Credit-worthiness Prediction in Energy-Saving Finance using Machine Learning Model

Companies can form their own "ESCO model" with capitals. New opportunities that Energy Saving Company (ESCO) do was to offer PSS business model in the of Agreement (ESA) or Performance Contract (ESPC), which known as "saving back arrangement financing." ESCO contracts could free owners from new upfront investment. Unfortunately, customer's creditworthiness becoming more crucial for ESCO. Machine learning used predict clients financing processes. This research aimed develop a scoring leverage machine and life cycle cost analysis (LCCA) evaluate alternative Indonesia. Research case studies leads clearer understanding factors affect all parties' decisions implement continue project. Both considerations, technology, administration emerge this study greatly influenced participants adopt decision In contrast, both parties agreed solve credit risk constraints on indicates influences were significant than technological factor shaping decisions.