K
Kathleen Martin
Guest
Neil Murphy is the Global VP at ABBYY, and believes AI is the way forward to tackle the ever rising cases of fraud. Along with other benefits, Murphy explains by using AI, financial organisations can reduce manual steps required in the onboarding stage, and process both structured and unstructured documents. In doing so, financial organisations gain a birds-eye view and can filter out suspicious and fraudulent actors.
Technological advancements, an increase in investment into security systems and fraud prevention initiatives have been widely adopted by the finance industry in an effort to curb scams and crises from occurring. Yet, the battle against fraud continues as unauthorised financial fraud losses across payment cards, remote banking and cheques totalled almost £800million in 2020, according to UK Finance. With fraud on the rise, the way financial organisations assess and manage risk needs to change.
Successfully selecting and mitigating financial frauds is not just about investing in the latest technologies it’s about digging deeper and taking a holistic approach to protecting organisations. This means financial companies need to take a closer look at improving their processes, using data more effectively and harnessing a combination of technologies to be secure.
So, how can banks and financial organisations take a holistic, AI-powered approach to fighting fraud?
Break down the silos
When it comes to data, there is no shortage of it in the finance industry — structured, unstructured, transactional, account-level – but while this data brings benefits in terms of consumer insights, when in the hands of nefarious actors, it can make fraud more pervasive. It’s true that initiatives like General Data Protection Regulation (GDPR) have certainly ramped up the regulation of consumer data, but there is still a huge opportunity to uncover insights with the data to bring benefits to the financial organisation.
In the financial industry, building trust and customer loyalty is incredibly important, which is why fraud can be detrimental to their reputation, and end up costing them. By collecting the data from fraud, anti-money laundering (AML), and cybersecurity, financial institutions can consolidate information across historically isolated functions and make more informed decisions with a holistic view of risk.
With the significant similarities of the data collected across AML, fraud, and cyber teams, breaking down these silos can provide a more transparent view of the threat landscape, better detect suspicious transactions, and streamline investigations. Since the criminals are using cyberspace to commit fraud and ultimately need to monetise that information and launder the proceeds so that the funds appear legitimate, it makes logical business sense to bring these functions together.
First steps to an AI-powered strategy
Prior to investing in the AI and automation technologies, financial institutions need to be able to identify the bottlenecks and blind spots in their business processes. Process intelligence can do this, giving organisations the tools to analyse less structured processes, identify opportunities for improvement, and increase both the speed and accuracy of executing said processes.
With this holistic approach, financial institutions can collaboratively collect and analyse intelligence from across the organisation. This model improves intelligence sharing across the industry and allows financial institutions to continuously test and improve their security playbooks.
Once they have a 360-degree overview of their business processes, the most effective place to begin automating is the onboarding process. Streamlining onboarding by leveraging modern technologies enables financial institutions to filter out fraudulent actors and deliver a more frictionless experience for their customers. Using a combination of technologies like artificial intelligence (AI), robotic process automation (RPA), and natural language processing (NLP) can enable financial institutions to ingest and process both structured and unstructured documents, minimise manual steps, and reduce the need for making redundant requests of the client. Establishing an effective client onboarding process not only enables faster detection of potential fraud but plays a significant role in developing relationships with new clients.
One thing is for sure, a holistic strategy provides the visibility necessary to better prepare for auditing and compliance requirements. It improves efficiency, protects the brand and reputation, and protects against sanctions or fines. There is greater protection against identity theft and fraud from a customer perspective, and fewer security incidents increase uptime, allowing customers seamless access to their financial lives.
Continue reading: https://thefintechtimes.com/abbyy-fighting-financial-fraud-with-artificial-intelligence/
Technological advancements, an increase in investment into security systems and fraud prevention initiatives have been widely adopted by the finance industry in an effort to curb scams and crises from occurring. Yet, the battle against fraud continues as unauthorised financial fraud losses across payment cards, remote banking and cheques totalled almost £800million in 2020, according to UK Finance. With fraud on the rise, the way financial organisations assess and manage risk needs to change.
Successfully selecting and mitigating financial frauds is not just about investing in the latest technologies it’s about digging deeper and taking a holistic approach to protecting organisations. This means financial companies need to take a closer look at improving their processes, using data more effectively and harnessing a combination of technologies to be secure.
So, how can banks and financial organisations take a holistic, AI-powered approach to fighting fraud?
Break down the silos
When it comes to data, there is no shortage of it in the finance industry — structured, unstructured, transactional, account-level – but while this data brings benefits in terms of consumer insights, when in the hands of nefarious actors, it can make fraud more pervasive. It’s true that initiatives like General Data Protection Regulation (GDPR) have certainly ramped up the regulation of consumer data, but there is still a huge opportunity to uncover insights with the data to bring benefits to the financial organisation.
In the financial industry, building trust and customer loyalty is incredibly important, which is why fraud can be detrimental to their reputation, and end up costing them. By collecting the data from fraud, anti-money laundering (AML), and cybersecurity, financial institutions can consolidate information across historically isolated functions and make more informed decisions with a holistic view of risk.
With the significant similarities of the data collected across AML, fraud, and cyber teams, breaking down these silos can provide a more transparent view of the threat landscape, better detect suspicious transactions, and streamline investigations. Since the criminals are using cyberspace to commit fraud and ultimately need to monetise that information and launder the proceeds so that the funds appear legitimate, it makes logical business sense to bring these functions together.
First steps to an AI-powered strategy
Prior to investing in the AI and automation technologies, financial institutions need to be able to identify the bottlenecks and blind spots in their business processes. Process intelligence can do this, giving organisations the tools to analyse less structured processes, identify opportunities for improvement, and increase both the speed and accuracy of executing said processes.
With this holistic approach, financial institutions can collaboratively collect and analyse intelligence from across the organisation. This model improves intelligence sharing across the industry and allows financial institutions to continuously test and improve their security playbooks.
Once they have a 360-degree overview of their business processes, the most effective place to begin automating is the onboarding process. Streamlining onboarding by leveraging modern technologies enables financial institutions to filter out fraudulent actors and deliver a more frictionless experience for their customers. Using a combination of technologies like artificial intelligence (AI), robotic process automation (RPA), and natural language processing (NLP) can enable financial institutions to ingest and process both structured and unstructured documents, minimise manual steps, and reduce the need for making redundant requests of the client. Establishing an effective client onboarding process not only enables faster detection of potential fraud but plays a significant role in developing relationships with new clients.
One thing is for sure, a holistic strategy provides the visibility necessary to better prepare for auditing and compliance requirements. It improves efficiency, protects the brand and reputation, and protects against sanctions or fines. There is greater protection against identity theft and fraud from a customer perspective, and fewer security incidents increase uptime, allowing customers seamless access to their financial lives.
Continue reading: https://thefintechtimes.com/abbyy-fighting-financial-fraud-with-artificial-intelligence/
