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Blog | Feb 11, 2022

Five Benefits of Process Mining in Banking and Financial Services

Five Benefits of Process Mining in Banking and Financial Services
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Banks, insurers, pension funds, and other financial service institutions operate in a highly regulated industry and they’re faced with growing demands for auditability, compliance and operational resilience.

Today’s financial institutions need to deploy sophisticated analytics and data-driven capabilities to increase growth and profitability, lower costs and improve efficiencies, drive digital transformation, and support risk and regulatory compliance priorities — all while supporting and driving business strategy.

Banks recognize that the only realistic way to deliver these priorities is to use intelligent automation, which is a set of combined technologies that enable digital workers to deliver more advanced banking automation capabilities.

While digital workers derived from robotic process automation (RPA) have skills used for basic automation, intelligent automation enables digital workers to easily integrate with advanced technologies like artificial intelligence (AI) and machine learning (ML). They can also master advanced analytical and cognitive skills, such as reading documents or performing activities that require rules-based thinking.

What Is Process Mining in Banking?

Introducing intelligent automation can seem like a daunting task. To ease in, some financial services organizations are beginning their automation journey with process mining, which is defined by Gartner as, “a technique designed to discover, monitor and improve real processes…by extracting readily available knowledge from the event logs of information systems.”

Through process discovery and mapping, financial services organizations get visibility to better understand and compare people, processes and systems against best practices. Full transparency and actionable insights make it easy to optimize processes, so companies can make critical decisions faster and improve results more easily.

Blue Prism Process Intelligence Powered by ABBYY Timeline offers tight integration between process mining, task mining and intelligent automation. It streamlines the customer journey so organizations can go straight from process mining to Blue Prism Capture, then bring it all into Blue Prism Design Studio.

Once banks have used process mining to identify areas for improvement, they can start thinking about how they can deploy digital workers to speed up tasks, improve accuracy and reduce operational costs.

Instead of having expert staff working constantly to move data from one system to another, digital workers can. They can access the same applications and systems as humans, which means they’re able to take on those laborious data handling and migration tasks, while freeing up people to undertake higher value work.

Benefits of Process Intelligence in Banking and Financial Services

Blue Prism Process Intelligence Powered by ABBYY Timeline is a single, unified solution that delivers a deeply integrated, best-of-breed process and task mining offering that drives more value from automation in less time. Process Intelligence can help financial institutions:

1. Gain visibility of processes and tasks

Banks and financial services institutions using Blue Prism Process Intelligence can map the real-time processes used across their organization, even when those processes access data held in siloed systems, including core banking applications and blockchains. Process mining provides the granular detail needed to understand what’s happening day to day in banks’ businesses, and how to do things differently in order to improve, optimize and reimagine the way they operate.

2. Drive digital transformation and innovation

There is no doubt that banking transformation is at the top of the agenda for every financial institution across the world, whether that’s supporting mobile apps, digitizing trade finance documents or automating cross-border payments. Using process mining, banks can increase certainty and buy-in for digital transformation programs by focusing in on the improvements that will deliver a strong return on investment when measured against business strategy.

3. Reduce regulatory and compliance risks

Banks can save time and avoid human error by automatically generating regulatory compliance reports through the extraction and configuration of data across platforms. They can also improve the speed and accuracy of sanctions checks to improve compliance, reduce risk and deliver faster cash cycles to customers.

4. Improve customer experience

Intelligent automation in the contact center significantly reduces the time required to identify customers and respond to requests within a multi-channel environment. As a result, financial service institutions can improve customer service Net Promoter Scores (NPS) while increasing employee retention rates.

5. Accelerate and scales automation

Once banks have achieved success and senior team buy-in with intelligent automation in one business area, they can replicate the same approach across the institution, using process automation to prioritize new areas for improvement according to chosen return on investment metrics.

Examples of How Process Intelligence Can be Used in Banking and Financial Services

Process mining can be used to analyze inefficiencies across a broad range of systems used by banks, from the back office through to customer-facing applications. Anywhere data flows between teams, customers and third parties can be analyzed and improved with the help of process mining. Banks are using it to improve processes across a wide range of applications, including those outlined below.

KYC and account management

Reports of regulatory fines imposed on banks continue to emerge, despite financial institutions’ best efforts to complete know your customer (KYC) checks as effectively as possible. Process mining enables new customers to open a bank account and apply for additional products in just minutes with automated KYC checking and affordability calculators.

Fraud and AML

Wherever employees need to make decisions that are commercial, transactional and high-volume, banks can use a solution that can fully automate and augment the human decision-making process involved in checking whether applications are real or fraudulent. This improves the speed, accuracy, scale and transparency of carrying out anti-money laundering (AML) checks and provides an audit trail for any future investigations.

Loan processing

Under intense pressure from fintech providers, which promise to make lending decisions in minutes, traditional banks need to build personalized, seamless, and digital customer journeys to stay relevant and competitive. That means undertaking and consolidating all of the checks and reporting needed to make a decision in parallel, which is only feasible when digital workers are used to collect and complete relevant data.

Transaction processing

Processing transactions within banking operations, such as trade finance, can be long-winded and resource hungry. By digitizing all the relevant documents and ensuring digital workers can move them safely and securely through an automated framework, banks can ensure funds reach their rightful recipients quickly and accurately.

Process Mining in Banking and Financial Services

Despite the great strides made in the financial services industry to simplify and standardize processes for the benefit of customers, as well as support growth for the banks themselves, the dependency of individuals and businesses on financial institutions will always remain.

Therefore, banks will continue requiring stringent controls to protect funds, to ensure detailed compliance checks are undertaken, and to guard against cyberattacks. Yet, while the complexity of a bank’s business cannot be readily deconstructed, intelligent automation delivered as a result of process mining enables banks to maintain and accelerate operational effectiveness.

The next stage will be to scale automation beyond initial projects to improve processes such as loan origination and mortgage decision making, using technologies such as AI and machine learning to understand more about customer behavior, predict future demand for financial products and release finance professionals from the drudgery of labor-intensive work.

Find out about other industry use cases for process mining in our article here

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