IT Leader, mLeasing
Orchestrate, Automate, and Manage
Complex, Long-running Decisions
1:1 Personalization and Engagement
Design your Next-Best-Action (NBA), Next-Best-Conversation (NBC), and Next-Best-Offer (NBO) with an outcome-driven approach around your business decisions. Then orchestrate the data, machine learning around the decision model. Use AI-powered arbitration to ensure the decisions are optimized for the personalized engagement across all channels in real time at scale. Guarantee the ROI, clarity and transparency based on Decision Model and Notation with Conformance Level 3.
Product Eligibility
Assess product eligibility of borrowers for specific product requirements based on multiple criteria, including their financial strength and credit history involving tens of thousands of decisions.
Advise borrowers on loan and credit options to satisfy their very individual needs. Ensure accuracy and consistency of the offers are maintained across all processes, applications, and channels.
Loan Origination Process
Map out the entire loan origination process including thorough due diligence of borrowers, underwriting and a complete risk assessment scoring, loan approval, and loan creation and disbursement and ensure straight-through processing. Make more objective, traceable, and transparent decisions and processes.
Data Quality and Validation
Data quality and validation can be defined and executed based on different business requirements and use cases across credit, risk, and lending process. Assess and validate if a customer’s personal data, earnings, and expenses fall within the acceptable range. Ensure the provided documents and information are valid and sufficient.
Credit and Lending Decision
Combine customer information and multiple sources of data; model credit, lending, and risk decisions; and determine the creditworthiness of an applicant based on calculations, formula, and business rules.
Credit Scoring
Build credit scoring models, deploy and run these score cards against different scenarios to decide on the accurate and appropriate customer scores and product offers. Fully assess credit risk for decisions made across entire credit lifecycle considering a cross-portfolio view and different scenarios.
Loan Lifecycle Management
Automate and manage decisions regarding questions and forms as well as and the priority of activities and tasks across the entire loan lifecycle right from converting leads to applications to loan origination process to managing post-closing application activities.
Pricing and Rating
Determine an accurate and personalized price covering the administrative cost of loan, credit score, repayment risk score, risks of a particular product type using the combination of machine learning-powered and rule-based aspects to build pricing models with maximum accuracy and transparency.
Fraud and Money Laundering Prevention
Detect and prevent fraud by analyzing large amounts of data across multiple IT systems and make situation-aware decisions. Combine predictive (data-driven decisions using AI/ML) and prescriptive (rule-driven decision) analytics to identify and prevent fraudulent transactions. Also, build robots that automate decisions using decision robotics.
Debt Collection – Calculation
Build a decision model for complex debt-to-income calculation involving multiple steps, as a single source of truth across multiple processes and systems. Also, ensure compliance with regulations and rules are simple, consistent, and transparent.
Case Study
mLeasing, a leading European leasing company delivering even complicated products with frequently changing multiple parameters, much faster.
Case Study
mLeasing, a leading European leasing company delivering even complicated products with frequently changing multiple parameters, much faster.
Clarity and Transparency in your regulated environment with proven ROI.
Composite AI model that combining business rules, machine learning, computational logic and data.
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