Tale of Data use cases in Insurance
How can we solve the problem of unclaimed contracts in banks and insurance companies?
The escheatment of bank accounts and life insurance policies is a technically complex subject for a number of banks and insurers to master. Some of them have recently been heavily sanctioned by the ACPR.
Why such penalties?
Under the Eckert Act, banks and insurance companies are required to draw up a list of dormant accounts and policies. This means that the relevant departments of these establishments must seek out and inform account holders and beneficiaries within the legal deadlines.
In practice, however, this search is not very fruitful. To maximize the chances of cross-fertilization, quality, up-to-date data is required. And that's where the research work gets really tricky. The key problem is to process the data appropriately to obtain reliable results.
To achieve this, the application of a research method is essential, as is the implementation of specific tools to comply with the Eckert Law. Technological solutions now exist that enable data to be matched with precision.
1. The state of the escheat market in France
The phenomenon of escheated contracts is proving to be of greater and longer-lasting magnitude than initially estimated when the Eckert law was passed in 2016. As a reminder, at the end of 2017, Caisse des Dépôts Consignations (CDC) had €4.7 billion in unclaimed contracts.
1.1 Limitation periods under the Eckert Act
Unclaimed assets are transferred to CDC by banks and insurance companies after a certain period of time.
When no transactions have been carried out on a bank account for twelve consecutive months and the account holder has not contacted the bank, or when the account holder has died and the beneficiaries have not asserted their rights within a period of one year following the death, the bank or insurance contract falls into escheat status. Normally, banks and insurers are obliged to keep escheated contracts in their management systems for several years. During this period, they are obliged to find the policyholder or beneficiaries. The period is five years for savings books, term accounts, securities accounts and PEEs (company savings plans). The limitation period for life insurance contracts is ten years. Once this period has elapsed, the funds from escheated contracts are transferred to the Caisse des Dépôts et Consignations. The latter must then keep them until the end of the thirty-year prescription period. Once thirty years have elapsed, and no claim has been made by the policyholder or his heirs, the unpaid funds are definitively transferred to the State.
1.2 The total amount of unclaimed contracts is growing steadily
The Eckert law is clear on the role to be played by banks and insurance companies. Since some major banks and insurance companies were nailed by the ACPR, many of them have been looking for effective solutions to reduce their number of escheated contracts. Despite these efforts, by the end of 2020, Caisse des Dépôts et Consignations had received 54,898 escheated life insurance policies worth a total of 172 million euros. Overall, since the adoption of the Eckert law, the amount of unclaimed escheated contracts has been exceptional. All bank and insurance products combined represent more than €6.4 billion, which CDC is required to keep for 30 years.
2. Why are so many contracts unclaimed?
Lapsed policies are policies that have not been claimed or paid out to the policyholder or beneficiaries when the policyholder dies. There are a number of reasons for these unclaimed contracts:
The insured has died and the heirs to the policy have not contacted the bank or insurance company to obtain payment of the capital.
The contract has expired and the policyholder has not requested payment of the subscribed capital.
The insured has died and his or her contact details are incorrect or missing: the insurance company cannot pay out the policy capital.
It should be pointed out that the bank or insurance company is not always informed of the policyholder's death.
In the first instance, it is up to the policyholder's family and friends to inform the bank or insurer in the event of his or her death.
Secondly, banks and insurance companies are responsible for identifying deceased customers.
To do this, they can query the databases of the Répertoire National d'Identification des Personnes Physiques (RNIPP), which specifies whether a person is alive or deceased. The point of entry into this file is AGIRA (Association pour la Gestion des Informations sur le Risque en Assurance), at the request of the insurance company or heirs.
However, the task is not an easy one, as the data coming from the management departments of banking or insurance establishments is not homogeneous. This data is often unreliable, with input, typographical and transcription errors. With the right technological solution, these errors are intelligently processed by upstream algorithms.
3. The question of data quality
Data quality is at the heart of the problem of escheated contracts. To successfully cross-reference data, it is important to have relevant, exhaustive and accurate data. From the outset, the information in the management systems of banks and insurance companies must be corrected.
3.1 Types of error
Very often, the most widespread types of error are of a spelling nature, due to typing errors for example (inversion of two letters, acronyms, inadvertent or deliberate misspellings, etc.). A name can be written in two different ways, but the similarity of the two spellings is difficult for a computer to manage. There are also other types of data that cause cross-referencing problems. These include address abbreviations (av. for avenue) and dates (87 for 1987).
The difficulty in matching data lies in the ability to homogenize each piece of data using intelligent parameters. However, the presence of inaccurate data in the information transmitted during queries carried out by AGIRA does not produce satisfactory results. The solution is therefore to make corrections and enhancements directly in the internal management systems of professional players.
Covering a wider perimeter or proposing corrections to all fields, such as surnames, first names and addresses, helps to strike a balance between the quality of the corrections made and the number of data to be cross-referenced.
3.2 Phonetic or measurement algorithms
To achieve this, it is necessary to set up a system of algorithms capable of performing the join between two data tables by matching on several flow columns. It would even be interesting to develop a fuzzy matching algorithm directly from the RNIPP database.
Generally speaking, the phonetic algorithm and the measurement algorithm are two approaches that can identify various errors (name variants, name inversion, insertion or deletion of punctuation, spaces, special characters, different spelling of names, e.g. 'Jon' for 'John', etc.).
Data quality within banking and insurance management systems is essential to optimize the process of identifying the beneficiaries of escheated policies.
4. Finding the right technological solution for managing escheated contracts
4.1 Penalties for non-compliance with the Eckert Act
Non-application of the Eckert law is severely punished by the ACPR. At the end of May 2022, the bank Natixis Interépargne was fined 3 million euros by the regulator for its faulty recognition system. In fact, it had used the Insee death database, the historical data for which ended in 2014. Nor did it cross-reference with the RNIPP database. It also largely reactivated inactive accounts by mistake. This was based on the return of letters sent to account holders as undelivered mail.
A month earlier, the ACPR had imposed a record fine of 8 million euros on the insurance company Mutex. The regulator criticized the company for a series of failings in its management of pension contracts, notably the lack of action in the search for beneficiaries of escheated contracts. The insurer had put in place a number of tools that did not enable it to respond to the problems.
4.2 The Tale of Data solution
To avoid this kind of costly malfunction, Tale of Data has developed a correction solution to improve the quality of raw data. Its application makes it possible to match names using the phonetic algorithm, and to remove special or unnecessary characters such as "né", "épouse", etc. Unwanted punctuation or spaces can also distort your search. Our tool eliminates these errors and standardizes your data, whatever the format, typology or size. In fact, this new-generation solution, integrated into our Tale of Data software, outperforms other competitive solutions.
Thanks to the data cleansing operation, our algorithm can then perform cross-referencing operations and facilitate their integration.
This process is ideal for matching the names of people in your database with other internal or external databases, by comparing approximate matches. Our matching tool enables you to match information based on pre-defined parameters, weighted according to the interest you wish to give them.
4.3 A typical example that the Tale of Data solution effectively solves
To demonstrate the effectiveness of our solution, here's a typical example of a recurring problem in finding the owners or beneficiaries of escheated policies. In one of your files, you have a person named Malorie Jullien-Dunes. However, she doesn't exist anywhere else. With our tool, the algorithm will look for approximate matches and propose several: Malaurie Jullien-Dunès and Malaurie Julien. Other criteria will enable you to refine these results by comparing date of birth, names of beneficiaries if any, address, etc.
For more information, you can send us some data for a test with our solution.