There has been an unprecedented explosion of Big Data applications across industries. Along with Big data, technologies like Artificial Intelligence (AI) are now touching every sector and enabling the smart automation of human endeavors. As Denis Ostapchenya of Andersen says, “the role of Big Data is increasing” as more people are comfortable sharing their personal information in exchange for improved services.

So, how are AI and Big data expected to impact the banking industry in 2022 and beyond?

Recent studies have found that over 80% of bank and credit union executives believe AI will be the key differentiator between winning and losing.

Let us look at 6 data trends that will impact banking in 2022 and beyond:

AI adoption and spending

According to IDC, AI spending will increase from $85.3 billion in 2021 to $204 billion by 2025. Despite the restrictions imposed by the COVID pandemic, data experts have found that over 70% of technologists have observed an acceleration in their AI adoption strategy over the last two years. The banking and financial sector will account for 13.7% of this spending (slightly less than the retail sector).

Among the major impact areas, AI-backed chatbots are transforming customer service by answering common questions about opening bank accounts or checking account balances. At an advanced level, using AI in capital market applications enables low-income individuals to engage in financial market transactions.

Cloud banking

Traditional legacy systems were designed for something other than AI and Big data applications. Hence more banks and financial institutions are moving their applications to the cloud. This is the emerging trend of cloud banking. Besides reducing infrastructure costs, cloud-based banking can easily scale to provide more computing power.

According to Gartner, cloud-native platforms will be the power behind 95% of digital initiatives in 2022, up from just 30% in 2021. Leading banks like JPMorgan Chase and Arvest Bank plan to migrate their core banking systems to a cloud-native platform. An IBM survey found that 88% of outperforming banks will likely include a hybrid cloud as part of their digital initiatives, while 34% want to deploy on the cloud to improve operational margins.

Hyper-personalization

The 2020 Deloitte report on “The future of retail banking” found that over 50% of consumers expect banks to anticipate their needs and make the right suggestions, even before they have made contact. This is the era of hyper-personalization, or real-time data, to generate valuable customer insights using data science and behavior analytics.

As foreseen by HSBC Bank in the 1990s, “customers will increasingly be able to expect a highly-personalized service determined by their individual requirements.”

AI-enabled personalization enables a “customer-first approach” by automating repeat transactions (for example, autopay) or suggesting the best investments for individual customers (based on their previous investments or financial goals). In the long run, data-backed hyper-personalization helps banks maximize their customer knowledge (beyond the KYC norms), address new customer service expectations, and forge long-lasting customer relationships.

Data fabric

John Duigenan, CTO of IBM, discusses data fabric as “the network in which all those data sources get connected to make them usable and accessible.” Over the years, banks and credit unions have found it challenging to integrate their data “silos” and have found it harder for external sources in pieces or behind firewalls.

The presence of multiple data silos is why banks and financial regulators are paying hundreds to millions of dollars in fines for violating data governance norms.

The answer to this problem is a data fabric system that provides a unified view of internal and external data. Gartner estimates that a data fabric can reduce data management costs by up to 70%.

Digital platforms

Large and small-sized companies are developing their digital products through mobile apps and websites to thrive in today’s industry. For instance, third-party non-financial companies like PayPal, Amazon, and even WeChat are embedding digital payment options into their applications to provide convenience to their users.

How does the banking sector respond to this challenge? KPMG believes digital platforms will become the “preferred and dominant business model for banks and financial institutions in the future.”

Digital platforms effectively connect the “underbanked” and small businesses to financial providers using their mobile phones. The only question is whether banks will create their digital platform or offer services through a third-party digital partner.

Identity verification (IDV)

As open banking and data sharing become more prevalent, banks are now realizing the importance of identity verification, also known as KYC. Fuel by McKinsey projects “IDV as a service” to be the next $20 billion market. This has been driven by the gradual shift towards online transactions along with the rise of cryptocurrencies.

On its part, digital IDV solutions can now scan through multiple identity documents in a matter of seconds or analyze customer records from third-party database systems in minutes. In short, IDV is shortening the time between application and approval.

Zac Chen, COO of TruliooIf, sums it up as the “future of identity is digital.” Effectively, banks must adopt a “risk-based approach” to balance providing the right CX that their consumers demand with an acceptable level of risk.

Conclusion

In the post-COVID era, data-driven technologies are gaining more acceptance in the global banking and financial industry. Once regarded as “traditional” and “outdated,” banks are opening up to the immense potential that Big Data and AI technologies can offer to their business model.

With its technical expertise in Big Data, Analytics, and AI, Emergys Solutions has helped its customers implement technology projects with time and cost savings of up to 50%.

Emergys Blog

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