Account opening and card issuing

Open more of the accounts you already attract

Your digital onboarding is the first real conversation with a new customer. If the offer is generic, the form is long or the credit check takes days, good applicants leave before they finish.

You also have to decline the right people. Identity checks, KYC and anti-money laundering rules apply to every application, and a model that rejects good customers costs you the revenue you spent to acquire them.

How account opening and card issuing works

Your team builds the models in H2O Driverless AI and runs them alongside the onboarding journey and decision systems you already run.

Step 1: join your onboarding data

Start with past applications, the offers shown, what each applicant chose, where they dropped off, and how the account performed after opening. Add credit bureau and internal relationship data where your policy allows.

Step 2: predict the right offer

H2O Driverless AI trains classification models that predict which account or card each applicant is most likely to take up and keep, so the first offer is the one that fits.

Step 3: check credit in real time

Credit models score the applicant's background during the application, using feature engineering across many data sources. Reason codes explain each decision, so your credit and compliance teams can review it.

Step 4: predict drop-off and early churn

Behavior models predict where an applicant is likely to stop and which new customers are likely to leave in the first months, so your digital team can simplify a step, prompt the next action or follow up.

Step 5: keep identity checks explainable

Identity and KYC models flag applications that need a closer look, with reason codes that support your KYC and anti-money laundering obligations.

Where the models run

The models run in four deployment options: on-premises, air-gapped, private cloud and cloud, so applicant data stays in the environment you choose.