Survey of 57 Indonesia lenders shows nascent data and analytics maturity

Based on this methodology, the white paper reported the following:

• 84% of respondents were committed to developing an advanced analytics strategy in 2023, while 79% were still in the exploration phase, assessing its viability for their businesses.
• Over half of respondents from Indonesian financial services institutions (FSIs) were poised to take action, with 67% gearing up to build more data applications, 59% looking to leverage predictive analytics and machine learning, and 54% aiming to centralize customer data on specialized enterprise platforms in the next one to two years.
• Nearly 49% of Indonesian FSIs were also planning to create a center of excellence for business intelligence, advanced analytics, data science, and/or AI over the next twelve months. However, more than half of Indonesian FSIs implementing or expanding data operations practices (56%) and data integration initiatives (61%) were doing so without a comprehensive strategy. Around half of these respondents expressed confidence or a high level of confidence in carrying out these initiatives (46% for data operations and 53% for data integration practices).
• 74% of business decision-makers among the Indonesian respondents indicated they prioritized improving customer experience — with leveraging advanced analytics-driven initiatives to drive customer experience outcomes ranking fifth on the list of operationalizing priorities, behind other objectives such as increasing revenue growth, improving customer acquisition, and enhancing productivity gains.
• 77% of Indonesia respondents faced technology obstacles in the integration of solutions; 77% faced constraints due to legacy technology, and 75% indicated facing challenges finding suitable AI/ML/advanced analytics models.
• 37% of Indonesian respondents reported budgetary constraints as a key challenge in operationalizing their advanced analytics strategy. Within the survey population, Indonesia had the lowest average annual budget for data analytics and procurement, with a mean allocation of US$320K, compared to the mean value of US$464K.
• 46% of Indonesian respondents faced other obstacles such as a lack of cross-functional collaboration; skills and experience shortages (46%); competing business priorities (44%); a lack of appropriate data and analytics processes (39%), and a perceived lack of readiness to implement data governance practices (37%).