Lending Software trends that Banks and Financial Services companies will need to adopt to support their digital transformation agendas
– Mukesh Jain, Advisory Board Member, Pennant Technologies
The financial lending industry has seen an uptick in business despite the pandemic. In fact, lending has seen an impressive growth in the second half of 2021, and even with the pandemic continuing, the industry looks set to prosper throughout 2022. Newer business models such as BNPL (buy now pay later) and peer-to-peer lending have become extremely popular on the online and offline platforms in the Retail Lending space.
To sustain this growth, lending firms need to deal with constantly changing customer expectations, heavy competition from FinTechs and also effectively manage high volumes. Handling all of these require lenders to go fully digital and adopt technologies which enable them to deliver hyper-personalised experiences, rapidly respond to customer demands and scale. Lenders need to extend their digital transformation agenda across the value chain, shifting focus from digital loan applications to automation of disbursals, servicing and collections.
So, what are the key technologies and how will they boost the lending industry’s growth in 2022?
FinTechs have been able to scale rapidly and nimbly thanks to modern technology platforms, while traditional lenders struggle with the burden of legacy applications. To stay competitive, lenders can adopt a microservices-driven architecture by creating small domain-driven re-usable modules which enhance their enterprise agility and enable hyper-scaling.
Further, by combining microservices with external-facing APIs, lenders can rapidly expose banking services to third parties creating new revenue streams and also consume external services to create new customer or employee experiences. Growing adoption of middleware and API gateways would be a crucial outcome of this trend.
Conventional lending processes have required multitudes of customer documents to evaluate eligibility. While the enablement of credit bureaus has facilitated automated decisioning to a certain extent, lenders have started to look beyond the traditional avenues to extend access to credit to the unbanked. We are seeing new credit models built on data sources such as psychographics, shopping, telecom, travel, taxes and social media profiles, etc. by third-party partnerships to facilitate improved credit decisioning.
On the other hand, we also see lenders partnering with eCommerce and FinTech platforms to embed finance solutions into customer journeys in a bid to enhance accessibility and create seamless experiences.
As organizations increasingly augment available data with external data, they need to create a strong customer platform, which enable them to store this information and access it to create actionable insight.
Customer data platforms including data warehouse and data lakes integrated with CRM and campaign systems would need augmentation (in terms of additional data elements and deeper integration) and adoption of Big Data technologies. This enhanced data framework with strong data science-based analytics enable hyper-personalization, better targeting leading to strong cross and upsell for deeper product penetration and efficient onboarding of new customers. Usage of APIs and microservices will enable collection of data from multiple sources and collate it in the customer data platforms for processing in a more efficient and secure manner.
AI technologies have already matured from being used to create novel virtual assistants providing weather updates to making self-driving cars a reality. AI/ML technology has the potential to transform the complete lending process as we know it, right from the lending application process to risk management and customer service.
By adding a layer of intelligent automation on the customer data platforms, lenders can unlock the value residing in data siloes to create new use cases and customer experiences. For example, human agents interacting with customers will be powered by real-time AI-powered insights which predict the reason for customer contact, track customer sentiment, prompt responses and provide required information to boost their productivity. Over time, we can expect all transactional customer interactions being managed via AI/ML powered conversational solutions allowing business functions to enhance their focus on complex value-building activities.
All the above trends necessitate a strong scalable, flexible and secure infrastructure. The adoption of cloud technology will help banks and lending firms address these problems while enhancing accessibility. Cloud will also help reduce capital expenditure, streamline workflows, and allow banks to scale on-demand.
We will see increasing trends where banks and financial institutions will adopt hybrid cloud technology to modernize their lending operations. According to a recent IBM Institute for Business Value survey, the value derived from a full hybrid, multicloud platform technology and operating model at scale is 2.5 times the value derived from a single-platform, single-cloud vendor approach.
Apart from the above technologies, lenders need to continue experimenting with newer technologies such as Blockchain, AR/VR, 5G/IoT as they mature.
Conclusion
The lending domain has been one sector whose success has always been dependent on its ability to keep pace with the evolving market conditions. We will see a rapid adoption of new technologies by lending firms worldwide. While the ‘Digital first mover’ train has already sailed, it is now or never moment for followers to catch up and survive. These trends offer an opportunity for innovators to leapfrog competition and become winners.
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