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Home Technology

Decision analytics: a digital rescue plan for banks

Steve Griffiths by Steve Griffiths
October 12, 2020
Photo by VisionPic .net from Pexels

Photo by VisionPic .net from Pexels

It’s now eight months since the pandemic started and neither consumers nor businesses are spared from its impact. For the first time in six decades, even the up-and-coming 45 countries in “developing Asia” are experiencing a recession.

Twice as many consumers worldwide are having problems paying their bills since COVID-19, based on the insights from Experian’s Global Insights Report. And more than a fifth are struggling to pay specifically their credit card and utility bills since the pandemic hit. What this means is that COVID-19 could potentially add US$440 billion to credit costs in Asia Pacific.

It’s obvious that the financial industry, especially consumer-facing players, need to brace themselves for a challenging road to recovery. Banks will need to carefully balance between putting their existing customers’ interest as a top priority, while mitigating credit risk and evaluating capital and liquidity.

For a bank to survive and thrive in these challenging times, decisioning analytics could save valuable time and resources in helping them manage customer credit risk.

Digital crisis management

For many banks, COVID-19 was a catalyst for digital transformation. Many organisations stepped up their digital analytics capabilities in areas such as hardship management, risk calibration and forecasting.

With a surge in customer demand in an economic downturn, banks and financial services providers need to ensure they handle larger volumes of requests in a customer-friendly, yet cost-efficient manner.

In Singapore, DBS alone received over 8,000 requests for mortgage relief and moratoriums on almost $1.6 billion of SME loans. As consumers and SMEs weather through fiscal challenges, their financial profiles evolve quickly as they borrow more to bridge income gaps.

Banks are increasingly relying on collection systems, supported by analytical tools that model consumer actions, assessing vulnerable populations in order to help them decide on the best strategy for engagement.

Analytics and machine learning can be used to build stress scenarios to prepare for the future. Banks are then able to redevelop and adjust current models to account for customer profile changes, calibrating against risk.

The current economic conditions are likely to be a true litmus test for financial services providers who can adapt their use of technology swiftly to pave the road for recovery. Many are looking for solutions that deliver a seamless and fair customer experience, and banking and financial services (BFSI) companies are turning their attention to cloud-based solutions for greater operational flexibility.

On-premise or cloud based? Flexibility is key

The reality is that the cloud is likely not a straightforward solution, especially for BFSI players. Many still operate on-premise, citing regulatory issues and compliance as the biggest barriers.

That said, cloud deployments are becoming more common in the industry. According to IDC, business agility is the most important trigger for cloud adoption. Experian’s study found that 85% of businesses are considering moving to the cloud specifically for this reason.

We’re increasingly observing traditional banks shifting to cloud technology – Standard Chartered Bank, for example, recently announced a three-year partnership with Microsoft to become a cloud-first bank for its core banking and trading systems.

The journey to the cloud is possible with a structured approach. For many, the actual migration to the cloud will call for an overhaul of both corporate culture as well as legacy infrastructure issues. For banks, this needs to be accompanied by a thorough risk assessment and careful, ongoing vendor management which will enable them to mitigate data and third-party risks.

It is undoubtedly challenging to brave through the COVID-19 storm and aftermath, but every cloud has a silver lining. Organisations that are bold enough to overcome the initial hurdles of cloud adoption will be able to respond to their customers’ growing needs while calibrating against risks. BFSIs that are agile and adaptable with the ever-evolving situation have the best chance of emerging victors from this crisis.

Related:  Talent shortage fears propel shift to skills-based strategies in Hong Kong
Tags: COVID-19credit riskscrisis managementdata analyticsdigital transformationmachine learning
Steve Griffiths

Steve Griffiths

Steve Griffiths is managing director, Decision Analytics, Operations & Transformation at Experian Asia Pacific. He leads the Decision Analytics team and is responsible for overseeing and growing Experian’s data insights and analytics business in the region. Griffiths is a senior business executive with more than 25 years’ experience in the technology and information services industries across Asia Pacific, EMEA and the United States. His tenure at Experian began as chief financial officer, Asia Pacific in 2013, before he moved on to Global CFO of Experian Marketing Suite role, followed by managing director, Operations & Transformation at Experian Asia Pacific.

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