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The Potential of Digital Lending

Digital lending has great potential to reach people who have so far not been involved in financial services. The rapidly growing online lending marketplaces (dubbed peer-to-peer, or P2P, lenders) and established financial institutions compete to find out who can provide borrowers with more funding and better terms. According to Autonomous research, by 2020 digital lending will encompass 10% of all loans in the U.S. and Europe at $100 billion in volume.

Mitesh Soni, Senior Director – Innovation, Fintech and Ecosystems at Finastra, shared his opinion on the subject with us.

In today’s competitive retail banking environment, customers are increasingly looking for simplicity, convenience and relevance. Simplifying the lending procedure, making it faster, more customer-centric, eliminating long waits and superfluous administration is perceived as critical by both customers and banks in order to reshape the customer experience. A major challenge for commercial banking lies in the complexity of workflows which remain mostly manual. Streamlining processes to make them more efficient in terms of time and cost will be the banks’ utmost priority

Scoring models are getting better over time as more data points become available for testing and algorithms become more precise through iteration. Three important points are helping with prediction: more data sources allowing more intelligent prediction; faster processing power to crunch through the data; better understanding of customer behaviours.

Data management is critical to lending and as more structured and unstructured data points get collected, challenges shift towards streamlining and orchestrating that data. This requires heavy integration and architecture to create API-level orchestration that reaches out to multiple customer endpoints.

Finastra has made strategic investments in AI and machine learning technology to improve data management and create more efficiencies for our clients’ lending operations. For example, Finastra has used AI tools to read credit agreements, select the relevant fields for deal onboarding and auto populate the data into the bank’s loan servicing application with no manual intervention. The technology is helping reduce operational risk, increase automation and enable our clients to scale their lending operations.

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