How automation helps banking institutions reduce their exposure to financial crime

By Guy Mettrick, Industry Vice President, Financial Services at Appian

The constantly evolving nature of criminal activity, regulation, technology and banking operations makes managing the financial crime lifecycle a complex challenge for banking institutions.

Preventing financial crime is also expensive. According to McKinsey, around 10% of a bank’s workforce is assigned to activities related to financial crime detection. And in 2022, North American financial institutions spent $56.7 billion on financial crime compliance, with the growth of Anti Money Laundering (AML) activity the largest contributor to increased costs at 55%.

Why KYC is critical to identifying financial crime

The Know Your Customer (KYC) process is a vital mechanism financial services companies use to mitigate and reduce fraud, AML, identity theft and terrorism financing. KYC is the mandatory process of identifying individuals and business customers when they open an account.

Commenting at the Fraud and Financial Crime Europe 2022 Conference in London,  Appian partner and Global Head of Banking at WNS Vuram, Rhys Jones, explained that the first time a customer interacts with a bank is during the onboarding process. He observed, “The best way to mitigate and reduce financial crime is to understand who you’re working with from the beginning.”

Historical challenges to KYC effectiveness and efficiency

Meeting KYC regulations is an onerous legal requirement for banks worldwide. In 2021, US financial institutions were fined $2 billion for failing to meet their KYC obligations. But effective and efficient KYC processes are critical because they help identify financial crime and assist banks in meeting their stringent compliance obligations.  Without them, organisations cannot properly assess the risk of doing business with an individual or organisation.

Today, institutional and retail customers demand speed and convenience from service providers, but many banks fail to meet customers’ increasingly sophisticated expectations. Thomson Reuters reports that 89% of corporate customers had a bad experience with KYC, leading to 13% changing financial institutions.

Conversely, McKinsey research reveals that accelerated friction-free onboarding improves customer satisfaction and delivers a 15% increase in banking revenue.

When creating and delivering a seamless KYC process, financial institutions face internal challenges as well as a volatile operating environment. Identity verification and fraud detection require the collection of vast amounts of documentation, but many banks continue to store data in silos and use disconnected legacy systems. This means customers are often required to provide the same information multiple times, and data is often captured manually or in systems inaccessible across the organisation. Files frequently require manual review to identify false positives, which currently account for 42% of AML alerts.

How digital transformation can streamline the KYC process

Many financial institutions are solving these structural challenges and improving their end-to-end customer journey through digital transformation. The benefits of digital technologies include fast access to data, time and cost savings, flexibility, and the ability to build reusable processes. Being able to access, analyse and extract quality data in real-time lies at the heart of identifying potential criminal activity, so leading banks are adopting a “data first” approach.

Low-code platforms with process automation allow banks to access the right data at the right time through a data fabric. This provides a virtual layer that centralises data and provides access to it wherever it resides, without the need to migrate any data. Access to centralised data enables a seamless and efficient completion of investigations and the generation of compliant reporting.

Intelligent automation tools speed up analytical processes by eliminating manual work and delivering efficiencies and insights in unified workflows. According to McKinsey, banks that increased end-to-end KYC process automation by just 20% reduced the number of customer outreaches by 18% and increased the number of cases processed by 48% per month.

• Automation can streamline investigations by gathering and presenting information in a consistent format for AML investigators. While there will always be a need for manual investigations and interventions, these become more focused and quicker when machine learning and AI are used to detect risk factors and reduce false positives.
• Intelligent document processing (IDP) can speed up KYC by automatically extracting relevant information from lengthy documents, and data security is improved through using IDP. Process mining can be used to monitor efficiency, such as checking the time taken to complete tasks.
• Banks use various niche software solutions such as transaction monitoring, name screening and sanction screening during the KYC process. Some also have access to AI and machine learning (ML) tools to help them better glean insights from and spot patterns in the data from those applications.

A low-code platform that facilitates end to end process automation through data fabric capabilities can integrate these various tools, connecting niche applications and new tools to existing systems. And most importantly, it can connect the data held in the different applications.

The ability to reuse, repurpose and recycle workflows saves banks time and money. Case management is one example of a process suitable for a reusable workflow because the steps are identical: a case is created, triaged, assigned to an investigator, reviewed and remediated.

Future-proofing the KYC process

Financial fraud protection will always be a moving target because criminals are becoming increasingly sophisticated and will continue to find new ways to obtain funds illegally. However, automation provides the tools, speed, and transparency to help financial institutions keep pace with emerging threats.

It also offers the flexibility needed to integrate new legislation into existing applications and accommodate growing challenges, such as wider ESG reporting demands.