integrating human expertise with cutting edge technologies.”
Image and article originally from thefintechtimes.com. Read the original article here.