Capitalizing on the digital revolution, companies are transitioning from traditional finance models to ones that use machine learning and AI. This allows them to create personalized offerings, acquire customers more expediently, and provide exceptional customer experiences. With technology acting as a catalyst, businesses can gear up for success in an intensely competitive market while providing their customers with limitless possibilities.
As the financial services industry continues to evolve, companies need to be able to make better decisions based on data from multiple sources. At ADI, we use AI and machine learning technologies to help you create a foundation for decision-making that is constantly scrutinizing ahead.
To help our clients in both the private and public sectors stay ahead of the curve, we offer AI-driven solutions to reinvent business models, solve challenges, and monetize data securely. Our expertise enables financial institutions to leverage their data for improved operational efficiencies, risk management optimization, and increased revenue. We are dedicated to partnering with our customers so they can thrive amidst a dynamic environment while reaching their desired objectives.
Who We Work With
Why Choose to Work With Us
Financial Services Solution Offerings
Risk Management
Operational Efficiency
Revenue Optimization
Parlay is a secure data exchange platform that enables limitless data sharing, perpetual ownership and granular access rights to the data by the data product owner. An integrated data science platform designed for faster access to datasets from a wide range of sectors, Parlay offers users a unique ecosystem for data insights. #ParlayData into infinite possibilities.
As the core platform technology provider for Parlay, Harbr helps connect Aboitiz business units, people, and data, to share and collaborate at scale, unlocking new value and insights. Harbr’s technology allows ADI to manage the data product lifestyle across the network where full control and auditability is granted. With the ability to automate data sharing agreements, enable secure multi-party collaboration, connect disparate datasets and ultimately generate new insights, ADI can help your organization build a data sharing platform just like Parlay.
Interested in building your own data sharing platform?
Case Studies
Transaction Monitoring (Financial Crime)
ADI’s Transaction Monitoring solution is designed to enhance alert management by improving the accuracy of alert detection while simultaneously reducing the number of false positives.
Leveraging advanced data science and AI methodologies, ADI has developed a machine learning model that scores alerts based on patterns seen in the current data. It enables the setting of a threshold for auto-disposal based on risk appetite, which reduces the need for manual review. The model is continuously learning to detect anomalous behaviors and suspicious activities with a higher degree of accuracy than rules-based systems.
ADI’s approach to transaction monitoring complements existing solutions and offers many benefits, including:
Improved Financial Crime Detection
Higher quality STRs to regulators
Increased Efficiency
Reduced operational costs due to auto-disposal of alerts
An AI Layer Without Disruption
Hybrid approach of rules-based systems and AI complements existing alert management processes, reducing the need for disruptive changes.
Alternative Scoring for SME Lending
ADI’s Alternative Credit Scoring solution enables lenders to reach a wider customer base by identifying creditworthy borrowers who may not meet traditional credit requirements.
At ADI, we use innovative data science and AI methodologies to leverage non-traditional data from publicly available sources, government data, partners, as well as data sourced directly from clients. Our machine learning models identify significant alternative data points and patterns that effectively measure credit risk, delivering a more inclusive and accurate approach to assessing creditworthiness.
ADI’s approach to credit scoring powered by machine learning models benefits both lenders and borrowers: