Improving npl collection rates with phone number intelligence

About Prelios
phone number intelligence One of the leading Italian non-performing loan platforms with a proven track record spanning the last thirty years, the Prelios Group is a pioneer in alternative asset management, credit servicing, and integrate real estate services. The company has emerge as one of the most prominent European NPL investors and providers of distresse asset management services to financial institutions across the continent.

With a staggering 40 billion euros in assets under management (AUM), 700+ employee and affinity for innovation, the company is positione to have a detaile vision of industry trends and growth forecasts that assists Prelios in its decision- making processes, investment strategy planning and the mitigation of risk.

The Challenge

As banks continue to de-risk and offload non-core loan portfolios, including non-performing loan (NPL) portfolios, numerous transactions have been close on the distresse loans market over the last decade.
The increase supply of non-performing loans portfolios gave rise to financial investors seeking new investment opportunities in the albania phone number list asset class, as well as to specialize debt collection companies carrying out actual debt collections.

albania phone number list

Within the NPL universe, unsecure retail loans to private individuals are typically those transacting at a lower price points due to no collateral and higher statistical write-off rates. These portfolios typically depend on the depth and quality of contact data, with the likelihood of loan recovery being positively correlate with reachability. As a leading Italian credit servicer, Prelios was no exception. With their high value of NPL portfolios under management and the looming challenge of contact validation, the risks of inaccurate data were all too real as invalid contact data could lead to faile collections, misguide strategy decisions, and significant financial losses.

While aiming to achieve optimal loan collection results for unsecure retail loans, Prelios face great challenges in confirming the validity of contact data and reachability of phone numbers associate with their recovery cases.

The Solution

Inhouse credit collection teams and specialize NPL servicing companies typically rely on numerous data sources to here’s how we deal with angry customers on the phone verify contractual, credit registry and real-estate data. However, when recovering unsecure loans to private individuals, these existing sources often fall short of actually verifying that contact data on file is valid. As reachability is the only intrinsic “collateral” these portfolios have, verification of contact data is of utmost importance.

As a way to enhance their loan collection processes and validate reachability, Prelios use Trustfull’s passive identity verification solution powere by digital footprints. The algorithm combines digital signals from various sources to paint a more complete picture of customer data validity and implie risk level, allowing Prelios to make better decisions.

Trustfull’s powerful identity scoring algorithm can reliably spot irregularities in customer information by assessing digital signals such as:

Phone number status

Indicates if the azb directory number is valid and connecte
to the network (and reachable)

Carrier Detection

The current network operator name of the
inspecte phone number

Disposable number check

Flags single-use disposable numbers available
on the black market

Porting history

Indicates if the number was porte from its
original network to a different network

Connecte chat apps

Shows in the number is registere with
popular messaging apps

Connectd accounts

Shows if the number is use on popular
online marketplaces and services

When collate together, these data signals paint a risk-picture about the phone number Prelios has on file, allowing them to identify reachable numbers where contact is likely to be establishe with the debtor.
In the opposite case, Prelios can now be instantly aware of cases where reachability can’t be ensure due to low phone score, and process these cases differently in accordance with their policies.

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