BCCL upgrades core banking platform with Red Hat and Temenos

“This standardization means better interoperability between our systems and helps us avoid the incompatibility issues we tend to see with proprietary software.” — Pablo Recepter, CIO at BCCL

As industry and regulatory environments in Argentina have evolved, Banco Credicoop Cooperativo Limitado (BCCL) needed to upgrade its core banking platform as part of its digital transformation initiative. To take advantage of this new platform, BCCL, a large cooperative bank that handles 2.65 million customer accounts and up to 4 million transactions a day in 267 branches and 24 service centers across the country, also needed to upgrade its software to create a robust IT foundation for its core banking systems and Temenos software.

Keeping pace with change

According to Pablo Recepter, CIO at BCCL, the project’s goal was to implement the necessary technology to ensure the bank’s transactions could function reliably and efficiently in an increasingly complex industry, as well as meet changing regulatory requirements. Cost containment was another major consideration.   

After evaluating several solutions, BCCL selected open source solutions from Red Hat, a Temenos certified partner. Already, the open source Red Hat platform has met key imperatives of BCCL’s operations so it can offer the kinds of innovative banking services it wants to deliver to its customers, effectively and safely operate in a complex regulatory environment and scale to meet its higher processing requirements.

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AI in banking: Where artificial intelligence and machine learning may take us

With an aim to separate hype from reality in Day 4 at Sibos, I was on a mission to understand what the existing and near-term applications of Artificial Intelligence (AI) were in banking.  With machine learning described as “table stakes” now, Richard Harris (Feedzai) during The Ethical Side of AI panel, suggested that the closest we have to understanding the impact AI will have is by looking at the internet – knowing the internet would change everything but twenty years ago, we didn’t know how – describes the state of AI today.

Risk mitigation appears to be an active area for current AI application. For example, with a worldwide impact of money laundering estimates between 2% to 5% of global GDP (upwards of $2 trillion USD), Heike Riel, IBM (Sensemaker: The interconnectedness of everything and advanced AI) cited a case where they found a reduction in false positives of 95% to 50%, along with a reduction of 27% in manual effort by using AI/ML to help discover the undefined unknowns in the data. Using AI to help triage fraud for human interpretation and action is considered ‘narrow’ AI – the application of AI to one particular task.  

Broadening the scope of AI beyond a single task may be on the horizon. In the future I can see a time when an AI would become a new hire to the bank, employed to derive new, company-wide insights to improve processes, identify efficiencies or ways to improve customer experience.

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The Many Faces of Risk in Banking

In the regulatory environment of banking, risk has typically been top of mind. It was also top of mind at Sibos, where I followed the sessions on topics such as distributed ledger technology and open banking with great interest. Sibos, held this year in Sydney, Australia, is an annual week-long event billed as a “premier business forum” for the financial community to gather and collaborate around payments, securities, trade, and cash management, among other key issues facing banks and financial entities today.

In the new high volume and low dollar transaction world of electronic payments, the surface area of business risk has expanded. And when your competitor is only a click away, mitigating both reputational and technical risk becomes more and more critical. Let me explain.

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Preparing to be open in open banking

If I had to sum up a theme from my second day at Sibos, it would be open banking. Sibos is an annual week-long event that bills itself as a “premier business forum” for the financial community to gather and collaborate around payments, securities, trade, and cash management. At this year’s gathering in Sydney, Australia, a number of sessions have focused on initiatives around open banking and open APIs.

Several of the live polls throughout sessions at Sibos have focused on customer relationships – putting the customer (and partner) at the core, and building initiatives around that to become a more open banking institution.

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The network effect of blockchain

The impact of decentralization to financial services was abundantly clear to me on the first day of Sibos.

Moving almost $2 trillion in securities from a legacy system to distributed ledger technology (DLT), the transition of the Australian Securities Exchange to a blockchain is one of the more public use cases to date. Transitioning banks to DLT, whether that be for treasury services, correspondent bank payments, settlements, securities or other applications, getting the use case right from the beginning is an important first step to successful adoptions.

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Bringing AI and machine learning data science into operation

Contributed content from Foutse Khomh and Giuliano Antoniol, Professors in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal (Canada), Montreal, Canada.

Red Hat, as an open source community leader, participated with AI/ML researchers at the Software Engineering for Machine Learning Applications (SEMLA) initiative – sharing how organizations can take advantage of modern infrastructure based on open technology such as agile integration, microservices, and containerized applications – to help build and deploy managed, scalable intelligent applications on hybrid clouds.

Organizations eager to adopt AI and machine learning (ML) are up against significant challenges.  The practice of bridging the gap between data science and operations, much in the same way that DevOps can for application development. And just as with DevOps, there are architectural, cultural and process considerations associated with creating an agile AI/ML environment. For example, parallel to modern DevOps, open hybrid cloud platforms can allow for faster turnaround of refining models, integrating disparate data sources more quickly, and making it easier to take advantage of ML capabilities and tools from both providers and third parties – who have made their solutions available as containerized services.

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Staking a claim in digital-only banks

Big names in the financial services sector are moving beyond incorporating a few online and mobile banking features into their traditional products and services. They’re stepping into full-scale, digital-only banking: Chase has launched Finn, for example, and Citizens Financial Group has created Citizens Access. Reportedly waiting in the wings is a national digital-only bank from Citigroup, too.

These new brands stemming from established banks will be going up against competitors such as Ally and GoBank, who have made the digital-only bank space their home from their inception. By launching their digital brands, Chase, Citizens Financial Group, and the others that follow, are creating options for escaping the confines of their existing processes and technology environments.

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