DATA PREDICTION

SPARK AI is a great solution for data prediction as the problem involves complex data over time and interactions between different user behaviours that can be difficult for people to identify.

AI can look at a variety of data, including new data sources, and at relatively complex interactions between behaviours and compared to individual history to determine risk.

Our system can also be used to recommend the best proposition that will most likely retain a valuable key for the stakeholder.

In addition, SPARK can identify the reasons why a certain user is at risk and allow authorities to act against those areas for the individual and more globally.

FRAUD DETECTION

SPARK can be used to analyse large volumes of transactions to find fraud patterns and then use those patterns to identify fraud or anomaly as it happens in real-time.

When fraud is suspected, AI models can be used to reject transactions outright or flag transactions for investigation and can even score the likelihood of fraud, so investigators can prioritize their work on the most promising cases.

The AI model can also provide reasoning for the decision to flag the transaction.

These reason codes tell the authorities where they might look to uncover the issues and help to streamline the investigative process.

Our system can also learn from the investigators as they review and clear suspicious transactions and automatically reinforce the AI model’s understanding to avoid patterns that don’t lead to fraudulent activities.

CREDIT SCORING

SPARK AI is a great solution for credit scoring using more data to provide an individualized credit score based on factors including current income, employment opportunity, recent credit history, and ability to earn in addition to older credit history.

This more granular and individualized approach allows banks and credit card companies the ability to more accurately assess each borrower and allows them to provide credit to people who would have been denied under the scorecard system including people with income potential such as new college graduates or temporary foreign nationals.

Our system can also adapt to new problems, like credit card abusers, who might have a high credit score, but are not likely to be profitable for the card issuer.

SPARK can also satisfy regulatory requirements to provide calculated reasoning for credit decisions that explain the key factors in credit decisions.

MOVEMENT DATA

SPARK systems have been proven successful at detecting anomalies in movement volume data.

This time series process looks at expected data volumes based on historical patterns. Upper and lower boundaries are also predicted based on volume variation.

This system is then used to compare real-time movement value to expected volume.

This real-time system allows authorities to be notified when movement start to spike above or fall below these boundaries so they can take action before an event takes place.

MEDIC AI

AI based solutions can be used to help hospitals make better decisions by narrowing the types of tests that are likely to be useful for a patient.

AI models can be created using volumes of patient information from healthcare systems together with data from pharmaceutical companies to predict likely test results a given patients.

This model is then deployed into an AI-driven application that can provide indications of which tests are likely to produce definitive or valuable results based on the patient’s medical history and current symptoms.

With this knowledge, the doctors can pursue treatments with the best outcomes and minimize the number of tests, which saves time and reduces costs to the patient.