Modernizing through intelligent integration and automation points the way to better management of risk and customer experience.
Banks are constantly seeking ways to enhance customer service through digitalization, but they are facing modernization chokepoints.
Challenges include optimizing data management, scaling technology and creating new digital opportunities to meet business needs. What’s more, financial institutions have to deal with complexities in risk management such as anti-money laundering (AML), cybersecurity and fraud.
Data can help, but for data to be leveraged effectively, it needs to be refined (like crude oil). When garnering this fuel for the digital economy, organizations need to be able to collect and integrate data effectively to meet business demands such as KYC and customer experience.
CybersecAsia finds out from Thomas Lai, Vice President & General Manager, Asia Pacific / Japan, Boomi, how modernizing legacy structures can help financial institutions become more agile and adaptive to fast-changing business needs, and provide superior customer experience.
What are the challenges that banks are facing with regards to risk management?
Lai: Substantial change in risk management is driven by multiple sources. Broadening regulations, rising fraud, and evolving customer expectations have notably impacted risk functions. Banks, especially the traditional players, will need new tools to circumvent them as legacy tools are ill-equipped to deal with these risks.
Technologies such as artificial intelligence and data analytics can strengthen banks’ ability to detect, analyse, and respond to new regulations and suspicious activities effectively. IDC finds that well over 60 percent of Asia Pacific banks plan to up spending on big data & analytics as well as artificial intelligence (AI) and machine learning (ML) tools. However, many are still challenged by disruptions such as increased instability and downtime, as well as heightened operational risks from migration.
The key here lies in bringing together the organization’s entire IT stack and removing friction so that quality, accurate, and actionable data can move freely to mitigate risk as well as drive business outcomes.
What are common modernization chokepoints for financial organizations in the region?
Lai: We often see banks grappling with disparate cloud applications due to strategic missteps in their modernization initiatives. This can result in technical debt. Many banks are ill-equipped to address data sprawl and fragmentation on the back of the exponential growth in data volume, locations, sources, and systems.
Most organizations seek a single 360-degree view of the customer to improve the accuracy and speed of decision making. By connecting and maintaining the “golden records” throughout systems in any environment to ensure the data quality, consistency, and visibility that enables financial organizations to move faster and make better decisions. In addition, this helps to improve operational efficiency as employees, and customers have a single, accessible and accurate repository to support analytical initiatives.
The more progressive institutions are also looking to provide new experiences for said customers to grow their share of wallet which can be done through data-driven insights.
Banks should look to integration to bring together newer applications with legacy IT that still forms the backbone in the tech stacks of many regional financial services providers. Organizations can benefit from low or no code integration applications. It’s now easy for IT to make adjustments as business processes change, and members appreciate the simplicity of a business workflow which they can easily access with an interface.
How can intelligent integration and automation help FSIs mitigate business risks and serve customers better in this competitive landscape?
Lai: In the plainest possible terms, it positions financial services providers to gain the requisite flexibility and speed to navigate market changes and rein in risk.
McKinsey finds that processes like cash disbursement, revenue management, and general operations may be automated fully. The report adds that this will simplify core internal transactions, help establish standardized reporting mechanisms, and raise efficiency.
As a result of process improvement, automation and smart integration, therefore, also increase customer value by bridging the gap between outdated back-end solutions and relatively new front-end solutions. This then enables financial institutions to establish processes that address both customer needs and add value for them.
What are some tips for organizations to effectively improve their agility and speed to response, as well as lower the total cost of ownership?
Lai: Organizations must first understand their needs, which can range from adapting to industry change, modernizing legacy systems, delivering a world-class customer experience or onboarding a new entity after an acquisition.
API-led solutions require the kind of human resources that many banks simply do not possess. That means integrations eat up more time, require continuous management, add to complexity and technical debt, while locking the business into a low-return investment.
On the other hand, there are lightweight tools that connect systems but ultimately fall short in the scale department. They also are not tailored to the business’ needs, nor do they hold up when any level of technical complexity is introduced.
However, trumping them are modern, cloud-native integration solutions that leverage crowdsourced intelligence. It is vendor-agnostic, meaning the business can run the applications it needs to thrive.
For instance, one of Australia’s largest mutuals, Teachers Mutual Bank, leveraged a low-code, plug-and-play platform to drive digital transformation – all while reducing IT operating costs with flexible, dynamic connectivity.
By replacing complexity with simplicity, a modern integration platform connects multiple generations of technology in hybrid ecosystems. Take for example Union Bank & Trust in the US, which markedly sped up its loan approvals process within three days of deploying such a platform.
Such solutions eliminate the need to own on-premises middleware or hardware. Through self-managing, self-learning, and self-scaling integrations, human intervention is also unnecessary.