Developments in digital technology are altering the direction of\ncredit scoring management within the processes of data verification and\ncredit risk assessment for prospective customers. Automation and big\ndata analytics are assisting credit information management institutions\n(LPIP) or credit bureaus in providing faster and more accurate\nassessments of customer eligibility, thereby accelerating credit\ndecision-making.<\/p>\n
Credit Bureau Indonesia (CBI), acting as a credit bureau company, is\nalso utilising digitalisation to provide more accurate credit data. This\nincludes debt history, credit transactions, and payment transactions,\nwhich can be utilised by lenders such as banks, fintech firms, P2_P\nlending platforms, and multi-finance companies.<\/p>\n
The President Director of Credit Bureau Indonesia (CBI), Anton K.\nAdiwibowo, stated that technology has transformed credit scoring from\nbeing solely based on historical data to incorporating credit behaviour\ncombined with alternative data. Furthermore, the use of machine learning\nin data processing results in superior risk profile data.<\/p>\n
CBI is encouraging the large-scale utilisation of credit data through\nmachine learning via its credit intelligence platform solution. This\nallows organisations, such as credit providers, to collect, process, and\nutilise credit data for making decisions regarding a customer\u2019s credit\nrisk.<\/p>\n
How is the credit scoring revolution and the use of credit\nintelligence unfolding in reading customer credit risk profiles? For\nmore details, see the dialogue between Shafinaz Nachiar and the\nPresident Director of Credit Bureau Indonesia (CBI), Anton K. Adiwibowo\non Profit, CNBC Indonesia (Monday, 21\/09\/2026).<\/p>", "url": "https:\/\/jawawa.id\/newsitem\/video-the-credit-scoring-revolution-how-technology-evaluates-customer-profiles-1789973498", "image": "" }, "sponsor": "Okusi Associates", "sponsor_url": "https:\/\/okusiassociates.com" }