HSBC Fusion – AI Credit Assessment: Best credit assessment initiative

Assessing credit for SMEs has been a longstanding challenge for banks for various reasons – with asymmetric information, manual processes and time-consuming evaluations probably being some of the biggest hurdles to overcome. However, by embracing new and emerging technologies such as artificial intelligence (AI), banks have the potential to stay on top of their game and enhance their overall efficiencies.

Case in point: PT Bank HSBC Indonesia. By integrating AI into its credit assessment process, the bank has ensured swift and accurate evaluations and revolutionised its approach to support SMEs – the backbone of so many economies – effectively. To develop HSBC Fusion, an AI-led credit assessment tool, the bank partnered with 6Estates, an enterprise AI solutions provider based in Singapore and specialising in domain-specific Large Language Model (LLM)-backed solutions.

HSBC Fusion’s notable achievements and benefits it has accrued for the bank has led it to pick up the Best Credit Assessment Initiative award at the Global SME Banking Innovation Awards 2024, hosted by Global Private Banker.

Embracing Innovation

HSBC Fusion was created to tackle three of the biggest problems in SME credit assessments – the lack of comprehensive financial data, which in turn creates information assymetries; the manual and time-consuming processes; and the higher costs of serving SMEs.

By partnering with 6Estates to leverage its AI technology, the bank trained the AI model on its vast customer data in order to spot suspicious activity with more precision than manual optimisation, while also collaborating with various teams within the bank to provide valuable insights and logical perspectives Additionally, the unique selling point of this tool is that it can capture information from structured, semi-structured and unstructured documents such as PDFs, photos and scans, to interpret context.

With this, HSBC Fusion has now successfully managed to cut down the time needed to analyse a potential borrower’s bank statements – completing what used to take hours in just minutes.

Compared to manual processes, the AI tool drives 70x faster bank statement analysis, boasts an 80% error reduction assuming a 5% human error rate, and a 76% cost reduction compared to human processing.

Ultimately, the bank has succeeded in elevating its customer experience by providing a faster credit decision time and accelerating access to their funding.

Hitting The Right Targets

This initiative marks a significant milestone in HSBC’s commitment to harnessing technology that enhances its banking operations and enables new customer benefits by partnering with technology innovators.

By leveraging the power of AI, the bank has not only enhanced and expedited the credit assessment process for loan applications, but it also promises earnings growth, improvements to decision-making and better and better risk management, which in turn, impacts the bank’s financial performance on profit maximisation through cost efficiency. This helps the bank fulfil its strategy of digitising at scale.

On top of that, this has also advanced HSBC’s ESG initiatives to accelerate new climate solutions, especially in carbon challenge industries. At the outset, the efficient and secure digitalisation of customer information reduces the need for printing and storing large volumes of physical documents.

Moreover, 6Estates’ credit assessment automation tools also enable quicker, more in-depth, and cost-effective analysis of traditionally more challenging borrower segments, such as SMEs.

Presence In Indonesia

Operational in Indonesia for more than 130 years, PT Bank HSBC Indonesia has a deep footprint within the country, with more than 50 branches spread out across 25 cities.

With an unparalleled track record across all debt products for Indonesian clients, HSBC Indonesia commands a strong presence in the local market – employing more than 4,000 people and offering a range of services in wholesale, wealth and personal banking.

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